Optimization of Gearshift Strategies using Road...

Optimization of GearshiftStrategies using Road

Information31st July, 2006

Anders Gaasedal Christensen, s001407

Master’s thesis30 ECTS-point

SupervisorsNils Axel Andersen & Ole Ravn

Ørsted•DTU, Automation

Technical University of DenmarkDK-2800 Kongens Lyngby, Denmark

Cover picture: http://imagebank.vtc.volvo.se- Dynafleet illustration & I-shift V 2512 AT Gearbox

Abstract

Research has intensified in the area of utilizing road information in controlof heavy trucks.

The demand for fast transportation of goods is rising and this forces thetrucks to keep a high cruising speed on the roads. In addition to this, heavytrucks are consuming an enormous amount of fuel. Saving energy - evena few pro mill would therefore be of great importance to the actors in thetransportation sector, as well as society in general.

This master’s thesis describes the task of optimizing gearshift strategiesusing road information. The aim is to increase the cruising speed and lowerthe fuel usage.

The project concerns two main parts. Firstly a feasibility study combinesGPS and a three dimensional road map, and secondly a simulation modelto investigate the performance of the improved controllers.

The feasibility study shows that it is possible to use this information toread the road ahead of the vehicle, and make a decision to shift gears.

The simulation model shows that it is possible to increase the averagespeed of a truck with more than 1% dependent of the road profile. Itfurther shows that if the speed is increased with 0.5%, it is possible to savemore than 1% fuel, decrease gearshifts significantly and increase minimumclimbing speeds.

Keywords: Automatic Gearbox Optimization, Road Information, GPS,GIS, Map Matching, Truck Model, MVEM.

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Preface

This thesis completes my studies for at Master degree in Electronics.The project has been conducted at Ørsted•DTU, Automation at theTechnical University of Denmark, supervised by Associate Professor NilsAxel Andersen, and Associate Professor Ole Ravn.

The project has been carried out in the period from the 1st of February -2006 to the 31st of July - 2006.

The work load is 30 ECTS point.

31st July, 2006, Ørsted•DTU, Automation, Lyngby

Anders Gaasedal (s001407)Email: [email protected]

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Acknowledgement

I express my gratitude to all the people who have contributed with valuablehelp and information through the project.

First of all thanks to my two main supervisors, Nils Axel Andersen andOle Ravn.

Thanks also to the Foreman, Jan Meyer Petersen at Volvo Truck CenterDenmark A/S, who have contributed with valuable data and backgroundinformation for the development of model and controller.

Thanks to Associate Professor Elbert Hendricks who has placed a largeeffort within the development of the diesel engine model specially adaptedfor this project.

Thanks also to Associate Professor Niels Kjølstad Poulsen at IMM •DTU for guidance in the use of Rule Based Control and Model PredictiveControl.

Thanks to Erik Hellstrom, Ph.D. Student at the division of VehicularSystems at the department of Electrical Engineering, Linkoping University,who have provided me with authentic road data for simulations.

At last, I want to thank my father Niels Nielsen, truck driver at thehaulage company Gustav Larsen & Son A/S who described the problem tome at first, and has contributed with valuable real life test data through theproject.

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Contents

1 Introduction 11.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.2 Volvo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.3 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . 3

1.3.1 Approach . . . . . . . . . . . . . . . . . . . . . . . . . 31.3.2 Expected Goals . . . . . . . . . . . . . . . . . . . . . . 31.3.3 Delimitations . . . . . . . . . . . . . . . . . . . . . . . 41.3.4 Advantages and Disadvantages . . . . . . . . . . . . . 4

1.4 Outline of the Report - Readers Guide . . . . . . . . . . . . . 51.5 Applied Software . . . . . . . . . . . . . . . . . . . . . . . . . 6

2 System Description 72.1 Existing Parts . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.1.1 Dynafleet Online . . . . . . . . . . . . . . . . . . . . . 82.1.2 I-shift . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

2.2 Project Components to be Developed . . . . . . . . . . . . . 112.2.1 Implementation . . . . . . . . . . . . . . . . . . . . . . 112.2.2 Flow Chart . . . . . . . . . . . . . . . . . . . . . . . . 12

3 Current Drive Optimization Systems 133.1 Speed Control . . . . . . . . . . . . . . . . . . . . . . . . . . . 143.2 Gearbox Control . . . . . . . . . . . . . . . . . . . . . . . . . 163.3 Engine Control . . . . . . . . . . . . . . . . . . . . . . . . . . 173.4 General Vehicle Control . . . . . . . . . . . . . . . . . . . . . 183.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

4 Road Information 214.1 GPS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

4.1.1 Communication with the Receiver . . . . . . . . . . . 224.1.2 GPS Parser . . . . . . . . . . . . . . . . . . . . . . . . 224.1.3 Latitude and Longitude to UTM Coordinates . . . . . 234.1.4 User Interface . . . . . . . . . . . . . . . . . . . . . . . 23

4.2 GIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

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4.2.1 TOP10DK . . . . . . . . . . . . . . . . . . . . . . . . 254.2.2 KMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274.2.3 Map Based on GPS Measurements . . . . . . . . . . . 294.2.4 Laser Scan . . . . . . . . . . . . . . . . . . . . . . . . 304.2.5 Authentic Road Data from Sweden . . . . . . . . . . . 31

4.3 Map Matching . . . . . . . . . . . . . . . . . . . . . . . . . . 314.4 Road Profile . . . . . . . . . . . . . . . . . . . . . . . . . . . . 334.5 Test of GPS/GIS System . . . . . . . . . . . . . . . . . . . . 344.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

5 Truck 375.1 Real Truck - Volvo FM9 - 380 . . . . . . . . . . . . . . . . . . 38

5.1.1 Specifikations . . . . . . . . . . . . . . . . . . . . . . . 385.1.2 Reference Tests . . . . . . . . . . . . . . . . . . . . . . 395.1.3 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . 43

5.2 1st Model - Simple . . . . . . . . . . . . . . . . . . . . . . . . 445.2.1 Engine . . . . . . . . . . . . . . . . . . . . . . . . . . . 455.2.2 Automatic Gearbox . . . . . . . . . . . . . . . . . . . 475.2.3 Rearaxle/Wheels . . . . . . . . . . . . . . . . . . . . . 485.2.4 Vehicle . . . . . . . . . . . . . . . . . . . . . . . . . . 485.2.5 Input - Real Road . . . . . . . . . . . . . . . . . . . . 505.2.6 Cruise Control . . . . . . . . . . . . . . . . . . . . . . 505.2.7 Output - Data/Gauges . . . . . . . . . . . . . . . . . . 515.2.8 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . 52

5.3 2nd Model - Advanced . . . . . . . . . . . . . . . . . . . . . . 525.3.1 Engine . . . . . . . . . . . . . . . . . . . . . . . . . . . 535.3.2 Clutch . . . . . . . . . . . . . . . . . . . . . . . . . . . 635.3.3 Gearbox . . . . . . . . . . . . . . . . . . . . . . . . . . 645.3.4 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . 65

5.4 Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 675.4.1 Fuel Usage . . . . . . . . . . . . . . . . . . . . . . . . 675.4.2 Climbing Capacity . . . . . . . . . . . . . . . . . . . . 675.4.3 Acceleration . . . . . . . . . . . . . . . . . . . . . . . 67

5.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

6 Controller 696.1 Reference Data . . . . . . . . . . . . . . . . . . . . . . . . . . 70

6.1.1 Truck Data . . . . . . . . . . . . . . . . . . . . . . . . 706.1.2 Driver Inputs . . . . . . . . . . . . . . . . . . . . . . . 70

6.2 Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 716.2.1 Truck States . . . . . . . . . . . . . . . . . . . . . . . 716.2.2 Road Sequence . . . . . . . . . . . . . . . . . . . . . . 71

6.3 Outputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 716.4 Controllers . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

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6.4.1 Normal - Reference . . . . . . . . . . . . . . . . . . . . 726.4.2 Simple - Economy/Power . . . . . . . . . . . . . . . . 726.4.3 Rule Based for 1st Model . . . . . . . . . . . . . . . . 736.4.4 Rule Based for 2nd Model . . . . . . . . . . . . . . . . 73

6.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

7 Tests and Results 797.1 Road Information . . . . . . . . . . . . . . . . . . . . . . . . . 797.2 Controllers . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

7.2.1 Comparison Test . . . . . . . . . . . . . . . . . . . . . 817.2.2 Detailed Test of Final Controller . . . . . . . . . . . . 87

7.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

8 Discussion 938.1 Road Information . . . . . . . . . . . . . . . . . . . . . . . . . 938.2 Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94

9 Conclusion 97

10 Future Work 99

Nomenclature 100

Bibliography 107

List of Figures 111

List of Tables 115

A Models 117A.1 1st Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118

A.1.1 1st Model - Main . . . . . . . . . . . . . . . . . . . . . 119A.1.2 1st Model - Engine . . . . . . . . . . . . . . . . . . . . 120A.1.3 1st Model - Gearbox . . . . . . . . . . . . . . . . . . . 121A.1.4 1st Model - Differential, Brakes and Wheels . . . . . . 122

A.2 2nd Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123A.2.1 2nd Model - Main . . . . . . . . . . . . . . . . . . . . 124A.2.2 2nd Model - Engine - Main . . . . . . . . . . . . . . . 125A.2.3 2nd Model - Engine - Fuel . . . . . . . . . . . . . . . . 126A.2.4 2nd Model - Engine - Turbo . . . . . . . . . . . . . . . 127A.2.5 2nd Model - Engine - Crankshaft . . . . . . . . . . . . 128A.2.6 2nd Model - Clutch . . . . . . . . . . . . . . . . . . . 129A.2.7 2nd Model - Gearbox . . . . . . . . . . . . . . . . . . 130A.2.8 2nd Model - Differential, Brakes and Wheels . . . . . 131

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B CD 133B.1 Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133

B.1.1 Report . . . . . . . . . . . . . . . . . . . . . . . . . . . 133B.1.2 Road Information . . . . . . . . . . . . . . . . . . . . 134B.1.3 Truck Model . . . . . . . . . . . . . . . . . . . . . . . 135

B.2 CD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137

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Chapter 1

Introduction

Nowadays, automatic gearboxes have become more and more normal inheavy trucks. The two most important reasons for this is the improvement ofdrivers comfort and more economic driving. Most drivers are happy to avoidhundreds of gearshifts through a working day, and the haulage contractorsare happy to know that the trucks are driven in the most economical way.However, automatic gearboxes suffers from not being able to read the roadlike the real driver. That makes automatic gearboxes inferior to a normaldriver with a manual gearbox in hilly conditions with steep gradients.

A normal driver reads the road, and decides if it is possible to reach thetop of a hill in that particular gear without loosing a lot of speed, or if itwould be more efficient to make a shift down immediately before the gradientto give the engine more torque for climbing the hill, and maintain a higherspeed on the gradient. The normal automatic gearbox often handles thissituation by using the top gear, trying to climb the hill, and waiting to shiftuntil the engine RPM1 drops below a certain limit. That causes the truck tolose a lot of speed, and makes it necessary to make the gearshifts when thedemand for torque is at its highest. Thus the drivers normally chooses toswitch to manual gear control and select the best gear immediately beforea certain gradient; thereby making use of the full potential of the enginetorque on the whole gradient.

Automatic gearboxes for trucks are very expensive, and every time thedriver chooses to select gears manually it can be conceived as a waste ofmoney to have bought an automatic gearbox. Since the driver believeshe/she can make a better selection of gears than the computer, he/she mustbe using some senses or earlier experiences that the computer does not haveaccess to. The aim of this project is to develop a system for automaticgearboxes to get closer to the behavior of an experienced driver.

1Revolutions Per Minute

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1. Introduction 1.1. Background

1.1 Background

The background for this project has been formed by several driving hourswith my father who is a truck driver. The truck he has been driving forsome years is equipped with the new automatic gearbox from Volvo, theI-shift system, which will be explained in detail in chapter 2. This gearboxis mostly a normal manual gearbox but controlled by a computer instead ofthe driver. The gearbox is very good at selecting the correct gear comparedto the load of the truck, the speed and engine RPM. Unfortunately it is notcapable of reading the road as the driver can.

The problem has been in my thoughts for some time, how to solve theproblem and make the gearbox capable of selecting the gears in a more ef-ficient way according to the profile of the road ahead of the truck. Severalideas for using different sensors have been considered in order to find a pos-sible solution. When the idea of using an integrated GPS2 system togetherwith a 3D digital map of the road came up, contact were established tosupervisors at DTU to determine if it could be the subject for my mas-ter’s thesis, and another contact were established to the Volvo PowertrainCooperation to ensure that the idea might be useful.

As described earlier I had access to a Volvo truck with an automatic gear-box, and the amount of possible equipment to a Volvo truck, including anonline transportation system3 and a GPS system. These factors determinedto base this project on the Volvo system.

Other large truck manufactures like SCANIA AB, Mercedes-Benz,M.A.N. AG are also using and developing automatic gearbox systems, whichare somehow similar to the Volvo system.

1.2 Volvo

Volvo was founded in 1927 and in 1928the first Volvo truck rolled off the pro-duction line, at that time a pioneer onthe market, shaft driven (compared toother trucks with chain drive), pneu-matic tyres (solid rubber tyres were nor-mal at that time) and a fully enclosedcab.

Through the years Volvo has beena pioneer in many areas. In the 1950sVolvo was the first to use turbochargedengines, and in the 1960s Volvo introduced tiltable cabs for easier access to

2Global Positioning System.3The Volvo ’Dynafleet Online’ system, will be explained in chapter 2

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1. Introduction 1.3. Problem Statement

the engine. Nowadays Volvo is still in the front rank of truck production byresearching many areas for improving the trucks, including drivers comfort,environmental-, safety- and economical aspects, etc.

The idea for solving the problem in this case includes several of theseadvanced techniques, some of which are already implemented in the Volvotrucks today (to be explained in chapter 2), and the opportunity for testingthe system or later implementation will be natural using the Volvo systemas background.

1.3 Problem Statement

The project is a result from own experiences with automatic gearboxes,and several statements from truck drivers complaining about the inabil-ity of an automatic gearbox to read the road, [Magazine, 2006b] and[Magazine, 2006a]. Thereby the problem statement can be defined as:

Develop a system that is capable of improving the gearshift strategiesfor automatic gearboxes by reading the road and selecting the optimal gearsequence for particular gradients.

The system will include a combination of GPS and GIS4 to obtain knowl-edge of the road in front of the vehicle, and thereby select the optimal gearsequence and the time of shifting. The gear sequence should be chosen bycombining the road data and the characters of the vehicle, engine, load,speed, etc.

1.3.1 Approach

The project initiates with an investigation of the GIS/GPS system: whetherit is possible to use such a system, and which parts are available on the mar-ket. Afterwards the project continues with the development of a simulationmodel, to be able to simulate the behavior of a truck, driving a road withgradients. The output of the model is likely to be the speed of the truckand the fuel consumption, these are the main areas of concerns.

The model will at first be adapted to fit a real truck driving on realroad conditions, and then extended with a new gearbox controller to give anatural view of the eventually gained performance.

1.3.2 Expected Goals

The project has several expected goals, both theoretical and practical.The theoretical aspect is to develop a simulation model that can be used

to show the behavior of a real truck, driving on both artificial and authentic4Geographical Information System - in this case, digital 3D maps.

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1. Introduction 1.3. Problem Statement

road sections. The model must also include the properties of the wholedrivetrain thereby giving the possibility of creating rules for a controller toimprove the gearshift strategies.

In the practical aspect it is important to investigate whether it is possibleto use a GIS/GPS system to control the gearbox of a truck.

The result of the simulation model also includes a practical goal since itis desirable to show a result as close to reality, to give a clear view of theadvantages and disadvantages of such a system implemented in real life.

1.3.3 Delimitations

Due to the limited amount of time, some limits have to be set for the project.The probability of making a system which can be implemented in a real

truck is impossible, since it would require an adaption of the project to fitthe system and software used in real trucks. Besides from that, a lot of testsare required to make sure it will work on a truck and not damage any partsof the truck nor make the vehicle unsafe to drive on real roads, during tests.

The investigation of using a GIS/GPS is also limited to some kind ofa feasibility study, whether it seems possible to implement and use such asystem. A fully functional system will require more data and tests than itis possible in this project.

1.3.4 Advantages and Disadvantages

The project includes several possible advantages and disadvantages usingan optimization system, here are the most important.

Advantages

Higher average speed By using the optimal gear for getting the maxi-mum torque it will be possible to increase the speed on steep gradients.

Improved fuel economy It should also be possible to get an overall fuelsaving in some cases even though the gearbox is controlled for gettingmaximum torque. This is possible because the vehicle will not lose asmuch speed, and speed changes are normally uneconomical.

Improved safety in relation to other vehicles If the vehicle can main-tain a higher speed on a gradient, the difference in speed compared toother vehicles will be smaller and the risk of accidents reduced.

Less wear If gear shifts are made when the load on the drive train is small,wear will be reduced.

Better use of the automatic gearbox The automatic gearbox will beused more for automatic shifting, and the capital which is invested inthis technology will be better utilized.

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1. Introduction 1.4. Outline of the Report - Readers Guide

Improved drivers comfort The driver will be relieved of makeing somegearshifts, specially in hilly terrain. This will increase comfort.

Improved safety The driver can fully concentrate on the traffic; it is notnecessary to think about selecting the right gear.

Disadvantages

Increased gearbox wear Making more gearshifts to maintain higher av-erage speed will cause more wear in the gearbox.

Poorer fuel economy In most cases the fuel economy will be poorer, sinceit is uneconomical to run in a lower gear than the highest gear.

Price of purchase Since the system is expensive to develop it will be moreexpensive than existing systems.

Not developed for all areas If a 3D map of the road is not available, thesystem cannot work, and must rely on the standard shifting strategyinstead.

In some cases the above mentioned factors will affect each other in a positiveor negative way. Increased speed will often entail a worse fuel economy.This means, that some kind of trade off between the different aspects willprobably be the final solution. Or the final solution will be a number ofsolutions, each designed to improved different conditions.

1.4 Outline of the Report - Readers Guide

Abbreviations and terminologies used through the report are presented in athe end of the report at page 100. List of figures and tables are also to befound at the end of the report, at page 113 and page 115 respectively.

A CD is attached at the back of the report, containing the report itself,program code, and other relevant data.

References to used literature are marked with [Author, Year] whichrefers to the Bibliography on page 106

The main chapters of the report contains the following subjects:

Chapter 2 - System Description Description of the whole system intwo parts, first the current available hardware and software which thesystem should be built on top of. And second a description of how thenew parts for the system should be implemented.

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1. Introduction 1.5. Applied Software

Chapter 3 - Current Drive Optimization Systems A summary anddescription of currently implemented or tested drive optimization sys-tems which uses road information to improve the control of engine,speed, gearshifts, etc.

Chapter 4 - Road Information In this chapter an investigation ofprocuring a usable 3D road map for this purpose has been carriedout, both in the matter of using existing data and also with respect tocreating maps from scratch with a GPS receiver.

Chapter 5 - Truck This chapter describes the development of a detailedtruck model used for tests and simulation of the entire system.

Chapter 6 - Controller Three different controllers for this system havebeen developed and tested in this project, the normal system, a simpleimprovement, and the final solution. Using more or less of the availableroad data.

Chapter 7 - Test Tests and simulations of the system are presented inthis chapter, including improvements compared to current systems.

The last chapters contains the discussion of the results, conclusion, and ideasfor future work and further development of this system.

1.5 Applied Software

The development of software modules and models has been carried out ona standard PC installed with Windows XP Service Pack 2.

• MATLAB version 7.0.4.365 (R14) Service Pack 2

• SIMULINK version 6.2 (R14SP2)

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Chapter 2

System Description

This project consists of several different parts, some of which are alreadydeveloped and used in trucks, and some of which are new and developed inthis project. The project includes three main parts:

Road information which has to be communicated from the new inte-grated GIS/GPS system to the onboard computer on the truck, tomake the truck capable of using the road profile ahead for control ofthe gearbox.

Truck which is the main part to be controlled. In this project it will bea model on a computer. However if the system indicates improvedperformance the possibility of implementation in real life could beinvestigated.

Controller which by using the information above is capable of calculatingthe necessary action to be carried out, to make the shifting strategymore efficient, using the road profile ahead.

2.1 Existing Parts

As described in the previous chapter, a Volvo truck is chosen as the referencesystem, because the project will include parts that are already developed andused in Volvo trucks today. Some of those parts will not in the first attemptbe used in the project but since they are already developed, the final solutionwill not be a very expensive and totally new accessory to the trucks. Insteadit will consist of already developed parts and an extra module for linkingthese together in a new way.

What currently are useful and available at Volvo is their transport in-formation system - Dynafleet Online, and an automatic gearbox - I-shift.This project will be an extension to these two systems making use of theDynafleet Online system to control the automatic gearbox.

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2. System Description 2.1. Existing Parts

2.1.1 Dynafleet Online

Dynafleet Online is a highlydeveloped Transport Informa-tion System (TIS) from Volvo.It is developed to improvelogistics and communicationbetween the hauler and thedriver.

It includes three mainparts:

Vehicle Management which reads out the vehicle data such as fuel con-sumption, speed, RPM, etc. It also stores it and transmit it to thehauler for statistic purpose and to monitor the driver.

Driver Management which tracks the driving and working time of thedriver, to prevent violations of the legal driving time and to maintainservice intervals, etc.

Transport Management which gives the driver and hauler the positionof the truck to make it easier to plan the most efficient route. It alsoincludes a communication module between the driver and hauler. Thissystem also includes traffic reports, fuel stations, workshops etc. tohelp the driver navigate through traffic as smoothly as possible.

For this project the Transport Management part is the most important,since it includes a navigation system based on GPS and digital maps, anda communication part, to send and receive messages and data between thetruck and the hauler.

As for now, the integrated maps are in 2D, which has to be extendedinto 3D for this project. Further description of these extensions will followin chapter 4.

2.1.2 I-shift

In 2001 Volvo presented the automatic gearbox, named I-shift. This is a fully automated gearchanging system whichoffers improved driver comfort, reduced fuel consumptionand lower gearbox weight.

The gearbox is mostly a normal gearbox controlled bya computer instead of the driver. The gearbox is a 12-speed unsynchronized range1/splitter2 gearbox, and the

1Range is a High/Low gear area resulting in 6 gears from the normal 3 gears.2Split is another High/Low gear, but splitting in between gears instead. (Total 12

gears)

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computer controls the clutch and the engine for smooth up/down shifting.The computer uses different sensors for selecting the optimal gear such asthe weight of the truck, gradients for selection of start gear, etc.

To give a clear understanding of the normal shifting strategy, the mostimportant parameters are listed here in the section below.

Basic Shift Strategy

The basic shifting strategy of the I-shift program is rather simple. At launchthe gearbox calculates the most efficient gear to use as startup gear (1. - 6.gear), by measuring the weight of the truck and the gradient of the road.

When the truck is accelerating or decelerating, the computer calculatesthe most optimal gear selection. If it is convenient to shift 1,2 or 3 gears upor down, dependent on the acceleration of the vehicle. If the truck has noload, it prefers to use few gears, e.g. 6-8-10-12. If the truck is fully loadedit may use all gears 1-2-3...-11-12.

When the engine speed rises above a certain limit a higher gear is se-lected, or when the engine speed drops below a certain limit a lower gearis selected. These limits for shifting is affected by the acceleration of thevehicle and the throttle level.

Additional Strategies

A number of additional strategies can affect the selection of gears, here arethe most important.

Performance Shift Function to give faster and more gentle gear shifts byusing the engine brake, the clutch and a special transmission brake inthe gearbox.

Basic Gear Selection Adjustment The driver can select gears manuallyduring engine braking.

Enhanced Shift Strategy Improved strategies for launch and precisiondriving by controlling brakes and suspension. When gearshifts areperformed during engine braking, the wheel brakes are activated tocompensate for the lost braking moment. This improves breaking ef-ficiency and comfort.

Eco Roll Activation of a special neutral function, lowering the fuel usage.Eco Roll is used on road sections where no engine or brake power isneeded.

Smart Cruise Control This works together with the brake pilot and en-sures that the brakes are not used unnecessary. The system is intendedto disable the brakes at the end of descents and let the vehicle run a

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little faster than desired before the road levels again. In this way ituses the momentum of the vehicle.

High Torque Direct Gear In top gear the engine is allowed to produceapproximately 200 Nm more than in other gears, because the top gearis the most efficient gear. The top gear couples directly through thegearbox and therefore more efficient.

Heavy Duty GCM 3 Controller from Volvo, optimizing gearshifts forheavy trucks of more than 60 tons.

Launch Control This system helps the driver to start the vehicle on steepgradients. The breaks are applied automatically until the torque de-livered from the engine is large enough to drive the vehicle.

Economy/Power Mode

Figure 2.1:I-shift gearlever

The driver has another possibility of controllingthe behavior of the gearbox. Right behind thegear lever is a button marked E/P, referring toEconomy- or Power mode see figure 2.1.

In the Economy mode the gearshifts are exe-cuted at the most economical engine speed, whichare often rather low. In the Power mode these lim-its is moved up higher because the engine producesmore torque at higher engine speed.

The limits are moved upwards both in the shiftup and shift down case, that means if the vehicle isaccelerating it will stay longer in that gear beforethe shift. Similar when the truck decelerates be-cause it can not cope with a steep gradient, it willmake the shift down earlier, i.e., engaging the lowergear earlier. This is not always an economic solu-tion but the driver gets more power for maintainingspeed.

This is actually what this project is about. The aim of the finalcontroller is to get more power by selecting a lower gear when neededcompared to the normal shifting strategy. An idea for a simple controller isto automatically activate the Power mode when driving into hilly terrain.This will be implemented and described in chapter 6.

A combination of the already implemented gear changing strategies andsome new ones will be developed in this project to particularly improvedriving in hilly locations.

3Gross Combination Mass

10

2. System Description 2.2. Project Components to be Developed

2.2 Project Components to be Developed

To extend the normal system to be able to read the road several componentshave to be developed, either new or extensions for existing parts.

The project contains three superior parts to be developed:

Extension for the Dynafleet Online system The normal 2D position-ing system in the Dynafleet Online system has to be extended witha 3D map to make the computer capable of reading the road heightprofile ahead of the truck. This part of the project is described inchapter 4.

Truck Simulation Model For the development and evaluation of a newcontroller, a truck simulation model is needed. The model shouldreflect reality as close as possible. The model should contain parts like:engine, gearbox, drivetrain, disturbance from road, air resistance, etc.Description and implementation of the model is to be found in chapter5.

Controller The controller can be developed on the background of themodel and later evaluated on the model to investigate whether thesystem is advantageous or not. If the result is positive, and the modelcan be verified to reflect the reality, there is an incentive to implementthis controller in a real truck. Three different controllers are imple-mented two simple controllers using only a few inputs, and a moresophisticated controller using more inputs for making the decisions.The implementation and description of the different controllers are tobe found in chapter 6.

2.2.1 Implementation

The system to be developed here is implemented as depicted in the flowchartin figure 2.2.

The position of the truck on the road is found by the Road Informationpart, which contains a Map Matching algorithm that combines a GPS posi-tion with a 2D digital road map. When the position is found it is comparedto a 3D digital road map and the 3D profile of the road ahead is transmittedto the Controller.

The controller evaluates the road profile in front of the vehicle, by meansof the important physical factors such as gradient, length of gradient, etc.This result, stationary data of the truck (weight of truck, engine size, etc.)and dynamic data of the truck (speed, RPM, gear, etc.) are compared andevaluated, and it is decided if and how the gear shifting algorithm shouldbe affected. The result is transferred to the Truck model and the result ofthese decisions and the disturbances from the road the truck is ’driving’ on,

11

2. System Description 2.2. Project Components to be Developed

can be measured at the output of the model including information of thefuel usage, average speed, number of gearshifts etc.

2.2.2 Flow Chart

The flowchart is separated in the three main parts referring to the threeparts implemented in this project. Besides inputs from the three parts, themodel also includes an external input, namely the road on which the truckmodel is driving. This road is both artificial road sections and authenticroad sections.

Figure 2.2: Flowchart of system implementation intended here in-cluding Road Information, Truck Model and, Controller.

12

Chapter 3

Current Drive OptimizationSystems

Research has already been carried out within this area - automotive systems,based on optimization from 3D road maps. This chapter describes some ofthe most important investigations in this area.

The area is however rather new, because positioning systems like GPShave not been available for public before the 2nd of May 2000, when it wasdecided to remove the international degradation of the civil GPS signal1.

Since that time several manufacturers of automotive components havestarted researching in the area of using positioning systems and digitalmaps to improve different facilities in vehicles. These manufacturers in-cludes many of the large truck manufactures and manufactures of utilitiesfor trucks, these includes: Volvo, Scania, MAN, Ford, Daimler Chrysler,Cummins and Bosch. More research has been carried out at the division ofVehicular Systems at the Swedish Linkoping University and the ChalmersUniversity of Technology in Goteborg.

A Swedish report [Gustafsson, 2006] has made a collection of referencesand descriptions of different researched systems. All systems described inthis chapter, which are not cited, refer to this thesis.

The chapter is intended to give the reader an overview of the differentapplications which can be optimized using positioning system. Bits andpieces from the different applications has been used in the development ofthis project. The research mainly concentrates around 3 areas: speed-,gearbox- and engine control.

1Before that a noise signal causing errors from 0-70 meters were added to the GPSsignal.

13

3. Current Drive Optimization Systems 3.1. Speed Control

3.1 Speed Control

The most popular area for using a road information system is for predictivespeed control, via this optimization of fuel efficiency.

The speed control includes different methods, the most important arelisted here:

ACC Normal ACC2 keeps a certain distance to the vehicle in front, butsometimes it is appropriate to change that distance. MAN has testeda system which increases the speed a little near the end of a descentor near the beginning of an ascent. And similar, decreases the speed alittle before the end of a descent or the beginning of a descent, whichis claimed to save fuel.

Limiting Speed in Curves Heavy vehicles can not maintain full speed insmall radius curves, and the cruise control could therefore be modifiedby means of a positioning system. (This is normally not a problemon highways). Scania and Mazda have described a system to calculatethe maximum safe speed to negociate a curve, and thereby affect thecruise control.

Adapt Speed to Road Type The possible cruising speed is often limitedby the type of road, i.e., small hilly roads with high curvature. BMWand Aisin have tested a system based on information from a positioningsystem.

Predictive Cruise Control This is the most efficient use of a positioningsystem to find the most economical speed compared to the profileof the road ahead. That means driving like a normal experienceddriver. Increase speed a little before an ascent, and lower the speed alittle before the end of the ascent. Similarly lower the speed before adescent, and increase the speed a little before the end of the descent.

The fact that the most3 efficient way of using a positioning system isto control the speed of the vehicle with reference to the road profile,makes it the most investigated area. Two new master’s theses fromthe Swedish Linkoping University, investigate the performance possibleusing Predictive Cruise Controllers.

Explicit use of road topography for model predictive cruisecontrol in heavy trucks[Hellstrom, 2005]This project describes the implementation of a MPC4 controller for

2Adaptive Cruise Control3What investigations shows at this time.4Model Predictive Control

14

3. Current Drive Optimization Systems 3.1. Speed Control

finding the optimal speed profile to save fuel, without lowering theaverage speed. The system is tested by simulation on a real section ofa Swedish highway documented by Scania. The results shows a fuelsaving of around 2.5% without changing the average speed. The testis performed on a 40 metric tons vehicle.

The fuel savings are obtained by letting the vehicle increase itsspeeda little over the desired cruising speed before gradients, and reducingthe speed slowly until the top of the gradient is reached. Similarfor descents, the speed is decreased a little before the beginning of adescent, and slowly increased until the end of the decrease., as depictedon figure 3.1.

0 500 1000 1500 2000 2500 3000

0

10

20

Alti

tude

[m]

0 500 1000 1500 2000 2500 3000

80

85

90

Position [m]

Spe

ed [k

m/h

]

Figure 3.1: Predictive Cruise Control

Vehicle control using look ahead information [Wingren, 2005]This project is focused on the same problem as above, but the con-troller in this project is to use a set of simple rules for describing theroad profile, and make simple control rules from this. This method isclaimed to save from 1.5% to 3.4% fuel.

The Predictive Cruise Control - DaimlerChrysler[Lattemann et al., 2004]Representatives of DaimlerChrysler has made a system, also usinga 3D digital road map, and a predictive cruise control. The fuelconsumption is lowered with 4.1% - 5.2%, with an increase in travelingtime of 0.3% - 1.4%.

Predictive cruise control systems do have a large potential for savingfuel, between 2%-5% dependent on the system and the road conditions.

The disadvantage of the system, compared to traffic conditions is thefact that the system is based on variations in traveling speed, both up and

15

3. Current Drive Optimization Systems 3.2. Gearbox Control

down. This is only possible if the cruising speed is below the maximumspeed limit. Most drivers today are forced to drive as fast as possible. This isrequired both by the hauler, because ’time is money’ and because the driverwants to get home as fast as possible. Trucks are therefore mechanically(or today by software) limited to drive right below 90 km/h. This speedis then the most normal for heavy trucks on highways, whether its legal ornot. The Predictive Cruise Control is therefore only effective if it is possibleto convince the drivers to drive slower than the maximum speed.

3.2 Gearbox Control

Several projects have been carried out in order to improve the shifting strat-egy of automatic gearboxes by using some kind of road information. Below,the most interesting are listed.

Predictive Gearshift Control Volvo Trucks have described a system ina patent, (also described in the report [Gustafsson, 2006]) which usesinformation on the road ahead and calculates the optimal gear shiftstrategy with regard to driver chosen parameters, such as emissionrates, average speed or fuel consumption.

The system uses a GPS and a digital road map to predict the futureroad profile. The decisions for gear shifts is also based on severalinternal sensors in the truck. The system also includes engine, turboand transmission characteristics.

This system description is close to the problem statement of thisproject, but unfortunately it has not been possible to get access toinformation of this patent.

Driving Force Nissan has described a simple system to calculate the nec-essary driving torque on the road ahead, and from this decide whetherit is advantageous to shift gears.

Aisin has tested a somehow similar system to the Nissan system,but this system uses simple rules together with a road map to de-cide whether a gear shift is necessary and most of all fuel efficient.The system also describes a strategy to turn off accessories like air-conditioning fan and defogger when full power is needed for an ascent.

Road Grade Honda has tested a system to estimate the road grade, bycomparing the actual acceleration and the predicted acceleration, thisvariable affects the gear shifting strategy. A navigation system is usedto determine which type of road the vehicle is travelling on. Theseparameters are used to affect the shifting strategies. The drawbackof this system is that it includes no predictivity, but it shows someimprovement using the two variables above.

16

3. Current Drive Optimization Systems 3.3. Engine Control

Learn from Experience IBM has tested a special system where the op-timization is based on learning. GPS positions, gearshifts and fuelefficiency are logged when driving, and when the vehicle return to a’known’ road it learns from the previous pass. It uses this informationfor making a more efficient gearshift sequence on repeated passes.

Geographical Position Toyota has tested a system where the gearshiftsare affected by the position, if the vehicle is in residential areas, orhilly terrain.

Other Implementations Several other systems have been implementedsystems to prevent unnecessary gear shifts in corners (2D maps asreference), systems to prevent unnecessary gear shifts near obstacles(2D maps as reference) and systems to shift up if traction is too lowfor the particular gear.

Several systems has been implemented, improving the control of automaticgearboxes in different ways. Unfortunately none of them has any referenceto specific measured improvements, which makes it hard to compare theseto the results of this project. The amount of research in the area makes itclear, however that this is an interesting area.

3.3 Engine Control

Using a positioning system also gives a number of possibilities for controllingthe engine, regard to demands for torque, economy and emissions. Severaltechniques have been tested, based on different levels of detail in the availableengine map.

EGR Volvo has tested a system controlling the EGR5 valve, which is anemission control technique. By recirculation a small amount of exhaustgas into the intake of the engine, the nitrogen oxide [NOx] emissionscan be lowered. Unfortunately the EGR system decreases the outputpower of the engine. The system implemented is used to control theEGR valve before gearshifts, to avoid incomplete combustion and toincrease torque on ascents.

SCR Scania has tested a system to control the SCR6 system. SCR is anafter threatment of the exhaust gasses, where an urea-based additive(AdBlue) is injected to lower the amount of nitrogen oxides. Sincethe additive is expensive it is only possible to control the amountof injected AdBlue in accordance with different areas, geographical-or jurisdictional area restrictions. The system is not predictive and

5Exhaust Gas Recirculation6Selective Catalytic Reduction

17

3. Current Drive Optimization Systems 3.4. General Vehicle Control

therefore it does not take attempt to improve the efficiency of theSCR system during gearshifts or changes in workload.

Fuel Maps In some systems, engine outputs are controlled by a so-calledfuel map. Cummins has tested a system to use different fuel maps indifferent locations. Three fuel maps have been implemented:

Low emission - for urban areas.

Fuel economic - for rural areas.

High engine output - for hilly locations.

Valve Timing Another way of controlling the output and emission of anengine is to control the valve timing. Volvo has tested such a system.The idea is to change the operating mode of the engine to achieve highoutput or low emissions. The system is predictive and is adapted tolower emissions at gearshifts and accommodates high torque demandsin hilly locations.

Turbo Volvo has tested a similar system to that above, to control the geom-etry of the turbo or change the limit of the wastgate7 valve. In thisway it is possible to eliminate turbo delay and increase the engineoutput when it is needed.

Engine Output Cummins has tested a similar system as above, includingmore parameters to give either low emission or high engine outputdependent on location of the vehicle.

Vehicle Accessories Aisin has tested a system to control vehicle acces-sories like aircondition, defogger, fan, etc. In accordance to roaddata. When high torque is required for driving, some of these couldbe switched off.

It is clear that Engine Control can be improved by the use of positioningsystems. The primary benefits are improved fuel efficiency, less emissions,quicker response in transient conditions and engine output on demand.

3.4 General Vehicle Control

Based on a number of the above areas investigated above, a group in Swedenconsisting of employees at Scania CV AB, Sodertalje, the Royal Instituteof Technology, Stockholm, and Linkoping University are collaboration onresearch in the area of vehicle control.

7The wastgate valve opens when the maximum turbo-pressure is reached and bypassingthe turbo.

18

3. Current Drive Optimization Systems 3.5. Summary

This project [Ivarsson et al., 2006] is part of a large project named IVSS8

to improve the safety of driving vehicles. The vehicle control project includesseveral subsystems like the systems mentioned above.

3.5 Summary

From the above it is clear that it is possible to improve vehicle control inmany ways using digital road maps with more or less detail. In the abovesections, different applications are presented separated in three main partsSpeed Control, Gearbox Control and Engine Control. These three areas areimportant, specially in commercial vehicles like heavy trucks. On figure 3.2the most important applications is listed according to the available detailsin the digital map.

Figure 3.2: Application for GPS/GIS aids in vehicles, according tothe amount of detail available in digital maps.

8Intelligent Vehicle Safety Systems is a program run by the Swedish road administrationand the Swedish vehicle manufacturers.

19

Chapter 4

Road Information

This chapter is the first main subject of this project, namely the investigationof procuring a 3D road map to be used as input in the controller for thegearbox. The chapter describes several solutions available to create a map,using existing data or creating maps from scratch with a GPS receiver.

This part of the project does not include a final solution instead it is afeasibility study for the use and creation of 3D maps for this purpose. Thispart includes 4(5) main parts, GPS, GIS (2D and 3D), Map matching andRoad Sequence. These are linked together as depicted in figure 4.1. GIS

Figure 4.1: Road Information part of the project.

data is used as a reference to the real world, first in the 2D version togetherwith a GPS and a map matching algorithm to find the exact position of thetruck. After this the road sequence is found using the 3D GIS data.

21

4. Road Information 4.1. GPS

4.1 GPS

The Global Positioning System (GPS) or the NAVSTAR-GPS1 (originalfull title), is a system that is able to calculate a very precise absoluteposition on the earth, by means of a receiver and a number of satel-lites. The system measures the distance to different viewable satellites,so that it is possible to calculate the absolute position on the groundwith an accuracy of a few meters. The GPS is also capable of cal-culating the time, speed and direction of the receiver. This projectis not highly dependent on a very accurate positioning system, but forother purposes where better accuracy is needed. The GPS system canbe extended to the Differential-GPS (DGPS) system. Where a GPS

Figure 4.2: HoluxGM-210 GPS receiver

reference station is used to calculate any de-viation from the actual position measured.This deviation holds for a radius of around200 km from the reference station and theaccuracy of the position measurement isaround 1 meter.[Zogg, 2002]

A GPS system has been implementedmany times but to make sure it is possi-ble to get this part of the system working,(together with a 3D map), a simple GPSsystem is implemented.

For this purpose a standard GPS re-ceiver is used to test the system, placed atthe disposal to the project from the super-visors. The GPS receiver is a Holux GM-210 GPS receiver, with a USBinterface.

4.1.1 Communication with the Receiver

Communication with the GPS receiver is made with MATLAB2. The rest ofthis project is also implemented in MATLAB, which makes communicationand transfer of data simple. A simple program handles the read out ofdata from the GPS, it is enclosed on the CD in appendix B, MATLAB fileOpenGPS.m and read gpsstring.m.

4.1.2 GPS Parser

Data from the GPS are received in different packages that are parsed intousable data. A number of different types of packages are received. They in-clude data of respectively position, speed, heading, satellites in view, time,

1NAVigation System with Timing And Ranging Global Positioning System2MATLAB, a mathematical computing program, developed by MathWorks

22

4. Road Information 4.1. GPS

etc. These data are parsed in the MATLAB file parse gpsstring.m in appen-dix B.

4.1.3 Latitude and Longitude to UTM Coordinates

The positions received from the GPS and parser are in the Latitude3 andLongitude4 format. For this project this coordinate system is not very ap-propriate since it is based on degrees, minutes and seconds. Thus the co-ordinates are transferred to UTM5 coordinates which are a conversion to a2D plane. The conversion is rather comprehensive and can be seen in theMATLAB file ll2utm.m in appendix B.

4.1.4 User Interface

To present the result graphically the MATLAB GUIDE6 has been used.MATLAB GUIDE is also compatible with SIMULINK7. A test of the GPSreceiver is performed by plotting the positions onto a known map.

On figure 4.3 a screenshot of the first version of the program can beseen. It reads data from the GPS, and plots it onto a small map which hasbeen aligned with an aerial photo8 of the surroundings to the building wherethe receiver was located. Besides from plot the program also validates the

Figure 4.3: Program for testing GPS

position in a simple way by showing the number of visible satellites. If it is3Horizontal lines running around the globe.4Vertical lines running from pole to pole.5Universal Transverse Mercator Coordinate6Graphical User Interface Design Environment7Simulation tool for MATLAB8Provided by the internet based aerial photo service, Google Earth.

23

4. Road Information 4.2. GIS

above 4 it makes a green marker, 4 equals yellow, and below 4 equals red.A lot more information can be parsed from the GPS data, but to make aninitial test this is satisfactory.

The next version of the program includes simple GIS data, (see section4.2 depicted in figure 4.4. The data from the GPS has now been convertedfrom latitude and longitude to UTM coordinates.

Figure 4.4: Program for testing GPS and GIS

Altitude, Speed and Heading have also been parsed from the GPS signal,and made visible by the program. Test data can also be seen in section 4.2.2where a short test run is made from Building 326, DTU to Nærum and backagain.

4.2 GIS

Global Information Systems (GIS) is the appellation of information oflandscape, geographical areas, topography, etc. In this project it is a 3Dmap of the roads where this system is going to be used. 3D maps are knownfrom the normal 2D maps used in the GPS navigation systems commonlyused in cars. The only difference is that this map also includes the heightabove sea level of the roads. From this, gradients can be calculated andused as input to the gearbox controller, whether it is necessary to changethe shifting algorithm.

This chapter includes investigation and description of 5 different maps:

24


TOP10DK Create a map from the digital Danish map TOP10DK9. Bycombining layers of road and altitude.

KMS Create a map by reading data from the online topographical map atKMS10 .

Map based on GPS measurements Log GPS data (position and alti-tude) and create a map from this data.

Laser Scan New technology has made it possible to laser scan landscapesfrom airplanes.

Authentic road sections from Sweden Two pieces of authentic roadmeasurements from Sweden have been made available for testing.

Further development Discussion of the need for extra development inthis area.

4.2.1 TOP10DK

This map has been placed at the disposal of the author by the Danish Na-tional Survey and Cadastre, KMS. The data is limited to the local area,Søllerød municipality. The TOP10DK system is a number of different lay-ers, which digitally describes different topographic features. One layer forhighways, one for main roads, one for heights, etc.

Two of the main themes, the highway theme and the DEM11 theme,

7.1 7.15 7.2 7.25x 10

5

6.186

6.188

6.19

6.192

6.194

6.196

x 106

Eastern [UTM Zone32]

Nor

ther

n [U

TM

Zon

e32]

Figure 4.5: TOP10DK 2DHighway theme of Søllerødmunicipality

7.21 7.22 7.23 7.24 7.25 7.26x 10

5

6.188

6.189

6.19

6.191

6.192x 10

6


Nor

ther

n [U

TM

Zon

e32]

Figure 4.6: Part ofTOP10DK DEM theme,of Søllerød municipality

9Topographical, 1:10.000, Map of Denmark10Kort & Matrikelstyrelsen

25


have been combined to find the altitude of every point at the highway. Thetwo themes are depicted in figure 4.5 and figure 4.6.

Abstract from the long straight lines in the two themes which are due tothe simple rough program developed for showing the results. The combinedresults can be seen in figure 4.7 where the map has been tilted for betterviewing of the elevation of the highway. Again, abstract from the long

7.147.16

7.187.2

x 105

6.185

6.19

6.195

x 106

0

20

40

60

80

100

Eastern [UTM Zone32]Northern [UTM Zone32]

Alti

tude

[m]

Figure 4.7: GIS 3D Highway of Søllerød municipality

straight lines.

Evaluation

During the further work with this map, a problem was encountered. Thehighway theme includes a lot of exit turns and lay ins, which are not nec-essary for this project. Several algorithms were tested to remove the extraentries, but it proved to be difficult and another solution is preferable.

Parallel to the work with the map, an enquiry was placed at KMS toobtain road data of the two steepest gradients on Zealand. Unfortunatelyit proved to be very expensive, around 15 e/km. This was considered to betoo expensive for the problem in hand.

Another problem with this solution is that the height of the highway isnot that accurate since the height is deduced from the altitude curves ofthe landscape, and not from the road itself. This problem that might besolved by means of filtering the data, since the altitude of the highway inthe landscape in some way can be seen as a lowpassed filtered version of thealtitude of the landscape.

11Digital Elevation Model

26


4.2.2 KMS

The solution for using online mapdata from KMS, is to read out the datamanually from an online map. This sounds rather time-consuming, but itappeared to be possible for smaller pieces of road. The occasion for tryingthis solution was the desire for two certain parts of the highway on Zealand,the two steepest gradients. Ordering those pieces of road directly from KMScost 100 euros, a large expense taking in consideration this as a feasibilitystudy.

KMS has an online 1:25.000 map at their website where it is possible topoint at a place in the map, and the program will return the UTM position.The height can be deduced from the surrounding contour lines. About 15minutes of work resulted in a 3D map of the two required gradients, and afew ours of work resulted in data for three pieces of road on Zealand, around150 km of highway.

Route 21 From Holbæk to Folehaven(Copenhagen), interesting because itincludes a steep gradient near Holbæk, called Elverdammen.

E20 From the Great Belt Bridge to Slagelse, interesting because it includesa steep gradient near Varby.

E47/E55 From Helsingør to Lyngby(DTU), interesting since it is close toDTU and therefore very usable for testing both GPS and GIS.

Figure 4.8: GIS 2D Data of Sealand

27


In figure 4.8 the roads, read off the online map in 3D are depicted, super-imposed on a map of Zealand. On figure 4.9 the roads are depicted in 3D,the altitude has been multiplied with 100 to make it more visible.

6.4

6.6

6.8

7

7.2

x 105

6.14

6.16

6.18

6.2

x 106

05000


Sealand

Northern [UTM Zone32]

Alti

tude

x 1

00 [m

]

Figure 4.9: GIS 3D Data of Sealand

Evaluation

The accuracy of these maps is more or less the same as the result from theTOP10DK. The altitude is constructed from landscape height curves, butcan be adapted by means of filters.

Due to the manual readout of this map faults occur when reading po-sitions or altitudes, but single major faults are easy to find and correctwhen checking the map. The 2D parts of these maps has been validated by

7.18 7.19 7.2 7.21 7.22 7.23 7.24

x 105

6.1865

6.187

6.1875

6.188

6.1885

6.189

6.1895

6.19

6.1905

6.191

6.1915x 10

6


Nor

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n [U

TM

Zon

e32]

GPS measurementGIS

Figure 4.10: 2D GIS and GPS from E47/E55 test

28


plotting GPS positions along them, while driving in a car, see figure 4.10.The result looks resonably accurate, the GPS positions follows the GIS

data of the road smoothly.Validation of the 3D data is a more difficult task, since the only mea-

surement of this is the GPS altitude which is not very accurate. A test hasbeen performed, driving from DTU to Nærum, and back again on the high-way. The altitude from the GPS has been logged, and plotted together withthe GIS profile of the road. The result is depicted in figure 4.11. It is not

6.187 6.188 6.189 6.19 6.191

x 106

10

15

20

25

30

35

40

45

50

55

60

Northern UTM 32

Alti

tude

[m]

GPS measurementGIS

Figure 4.11: 2D Profile GIS and GPS from E47/E55 test

possible to say whether the GPS or the GIS data is the more correct fromthis test, since real accurate data of the road are not available. It is obviousthat the road has not moved between the way out and the way home, whichthe GPS data shows. The result however shows coherence, primarily in thetrend of the curve. Some offset is seen in the altitude but that is normal forGPS measurements.

During test driving it was noticed that the GPS positions was more ac-curate, compared to the visible profile of the road. Therefore the possibilityof creating a map, based on GPS measurements was investigated.

4.2.3 Map Based on GPS Measurements

It is possible to log data when driving on roads, although the GPS mea-surements are affected by noise, several runs on the same road should givea sufficient digital picture of the road profile. The evident advantage of thissolution is that it is possible to create maps, very inexpensively, and newroads can be mapped when first used.

Another possibility with this system could be on online updating of aglobal map. If a truck has passed a piece of road which are not mapped

29


before, it could log the data, and transmit it to an online global database.When a number of trucks have passed that road, a sufficiently accurate mapwill be available for other trucks.

6.187 6.188 6.189 6.19 6.191 6.192 6.193 6.194

x 106

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30

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Northern UTM 32

Alti

tude

[m]

Reference GISGPS measurementFinal GIS

Figure 4.12: 2D Profile of map created from GPS measurements atE47/E55

In figure 4.12 the result of this implementation is depicted. The mapfrom section 4.2.2 is used as reference (the green line), this profile is updatedwith several measurements from the GPS (the blue lines), and the final resultof the update is the red line.

Evaluation

This map has proven to be very accurate from a visual evaluation. Themap is only based on 5 measurements, which is very little compared tothe number of trucks driving on highways. It is not unlikely that in a fewdays, hundreds of trucks would pass a certain piece of road, and sufficientdata would be available for creating a good road map. In a Swedish project[Johansson, 2005] it is also concluded that the GPS receiver is the best sourcefor creation of maps. However the system could probably be improved usingother sensors like barometers, torque sensors on driving vehicles, etc. anda method called Sensor Fusion also described in [Jansson et al., 2006]. Useof statistics, Kalman filters, or the like could improve the result.

4.2.4 Laser Scan

A new possibility for the development of an accurate 3D road map has beenintroduced in the early 2006. Airplanes have made a full laser scanning ofDenmark to produce digital elevation models. The accuracy should be 15

30

4. Road Information 4.3. Map Matching

cm. The project has not yet been converted into digital road models, but itshould be possible to deduce this out of the data. The only problem of thissolution could be the purchase price of maps. [COWI, 2006]

4.2.5 Authentic Road Data from Sweden

In the master’s thesis [Hellstrom, 2005], a section of the E4 highway in Swe-den is used for testing, more precisely the piece of road between Linkopingand Jonkoping, a total of 127 km, depicted in figure 4.13. This piece of roadhas been placed at the disposal of the author by Erik Hellstrom. The roadis measured with an accuracy of 1 meter and provides a very good testingroute. The gradient of this piece of road varies between about +/- 4%.

0 20 40 60 80 100 1200

100

200

300

Alti

tude

[m]

0 20 40 60 80 100 120−5

0

5

Gra

dien

t [%

]

Position [km]

Figure 4.13: E4, Linkoping - Jonkoping, road profile.

4.3 Map Matching

The position found by the GPS does not match the map exactly. Due tothe noise on the measurements the position will fluctuate around the realroad in the map. To find the actual position of the truck it is necessary

31

4. Road Information 4.3. Map Matching

to combine the GIS and the GPS data. This is possible by using a Mapmatching algorithm. The problem is depicted in figure 4.14, where the raw

Figure 4.14:Map matchingalgorithm.Raw GPSdata

Figure 4.15:Map matchingalgorithm.Matched data

GPS positions fluctuate around the real road. By projecting the positionsto the nearest piece of road with the map matching algorithm, the exactposition of the truck on the road can be found, as depicted in figure 4.15.

In this project a rather simple map matching algorithm has beenimplemented, the algorithm is described in [Dakai Yang, 2003]. Thealgorithm calculates the matched position by means of simple point to lineequations, references in the formulas can be seen in figure 4.16:

Figure 4.16: Map matching algorithm

From a point P (x0, y0), find the nearest point D(x3, y3) on a line goingfrom A(x1, y1) to B(x2, y2)

ax + by + c = 0 (4.1)

where

a = 1 b = −1/k c = −x1 + (1− k) · y1 (4.2)

k =y2 − y1

x2 − x1

32

4. Road Information 4.4. Road Profile

Based on the equation of perpendicular length from a point to a line, PDis:

d =|ax0 + kby0 + kc|

b− ka(4.3)

If PD is the smallest distance from point P to the surrounding roads, thenthe coordinate of point D is:

x3 =bx0 + kby0 + kc

b− ka

y3 =−1/k

x3 − x0+ y0 (4.4)

This algorithm is simple, but sufficient, if there are no crossing roadsetc. For this project it is no problem, but in a later real implementationit would be necessary to include these aspects. Because these problems arealready handled in the current GPS navigation systems, it was decided notto work more on this part.

7.206 7.208 7.21 7.212 7.214

x 105

6.1866

6.1867

6.1868

6.1869

6.187

6.1871

6.1872

6.1873x 10

6

Eastern UTM 32

Nor

ther

n U

TM

32

GPS measurementGIS roadMatched GPS

Figure 4.17: Test of the map matching algorithm

In figure 4.17 the result of the map matching algorithm is depicted,the red crosses are the GPS positions, the green line is the road, and theblack dots are the map matched positions. When the position gets closerto the road than a specific distance, it starts to match the measured GPSpositions on to the known road. This function can be seen in the MATLABfile match map.m in appendix B.

4.4 Road Profile

When the absolute position of the vehicle on the road (digital map) is known,it is possible to determine the road profile ahead of the truck.

33

4. Road Information 4.5. Test of GPS/GIS System

The profile of the road in front can be described by a number of differentparameters. The most important are:

• Gradient of road at present position

• Distance to steeper gradient

• Distance to end of gradient

• Length of gradient

Figure 4.18: Description of the road sequence in front of the vehicle

These parameters are used by the controller (see section 6), to read the roadand determine if it is convenient to make a shift down or up.

4.5 Test of GPS/GIS System

The whole system of Road Information has been implemented in a MATLABGUIDE interface, a screenshot of the program userinterface can be seen infigure 4.19. The program includes GPS-, GIS-, Mapmatching- and a simpleversion of Road Profile/Controller implementation. The GPS can be eitheron-line or off-line (already logged data), matched on the three pieces of roadimplemented in the GIS section. (Route 21, E20 and E47/E55). The resultof the GPS, GIS and Mapmatching algorithm is depicted in the window atthe top left. A simple Road Profile/Controller has been implemented bylooking at the road gradient ahead. If its above a certain gradient the MaxGear is changed to the appropriate gear for that particular gradient.

In the Controller section, this part will be upgraded to use more infor-mation about the road and vehicle. The program is implemented and testedto work driving in a normal car, to determine if it is possible to control thegearbox from a GPS/GIS solution.

The program can be found in appendix B MATLAB file program 6.fig

4.6 Summary

Communication has been established to the GPS, and data can be receivedand converted in order to combine it with the available GIS data.

34

4. Road Information 4.6. Summary

Figure 4.19: Program calculating the road sequence ahead of thevehicle

The task of procuring a usable 3D map has proven to be difficult. Dif-ferent solutions has been tested and investigated, and the possibility forcreating the map rather than buying one from a second source looks feasi-ble.

A simple map matching algorithm has been tested, and the whole sectionhas been implemented into a program with a controller, which can give acommand to the driver to shift one gear down, if the gradient of the presentroad section is too steep. The program has been tested in a driving car,showing expected results.

35

Chapter 5

Truck

This chapter describes the control object to be controlled in this project,namely the truck. Due to the relatively short amount of time available forthis thesis, it has not been possible to implement and test the system on areal truck. Instead a simulation model has been developed to match a realtruck as close as possible. Another important issue about having a model isthe possibility of creating a controller, based on the information containedin a model.

This chapter consists of three main parts:

Real Truck This is a description of the reference truck which the projectis based on. This truck is chosen because it was easy to obtain simpledaily running tests to achieve some references for the development ofa model.

1st Model - Simple The first model to be developed can be seen as a fea-sibility study to investigate whether it is possible to control a truck bymeans of a GPS/GIS system. The main characteristics of a truck willbe implemented. And the result will constitute the basis for continuingwith a more advanced and more accurate model.

2nd Model - Advanced The intention for this model is to get as close aspossible to the behavior of a real truck, to make it plausible that thesystem would be worth the effort to install in a real truck.

The Truck is linked together with the rest of the project as depicted onfigure 5.1. The truck receives inputs from the road, (artificial or authentic)and from the controller (will be descriped in chapter 6). The different statesand output of the truck are fed back to the controller, for the next controlsequence. The truck will as described in the beginning of the chapter be inthe form of a simulation model. In the final solution, the system should beimplemented on a real truck.

37

5. Truck 5.1. Real Truck - Volvo FM9 - 380

Figure 5.1: Truck part of the project.

5.1 Real Truck - Volvo FM9 - 380

As mentioned in the Introduction it was possible to get simple driving ref-erence data from normal driving, through my father who is a truck driver.

Figure 5.2: Volvo FM9 - 380 Strawtransport

The truck is a Volvo FM9 - 380, depicted in figure 5.2. It is built forstraw transport, 24 bales of 500 kg each.

5.1.1 Specifikations

Main data of the truck:

Engine D9A380, 9 Liter, Inline 6, 380 HP, 1700 Nm at1150 - 1550 RPM

Gearbox I-shift VT2412B GSS-AGS, Split/Range,12 forward, 4 reverse.

Rear-axle ratio 1:3.10Total weight 24.000 kgTruck weight 12.000 kgBuilt 2002

38


Detailed engine, gearbox and rear-axle data are supplied by Volvo TruckCenter Denmark A/S.

The following two models are fitted to match the above truck, by ad-justing average fuel/kilometer usage, air drag, rolling resistance, climbingresistance, gearbox behavior, etc.

5.1.2 Reference Tests

A number of tests has been conducted in order to collect reference data forthe models.

Engine Tests at Volvo

Engine tests have been performed at Volvo Truck Center Denmark A/S tomeasure properties of turbo pressure and engine response time. The truckused for engine testing is depicted in figure 5.3.

Figure 5.3: Volvo FM9 - 300 Test truck at Volvo Truck CenterDenmark A/S

Unfortunately it was not possible to use a truck similar to the othertruck used for driving tests. This truck is only a 300 HP version, the otheris a 380HP. The main difference is the turbo pressure limit, which gives theextra 80 HP. But the response time of the engine and turbo are similar.Another test were carried out on a FM9 - 340HP, unfortunately all data ofthese tests were lost during the transfer from the truck to a PC, the onlydata obtained were a number of values written down manually during thetest drive, including the maximum turbo pressure.

39


Maximum turbo pressureFrom measurements of the FM9-300 and FM9-340, the value of the max-imum turbo pressure in the FM9-380 has been estimated for use in thedevelopment of models.

Truck FM9-300 FM9-340 FM9-380Turbo Pressure 183 kPa 208 kPa 230 kPa (estimate)

Table 5.1: Estimated maximum turbo pressure of FM9

Response timeThe turbo pressure is logged by the truck in intervals of 0.6 seconds, a plotof the turbo response can be seen in figure 5.4. The graph shows that the

0 1 2 3 4 5 680

100

120

140

160

180

200

Time [s]

Tur

bo p

ress

ure

[kP

a]

Figure 5.4: Volvo FM9 - 300 Turbo pressure. Dynamic response.

turbo is at 90% pressure after 2 seconds. This agrees with promotionaldata, which states that the engine is capable of producing 90% power after2 seconds.

Fuel Usage

Average Fuel UsageThe average fuel usage has been logged during normal highway driving.Measurements were made over several kilometers, including driving in bothdirections on different days. Disturbances such as wind speed, atmosphericpressure, etc., are assumed to be minimized.

40


Average fuel usage 2.9 km/literAverage fuel usage (highway - 85km/h) 3.1 km/liter

Max Fuel UsageTests for determining the maximum fuel usage in the highest gears havebeen carried out on steep gradients. The measurements were made at 1350RPM in the middle of the high torque area.

Max Fuel, 11 gear 1.0 km/literMax Fuel, 12 gear 1.1 km/liter

Speed and Fuel Usage During Climbing

On the highway E20 on Zealand, at Varby, measurements have been carriedout when the truck was climbing the gradient. The gradient has a certaininclination and length which makes the truck shift down once, when drivingin Automatic mode.

The measurements have been collected by looking at the gauges anddigital displays in the truck when climbing the gradient. The measurementstarts at the bottom at cruising speed (85km/h) and ends when the samespeed has been reached on top of the gradient.

0 2 4 6 8 10 12 140

50

100

Tur

bo −

pre

ssur

e [%

]

0 2 4 6 8 10 12 14

11

12

Gea

r

0 2 4 6 8 10 12 14

1

2

3

Fue

l [km

/l]

0 2 4 6 8 10 12 1460

70

80

90

Spe

ed [k

m/h

]

Figure 5.5: Speed and fuel tests at Varby - E20. Automatic - Solid,Manual - Dashed

The test was carried out 6 times, 3 times in Automatic mode, and 3

41


times in manual mode, where gearshifts are controlled by the driver. Dueto small changes in the wind condition and load condition, the data showsome uncertainty.

Mode Min speed Load WindAutomatic 69 12.9 Little followingAutomatic 67 12.1 Little headAutomatic 65 12.7 None

Manual 78 12.2 NoneManual 77 12.7 Little headManual 79 12.6 Little following

Table 5.2: Speed and fuel tests at Varby E20.

The tests clearly shows that the average speed can be increased by lettingthe driver control the gearbox, using experience and driver skills. Whetherthe overall fuel usage is changed is impossible to decide from the tests. Thathas to be revealed by simulations.

Gearbox

The gearbox has been tested to determine when the automatic decides toshift gears. The gearbox can be driven automatic in two modes, Economyor Power.

Shift down is only performed when the truck is at full load and the enginespeed is decreasing.

The gearbox has been observed to shift down normally at:Economy mode 1050 RPMPower mode 1200 RPM

The gearbox has been observed to shift up normally at:Economy mode 1600 RPMPower mode 1700 RPM

Besides this, the gearbox also uses other parameters to control the gearshift. The throttle and load also affect the shifting.

If the driver or Cruise Control asks for high power by pressing the throt-tle, the engine speed for shifting up will be raised. And similarly if the driverreleases the throttle, the gearbox will shift up as soon as possible.

If the load on the engine is low, the limit for shifting up will also beraised, and the gearbox then decides to shift 2 gears at a time. This is moreeconomic. If the load is high, it will assure that the RPM is held in the hightorque area of the engine. The whole strategy is depicted in figure 5.6.

42


0

50

100

0

50

1001200

1400

1600

1800

2000

2200

Load [%]Throttle [%]

Shi

ft up

[RP

M]

Figure 5.6: The effect of throttle and load on the gearbox strategyfor shifting up.

Acceleration

To give an overview of the total elapsed time of acceleration includinggearshifts, an acceleration test has been carried out. The truck is accel-erated from 0 to 80 km/h on plain road, both empty (12 t) and fully loaded(24 t). The throttle is placed at either full normal throttle or Kick-Downwhich is similar to using the Power Mode described in the previous section.The Kick-Down function normally forces the gearbox to shift one gear down,if it is possible, to deliver extra power on demand of the driver. The resultis presented in table 5.3.

Weigth Mode Time12 ton Full (Eco) 33.3 s12 ton Kick-down (Power) 32.0 s24 ton Full (Eco) 43.5 s24 ton Kick-down (Power) 35.5 s

Table 5.3: Test of acceleration 0 - 80 km/h.

5.1.3 Evaluation

The above tests are very useful for matching of the models to the real world.Most of the results are made by visual reading of instruments, which arenot very accurate. But due to the limited amount of time available, it wasnot possible to make all these tests in a special test truck equipped withcomputers for logging the data.

43

5. Truck 5.2. 1st Model - Simple

All of the reference data of the truck has been incorporated in two MAT-LAB files for the following two models: truck data.m for the 1st model, andtruck data new.m for the 2nd model, both to be found in appendix B.

5.2 1st Model - Simple

A simple model of a truck has been developed and implemented, to get anoverview of the system, and test whether it is possible to change the behaviorof a truck using inputs from a GPS/GIS system. The model includes vehicledynamics, road conditions, and drivetrain. The model has been implementedin MATLAB and SIMULINK, see appendix A.1.

The model has been implemented using very simple equations and phys-ical properties of the different parts. Using the test data from the previouschapter, the model has been adjusted to match the output of a real truck.

The model consists of 7 main parts, linked together as depicted in figure5.7.

Figure 5.7: 1st Model main parts.

Engine Simple engine, including most important time constants.

Automatic Gearbox Simple automatic gearbox including a timedelay.

Rearaxle/wheels Ratios and conversions

Vehicle Physical model of vehicle

Real Road Road profile, authentic or artificial.

Cruise control Cruise control to maintain a cruising speed.

Output/Gauges Output data for evaluation.

44


5.2.1 Engine

The engine has been modeled by a few simple parts. A total torque curve,a power time constant, a turbo with another time constant, a clutch, and acalculation of fuel consumption.

The output torque of the engine can be calculated by the formula:

Te = Cl · (Tnorm(n) + Tturbo(n)− TV EB(n)− Tdrag(n)) (5.1)

Where Te is the total engine torque, Cl is the clutch which can have thevalues 0 or 1 controlled by the automatic gearbox, described later. Tnorm

is the torque delivered by the normal engine, Tturbo is the extra torque theturbo delivers in its working area and TV EB is the negative torque providedby the engine brake if the speed is above the reference. Tdrag is the negativetorque provided by the internal friction in the engine and n is the enginespeed.

Normal Engine Torque

The torque from the engine is calculated by the formula:

Tnorm = Tnormmax(n) · 1τengines + 1

·Kthrottle (5.2)

which is simplified to a 1st order system, where Tnormmax is the maximaltorque to be delivered from the normal engine, found from a reference-tablevia the engine RPM. τengine is a time constant for the engine to built uppower and Kthrottle is the position of the throttle, can vary from 0 to 1.

Turbo

The extra torque from the turbo is calculated by the formula:

Tturbo = Tturbomax ·1

τturbos + 1·Kengine (5.3)

which is also simplified to a 1st order system, where Tturbomax is the maximaltorque to be delivered from the turbo, found from a reference-table via theengine speed. τturbo is a time constant for the turbo to built up power andKengine is the 1st order delayed engine load from above.

Engine Drag

When the vehicle is pulling the engine, going down steep gradients, theengine will produce a small negative torque, given by the equation below.

Tdrag = ad · n + bd (5.4)

45


0 500 1000 1500 2000 2500 3000−500

0

500

1000

1500

2000

RPM

Tor

que

[Nm

]

Normal engine torqueExtra turbo torqueTotal engine torqueDrag Torque

Figure 5.8: Engine torque of a Volvo FM9, 380HP

The engine torque is depicted in figure 5.8.

It should be mentioned that the total torque is from the Volvo descriptionof the engine, the two other curves are created by a simple qualitative guessand may differ from the real facts. But the overall result of this system is anengine which has a working area with some time delays, including the timeconstants in the turbo. The low area engine speed differs a lot from the realworld, but is made in this way to simplify the whole clutch mechanism, i.e.the truck is able to start from 0 km/h with 0 RPM in 1st gear.

VEB

An Engine brake (VEB - Volvo Engine Brake) has been implemented tobrake the vehicle if the speed increases above the desired reference speed.

TV EB = kstepn

nmax· TV EBmax ·

1τV EBs + 1

(5.5)

Which is a simplified 1st order system, where kstep is a constant kstep ∈ [0; 3]referring to 0 brake or step 1-3, 3 is most braking torque. TV EBmax isthe maximal breaking torque to be provided by the engine brake, whichequals 80% of the normal driving torque on this engine at max engine speed,depicted in figure 5.9 The engine is lagged by the τV EB time constant, whichequals the engine time constant.

46


0 500 1000 1500 2000 2500−1400

−1200

−1000

−800

−600

−400

−200

0

Bra

ke T

orqu

e [N

m]

RPM

VEB − step 1VEB − step 2VEB − step 3

Figure 5.9: Engine brake torque of a Volvo FM9, 380HP

Fuel Consumption

The fuel consumption is calculated in a rather simple way [Hellstrom, 2005].

fc = n ·Kthrottle · 16 · 104

ncyl

nr(5.6)

Where fc is the fuel consumption in liter/sec, ncyl is the number of cylindersand nr is the number of crankshaft revolutions per stroke.

The SIMULINK engine block can be seen in appendix A.1.2.

5.2.2 Automatic Gearbox

The gearbox is mainly a system to multiply the torque delivered from theengine.

The gears are selected by a simple algorithm which shifts the gear up,when the engine speed reaches 1650 RPM and shifts down when it dropsbelow 1050 RPM. This is a simple algorithm but sufficient for the first model.

A gear efficiency has been included in the model, and the efficiency isas depicted in figure 5.10 [Hellstrom, 2005]. The efficiency is highest in thetop gear. The gearbox is also equipped with a time delay to simulate thetime it takes to shift gears, meanwhile a command is sent to the engine toset the output torque to 0 (activated clutch).

The gearbox controller can also be given a command to force a shift up-/down from the controller described in chapter 6. The SIMULINK gearbox

47


1 2 3 4 5 6 7 8 9 10 11 120

5

10

15

Rat

io [x

:1]

1 2 3 4 5 6 7 8 9 10 11 1285

90

95

100

Gear

Effi

cien

cy [%

]

Figure 5.10: Gear ratios of an I-shift VT2412B

block can be seen in appendix A.1.3.

5.2.3 Rearaxle/Wheels

The rearaxle and wheels are a conversion from the engine/gearbox torqueto a force acting on the road. The rearaxle includes a gear ratio and anefficiency constant. The model includes wheel brakes to make it possible tokeep the speed down when driving downwards on steep slopes. Otherwisethe overspeed gained could be use to climb the next hill and influence theresult.

The total equation of the rearaxle and wheels:

ωw =Tgirηr − kbB − rwFw

Jw(5.7)

Where ωw is the angular acceleration of the wheels, Tg is the torque deliveredfrom the gearbox, kb is a constant parameter, B is the brake control signalB ∈ [0, 1]. rw is the wheel radius, Fw is the total force acting on the wheelsand Jw is the wheel inertia. ir is the rearaxle ratio and ηr is the rearaxleefficiency.

The SIMULINK wheel block can be seen in appendix A.1.4.

5.2.4 Vehicle

A simple total longitudinal acceleration vehicle model has beendeveloped, inspired from the article [Mangan et al., 2003] and[Kiencke & Nielsen, 2000].

The model is derived from the two general equations:

F = m · a (5.8)

48


andT = J · ω (5.9)

Where m is the mass of the vehicle, F is the total driving force, a is theresulting acceleration of the vehicle, T is the Torque, J is the moment ofinertia and ω is the angular acceleration.

The total driving force is a combination of the force from the drivelineand the opposing forces acting against movement of the vehicle.

F = Fdl − Frr (5.10)

Running Resistance

The running resistance consist of 3 forces:

Frr = Fro + Fae + Fcl (5.11)

Where Fro is the rolling resistance, Fae is the aerodynamic drag and Fcl isthe climbing resistance and downgrade force.

Rolling Resistance

The rolling resistance is a product of the deformation of the tire on thecontact patch to the road surface. The total resistance can be calculatedusing this equation:

FRo = f ·m · g · cosα (5.12)

Where f is the rolling resistance coefficient, here is as reference used 0.007[Hellstrom, 2005] and later adjusted to match the real vehicle. g is gravity(9.81m/s2), m is the mass of the vehicle and α is the longitudinal roadgradient.

Aerodynamic Resistance

The aerodynamic resistance is calculated using the equation:

Fae = 0.5 · σ · cw ·A · v2 (5.13)

Where σ is the air density, 1.19kg/m3 at 100m altitude and 20 ◦C. cw is thevehicle drag coefficient. This is different for every vehicle but here the value0.6 is used. [Hellstrom, 2005]. A is the front area of the vehicle which forthe Volvo FM9 truck is 9.75m2.

49


Climbing Resistance

The climbing resistance which is by far the largest force acting on the vehiclecan be calculated from:

Fcl = m · g · sinα (5.14)

Driveline Force

The force acting from the driveline can be calculated from the expression:

Fdl =Te · ig · ir · ηg · ηr

rw(5.15)

Where Te is the torque delivered by the engine, ig is the gear ratio of thegearbox. ηg is the gearbox efficiency.

Complete Vehicle Model

The complete vehicle model including forces, mass and moments of inertiacan now be stated:

v =rw

Jw + mr2w + ηri2rηgi2gJe

(ηrirηgigTe

−kbB − 0.5cwAσrwv2 −mgrw (fcosα + sinα))

(5.16)

5.2.5 Input - Real Road

The model is simulated driving on authentic or artificial road sections. Dur-ing simulation the acceleration of the vehicle is integrated to give the speedand again to give the driven distance. This distance is used to look at themaps of a certain road and find the gradient of the road, thus it is possibleto drive on the real roads with the model. Besides several constants themodel is also fed with a reference speed for the Cruise Control.

5.2.6 Cruise Control

The Cruise Control is implemented to make the vehicle maintain a certainspeed. The cruise control is implemented as two simple PID1 controllers,one for the throttle and one for the brakes. It has not been possible toobtain the real values for these controllers, instead the controllers are tunedto give a fast and damped response.

Both of the controllers are implemented in this form:

Gc(s) = Kp

(1 +

1τis

)τds + 1

αccτds + 1(5.17)

This is actually not a PID controller but a PI-lead controller.1Proportional-Integral-Derivative controller

50


Throttle Controller

The input to the controller is the deviation of the speed compared to thereference speed and the output is the throttle position to the engine.

The parameters are: Kp = 10, τi = 10, τd = 3, α = 0.01.

The controller has also been equipped with an anti-integrator-windupsince the control signal (throttle) is limited.

Brake Controller

The input to the controller is the deviation of the speed compared tothe reference brake speed (a few km/h higher than the reference cruisingspeed), and the output is the pedal position to the brakes.

The parameters are: Kp = 0.2, τi = 10, τd = 3, α = 0.01.

The controller has also been equipped with an anti-integrator-windupsince the control signal (brake) is limited.

5.2.7 Output - Data/Gauges

The output of the model is presented in two different ways: online andoffline. During the simulation, the states of the model are presented on anumber of gauges depicted in figure 5.11, which gives a clear overview ofthe simulation. After the simulation is carried out the result is saved in anumber of files for offline inspection.

Figure 5.11: Gauges from the simulation model, similar to thegauges in a Volvo Truck.

51

5. Truck 5.3. 2nd Model - Advanced

5.2.8 Evaluation

This model is a rather simple implementation and is only tested with asimple controller (many details are left out). However the model gives anoverall idea of the performance using a system to read the road in front ofthe vehicle.

The most important problem with this model is the simulation of fuelconsumption. This is a very rough and inaccurate function and is the pri-mary reason for constructing a more advanced and realistic model. TheSIMULINK diagram of the whole 1st model can be seen in appendix A.1.1.

5.3 2nd Model - Advanced

The 1st model developed in the previous section is based upon simple basicknowledge of the driveline of a truck. The engine is based on a certaintorque, and a number of time constants to reflect reality.

This model is good for simple test of the system and to give an overviewof which parameters a controller for the gear shifting strategy affects. Nochanges are needed for improving the equations describing the vehicle itself.The input and output to the model are also the same as in the first model.

Three parts of the model, concerning the driveline are improved in the2nd model:

Engine A more accurate engine model is needed where the correct timeconstants and small secondary effects can bring the result closer toreality. One of the most important parameters to improve is the fuelconsumption. In the first model, the fuel consumption is a calculatedvalue based on engine speed and throttle position. The more correctway of simulating the fuel consumption is to base the model on energyconsiderations.

Clutch In the first model the truck can be started from 0 RPM, that isnot possible in real life. In the first model this also means that theengine model is adapted to have a working area from 0 RPM to 2500RPM. This needs to be improved since a real engine can normallynot work below approximately. 600 RPM. Therefore a real clutch isimplemented in this model to make it possible to start the model from0 km/h.

Gearbox The gearbox in the first model was a simple ratio conversionwith a time delay of a fixed time to shift gears. In the second modelthe whole shifting sequence is incorporated to give a more accurateresponse. The gearbox normally controls the engine to make the enginespeed correct for engaging the next gears, this takes some time and

52


consumes a small amount of fuel. These parts are included in thissecond model.

5.3.1 Engine

The new engine model is based on the MVEM (Mean Value Engine Model)which is a dynamic description of the states in the engine by means of a setof nonlinear differential equations. The model uses mean values instead ofinstantaneous values, and is simplified so that it is just sufficient to describethe time development of the most important engine variables. In spite of thesimplification the model is capable of describing the conditions in an enginewith a very high accuracy, and similar models are used by both DelphiAutomotive and Bosch for control of air/fuel mixture and throttle/power.

In this project the model is simplified and adapted to fit a large dieselengine with the main emphasis on fuel consumption, time constants andtorque produced.

Introduction

The MVEM modeling of turbocharged engines, requires two main dynamicsystems. The crank shaft dynamics and the air supply dynamics.

In a diesel engine the fuel supply to the cylinders is controlled accordingto the available air supply in the intake manifold. The purpose of the modelin this thesis is to model a heavy duty turbocharged diesel engine duringmedium to high load operation, normally used in highway operation. Thissimplifies the task of modeling significantly, specifically the dynamic airsupply is easier to model during medium to high engine operation.

The need for modeling of the air supply dynamics relies on the factthat the output in a turbocharged engine is strongly affected by the airflow dynamics. The fact that a turbocharger has a finite reaction time,makes the modeling of air dynamic very important. The turbocharger isa compressor driven by an exhaust turbine on operation range of morethan 50.000 RPM. Acceleration and deceleration of the turbocharger shafttakes a lot of time and is thus not negligible. Thus this must be takeninto consideration in the investigation of optimum vehicle operation inhilly locations. The effect is especially visible during gearshifts where theengine is moved from high torque to zero torque and back again. Here theturbocharger time constant is the most important variable to affect theperiod of time when the engine is not delivering full torque to the driveshaft.

Fortunately the model required in this project can be based on a foun-dation which already exists in the form of MVEMs already constructedand which are available in the literature. The model is primarily based

53


on earlier work done on the modeling of very large ship diesel engines, de-scribed in [Hendricks et al., 1984] and more detail in [Hendricks, 1989] aswell as later work on turbocharged common rail diesel engine models forcars [Hendricks et al., 2004]. Two other important references has been used:the detailed compressor model from the SAE paper [Hendricks et al., 2005]and the port air mass flow model from [Hendricks et al., 1997]. Furtherassistance with the model has been provided from local experts at DTU,[Hendricks & Sorenson, 2006]. In order to construct this simplified dieselengine model, bits and pieces from the references above have been com-bined as appropriate for this special task. The model has been adapted andchecked against available data of the real engine.

None of the data on the engine has been supplied by the manufacturer,thus the required MVEM has been constructed only on the basis of speedand torque curves provided in promotional material, simple measurementscarried out on a daily running truck, and measurements on a truck withthe VCADS2 at Volvo Truck Center Denmark A/S.

Figure 5.12: Primary parts of the engine

The functionality of the engine is depicted in figure 5.12, a more detailedflowchart can be seen in appendix A.2.2

The fuel is fed into the cylinders, together with an amount of air. Thisgives a certain efficiency which gives the amount of torque delivered onthe crank shaft. Some power are also let out through the exhaust whichdrives the turbocharger. The turbocharger provides the engine with a higherpressure when more fuel is fed into the engine, this means more air/fuel intothe crankshaft, which means more torque on the crankshaft.

Crank Shaft Speed Dynamics

In [Hendricks et al., 1997] the crank shaft speed equation is written:

n =1In

(− (Pf + Pb) + Huηimf (t− τd)) (5.18)

2Vehicle Computer Aided Diagnostic System

54


where n is the crankshaft speed, I is the moment of inertia of the engine,plus eventually load. Pf (n) is the loss of friction in kW and the powersupplied to the load is Pb(n) in kW and mf is the fuel mass flow kg/s.

The frictional losses are obtained from a normally used expression de-scribed in [Heywood, 1988] which can be scaled with the engine displace-ment. The expression in [Heywood, 1988] is based on a 1.275 liters engine,thus the frictional losses can be determined by scaling:

Pf (n) =Vd

Vref

(1.673 + 0.272n + 0.0135n2

)(5.19)

where Vref = 1.275L is the reference engine, Vd is the displacement of thelarge engine (in this case 9.4 liters). The parameters in equation 5.19 havebeen obtained from measurements at MEK3, DTU.

The last term in the right parenthesis in equation 5.18 includes the heat-ing value of the fuel, (i.e. the power included in the fuel) Hu = 43kJ/kg.The indicated efficiency ηi in the same place is also obtained from experi-ments conducted at MEK, DTU. This is a typical value of the efficiency ofa modern diesel engine. It is given by the equation:

ηi(Φ, n) ∼= 0.47(1− 1.334 (Φ− 0.45)2

)(5.20)

This approximation is possible because the indicated efficiency is onlyweakly dependent on the engine speed in the medium/high load region.Φ is the fuel/air equivalence ratio, given by the expression:

Φ =mfLth

map(5.21)

where mf is the fuel mass flow, map is the port air mass flow, and Lth = 14.7is the stoichiometric air/fuel ratio. Equation 5.20 is a very flat parabola inθ.

The rate at which air can be supplied to the four cycle engine is givenby the port air mass flow, which is given by the speed density equation:

map =Vd

120RTi(ev · pi) n (5.22)

where Vd is the engine displacement volume, R is the gas constant, Ti isthe temperature of the air in the intake manifold. (ev · pi) is the volumetricefficiency times the intake manifold air pressure (i.e. the air charge perstroke) described in [Hendricks et al., 1997].

The aircharge per stroke derived in [Hendricks et al., 1997] is given by asimple universal equation:

evpi = si(n) · pi + yi(n) (5.23)3Department of Mechanical Engineering

55


where si(n) and yi(n) are only very weak functions of the engine speed andare effectively constant. Typical values found for these parameters of a dieselengine are si = 1.05 and yi = −0.13.

The last parameter in equation 5.18 is the time delay τd from the injectionof fuel until the torque increase on the crank shaft, is given by the equation:

τd =60n

(1 +

1ncyl

)(5.24)

where ncyl is the number of cylinders.The SIMULINK engine crankshaft block can be seen in appendix A.2.5.

Intercooler

The intake manifold pressure and temperature used above are determinedby the intercooler, which most turbocharged engines are equipped with.The purpose of the intercooler is to lower the temperature of the intake air,and thereby increase the air density. The intercooler is cooling the intakeair by the ambient air when driving. This is necessary because when theturbocharger is increasing the intake pressure the air is also heated up.

In principle the intercooler is a dynamic system, like the crank shaftspeed state equation and the compressor pressure. But since the engineis assumed to operate near maximum load, and for the sake of simplicitythe intercooler can be assumed to operate instantaneously and an algebraicequation can be used to describe it instead.

The intake manifold pressure and temperature are given by:

pi = 0.916pc + 0.0065 (5.25)

andTi = 0.229Tc + 210.6 (5.26)

where pc and Tc are the compressor outlet pressure and temperature.These equation are derived by measuring on a real turbocharged engine,described in [Hendricks et al., 2004]. The measurements was carried out ina lab and an air to water intercooler was used instead, but the results aresimilar to an air to air intercooler used in trucks. The intercooler was foundto give a constant efficiency of 70% over the entire operating range of theengine.

The purpose of including the intercooler as a static model is to give themodel the required functionality. In principle a dynamic model could beimplemented if required. A dynamic model of an air to air intercooler hasbeen derived in [Muller, 1997] and [Muller et al., 1998].

56


Turbocharger State Equation

The turbocharger is driven by the energy in the hot exhaust gasses fromthe cylinders. In [Hendricks et al., 1984] and [Hendricks, 1989] it has beenshown that the outlet pressure can be modeled by a first order system. Theexhaust power is a function of the amount of fuel fed to the engine.

If it is assumed, that the power available to drive the turbine isPexhx(kW ) then the compressor outlet pressure can be found by:

pc =1τc

(−pc + f (Pexhx, n)) (5.27)

where

f (Pexhx, n) = c1(n) · Pexhx + c2

=(0.0678n2 − 0.3281n + 0.5024

)Pexhx − 0.2 (5.28)

where the constants c1 and c2 have been adjusted according to the compres-sor characteristic map in [Hendricks et al., 1984]. A compressor character-istic map is a plot of the compressor pressure ratio against the temperatureadjusted compressor mass flow (here map).

The time constant τc is found by:

τc =p

1κc

map(5.29)

where κ = cp/cv = 1.4 (The adiabatic constant) for air. The time constantshould be in the order of 1 - 3 sec at maximum mass flow [Hendricks, 1989].

In equation 5.28 the adjustment of constants and functions is carriedout by looking at the maximum volumes and pressures to be handled bythe compressor for at certain engine. The required air mass flow are judgedfrom the engine displacement and the equivalence ratios which must obtainat the highest engine output. The linear load lines in the compressor mapin figure 2 in [Hendricks et al., 2005] has been found to work generally atmedium to maximum engine loads, related to the engine speed. The par-abolic dependence of the slope on the engine speed has also been found tobe generally true.

The power to drive the turbo, Pexhx, must be a proportion of that usedto drive the engine. An effective efficiency can be used to set this proportion.This efficiency should be a factor in the order of 1−ηi

2 = 1−0.472 = 26.5% of

the fuel used to feed the engine. If mf is the fuel flow used to drive theengine, then the power can be expressed as:

Pexhx = 0.265 ·Humf · 0.157 (5.30)

57


where the factor 0.157 gives a scaling factor from exhaust power to the massflow (linear) equation, here for the target engine of 9.4 liters. During thisproject it has proven that it is possible to adjust the constants in equation5.28 and equation 5.30 to make the model capable of describing the targetengine in the entire upper operating range.

The compressor in this project is assumed to be working at the top ofits operating range, and can therefore be assumed to operate at a more orless constant efficiency. A reasonable guess for its outlet temperature canthus be given assuming an efficiency of about 73%. The outlet temperatureis then described by

Tc = Tc (ηc, prc, Ta) = Ta

(1 +

Yc

ηc

)= Ta +

Ta

ηc

(p

κ−1κ

rc − 1)

(5.31)

where ηc = 0.73, prc = pc

paand pa,Ta are respectively the ambient pressure

and temperature. The SIMULINK engine turbo block can be seen inappendix A.2.4.

Adjustment of Model - Static

The entire engine model has been implemented in SIMULINK, see appendixA.2.2.

To Benchmark and adjust the model, it has been loaded with an infinitelylarge moment of inertia without any torque load. In this way it is possibleto measure the full torque of the engine without the engine speed increasing.Thereby a torque curve can be made. The engine parameters can then beadjusted to fit the torque curve of the real engine.

The adjustment of the engine includes several steps:

Fuel function The output of the engine is controlled by the amount offuel fed to the engine. From the promotional engine data at the Volvowebsite, the power curve can be deduced and the required amount offuel calculated.

Turbo pressure When the fuelling function is correct, the turbo pressurecan be adjusted to match the real engine data.

Efficiency When the turbo pressure is correct, the efficiency of the enginecan be adjusted to produce the correct torque and power.

Fuel FunctionThe fuel function is calculated to produce the right amount of power. Bycombining equation 5.18 and equation 5.19 and inserting points from the

58


500 1000 1500 2000 25000

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

RPM

Fue

l Mas

s flo

w [k

g/s]

Maximum FuelMinimum Fuel (Idle)

Figure 5.13: Fuel Function

power curve, a number of fuel values for different engine speed can be cal-culated. With the MATLAB curvefit function a fuel function can be found:

mf = −0.01201n2 + 0.04284n− 0.02161 (5.32)

This function works from around 800 RPM and up, below this a linearfunction has been fitted to supply the engine with the correct amount offuel.

The minimum fuel fed to the engine is the idle fuel which means thenecessary amount of fuel to overcome the internal friction in the engine atidle speed. Now the engine is actually adjusted to match the target enginein regards to power and torque. Now the turbo pressure has to be adjustedto match the target engine to make sure the turbo has the right influenceon the engine. Afterwards the efficiency of the engine might have to beadjusted slightly to make the power and torque fit again.

The SIMULINK engine fuel block can be seen in appendix A.2.3.

Turbo pressureAt Volvo Truck Center Denmark A/S, a test drive was conducted in orderto measure the maximum turbo pressure. The truck was equipped with theVCADS software for monitoring the important sensors in the truck. Themaximum turbo pressure was measured, peaking at pcmax = 230kPa. Themeasurements can be seen in figure 5.14 as the red curve.

The blue line shows the simulated values after adjustment of theconstants in equation 5.30.

When the turbo pressure is confirmed to be correct the actual efficiencyof the engine can be found. It will probably deviate a bit compared to the

59


500 1000 1500 2000 25000

50

100

150

200

250

RPM

Cha

rge

Pre

ssur

e [k

Pa]

SimulatedMax, Volvo − D9A380

Figure 5.14: Maximum turbo pressure

value used in the fueling function. After a few iterative adjustments it is

500 1000 1500 2000 25000

50

100

150

200

250

300

RPM

Pow

er [k

W]

Volvo − D9A380Simulated

Figure 5.15: Engine power

500 1000 1500 2000 25000

500

1000

1500

2000

RPM

Tor

que

[Nm

]

Volvo − D9A380Simulated

Figure 5.16: Engine torque

possible to make all the values fit. And the simulation compared to realvalues can be seen in figure 5.15 and figure 5.16.

The result of the simulations also shows the real efficiency of the enginedepicted in figure 5.17, which shows that the overall efficiency is around45%. The fuel/air equivalence ration can be viewed in figure 5.18 whichshows an overall value of around Φ ∈ [0.6; 0.7] in the working area which isnormal of diesel engines at high loads. Normally Φ ∈ [0.1; 0.7].

Adjustment of Model - Dynamic

The model also needs some adjustment to fit the dynamic response of thereal engine. The real engine is capable of delivering 90% of the requested

60


500 1000 1500 2000 25000.41

0.42

0.43

0.44

0.45

0.46

0.47

RPM

Effi

cien

cy (

Eta

i)

Figure 5.17: Engine effi-ciency ηi

500 1000 1500 2000 25000.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

RPM

Equ

ival

ence

rat

io (

The

ta)

Figure 5.18: Equivalence ra-tio θ

torque after 2 sec, as seen in figure 5.4. This can be achieved by adjustingthe time constant in the turbocharger equation 5.27.

Another parameter to take into account is the fuel injection. The fuelinjection can not be changed momentarily since it will cause the equivalenceratio Φ to move outside the allowable boundaries and make the efficiencyand torque drop rapidly, because the air supply can not change rapidly seefigure 5.20. The fuel has to be lagged to follow the lag in the air supply. Atime constant related to the time constant of the turbo has therefore beenadded to the fuel input.

The results of the dynamic adjustment can be seen in figure 5.19 and fig-ure 5.20 as the red curves, compared to the blue curves without the timelag.Since the efficiency of the engine is kept as even as possible during changesin the operating point, the rise time of the torque produced is not affectedsignificantly compared to the model without the fuel lag. The result can beseen in figure 5.19

61


0 5 10 15 20 25 30 35 40 450.005

0.01

0.015

Fue

l Mas

s flo

w [k

g/s]

0 5 10 15 20 25 30 35 40 450

100

200

300

Tur

bo p

ress

ure

[kP

a]

0 5 10 15 20 25 30 35 40 45500

1000

1500

2000

Time [s]

Tor

que

[Nm

] Without timedelayWith timedelay

Figure 5.19: Engine dynamic response - Torque. It is seen that theresponse with the fuel time delay is not remarkable slower than theresponse without the time delay.

0 5 10 15 20 25 30 35 40 45

0.35

0.4

0.45

0.5

Effi

cien

cy [e

tai]

0 5 10 15 20 25 30 35 40 450.4

0.6

0.8

1

Equ

ival

ence

rat

ion

[thet

a]

Without timedelayWith timedelay

Figure 5.20: Engine dynamic response - Efficiency. The efficiencyis kept high by using a time delay in the fuel injection.

62


5.3.2 Clutch

A clutch has been implemented in the model to give the possibility of startingthe truck from 0 speed. A clutch is a rather simple device to model, inpractical it consists of three different modes:

Disengaged When the clutch is fully disengaged, no torque is transmittedthrough the clutch.

Slipping Going from disengaged to engaged, or opposite can be definedas slipping where the torque is determined primary by the dynamicfriction in the disks in the clutch.

Engaged When the clutch is engaged, the full torque is transmittedthrough the clutch.

Dynamic Model

When the clutch is disengaged the torque transmitted via the clutch Tcl iszero:

Tcl = 0 (5.33)

When the clutch is slipping the torque transmitted via the clutchis[Glielmo & Vasca, 2000]:

Tcl = kFnsign(n− ng) (5.34)

wherek = 4Rclµd/3 (5.35)

Rcl = 0.3[m] is the equivalent disk radius, µd = 0.4 [Glielmo & Vasca, 2000]is the dynamic friction coefficient. Fn[N ] is the force on the clutch. n andng are the rotational speed of the crankshaft and the input axle in thegearbox.

When Tcl becomes higher than the load torque Tl the clutch is engaged,and the torque transferred is equal to the torque delivered to the clutch fromthe engine.

Tcl = Te (5.36)

andne = ng (5.37)

The clutch has been implemented in the SIMULINK model which canbe seen in appendix A.2.6.

63


5.3.3 Gearbox

The gearbox is primarily a number of different gear ratios to convert thetorque from the engine to the rear axle. The gearbox implemented includesthree special functions, to imitate the real gearbox:

Start-up gear The gearbox calculates which gear it is possible to use asa start up gear, by means of weight of the vehicle and gradient of theroad.

Decision of gear shift The gearbox follows a number of rules about whento shift gears.

Shifting sequence The shifting sequence is implemented as the real gear-box, i.e. the engine is used to control the speed of the gears to makethem synchronize when shifting.

Start-up Gear

The startup gear is selected automatically. It can vary from 1-6 dependenton the load in the initial start up moment. Based upon the torque the engineis capable of producing at 800 RPM, the highest possible start up gear isselected compared to the torque from the weight of the vehicle and gradientof the road.

Decision of Gear Shifts

As described in section 5.1.2 the gearbox has a number of different rulesfor which affects the gearshift. These are affected by the throttle posi-tion and the load on the engine. These rules are all implemented in theSIMULINK model, to use the shifting strategy depicted in figure 5.6. TheEconomy/Power mode can be selected to affect the shifting strategy.

Shifting Sequence

One of the most important extensions of the gearbox compared to the firstmodel is the sequence of shifting a gear. This includes a number of statesas depicted in figure 5.21: The shifting sequence includes 8 steps, all imple-mented in the SIMULINK model, which can be found in appendix A.2.7, andin the MATLAB file gear shift function.m which can be found in appendixB.

Command to shift gears A command from the computer to shift gearsis received.

Request zero torque A request for zero torque in the gearbox is parsedon to the throttle control, i.e. cut fuel to idle level.

64


Figure 5.21: Gearbox shifting sequence

Wait Wait for the torque to drop to zero.

Shift to Neutral Disengage the old gear, go to neutral.

Change RPM for new gear ratio If the new gear is higher than the oldgear, the engine needs to decrease RPM. This is performed by cuttingthe throttle and engaging the engine brake to make the RPM decreaserapidly. If the new gear is lower than the old gear, the engine needsto increase RPM. This is accomplished by increasing the throttle.

Wait Wait for the correct engine speed.

Engage new gear When RPM is correct, engage the new gear.

Put on torque again The shift is completed and torque transfer can bereestablished.

The whole sequence is completed within a few seconds, but the torqueto drive the vehicle is zero during the shift, which causes the vehicle to loosespeed especially if it is carried out on a steep gradient. The sequence isdepicted in figure 5.22 and figure 5.23, respectively shift down and shift up.

5.3.4 Evaluation

Compared to the first model, the 2nd model is more alike the real drivelinein a truck. Specially the fuel usage is now very accurate, because the wholedriveline is based on the input of fuel, compared to the first model wherethe fuel was calculated separately.

Delays from fuel input and turbo has now been modeled in more details,and on the basis on more tests.

One of the forces about the 2nd model is the ability to be adapted todifferent engines. In this case it has been adapted to a 9.4L 380HP engine,however it is easy to adjust the model to fit another diesel engine, only thefuel function and turbo pressure has to be adjusted to match the new engine.

The whole SIMULINK diagram of the 2nd model can be seen in appendixA.2.1.

65


34 34.5 35 35.5 36 36.5 37 37.5 380

0.51

Thr

ottle

34 34.5 35 35.5 36 36.5 37 37.5 380

1000

2000

Tor

que

[Nm

]

34 34.5 35 35.5 36 36.5 37 37.5 38

11

12

Gea

r

34 34.5 35 35.5 36 36.5 37 37.5 380

0.51

VE

B

34 34.5 35 35.5 36 36.5 37 37.5 380

0.51

Neu

tral

34 34.5 35 35.5 36 36.5 37 37.5 381000

1200

RP

M

Time [s]

EngineGearbox

Figure 5.22: Gear shift sequence - shift down

1048 1049 1050 1051 1052 1053 10540

0.51

Thr

ottle

1048 1049 1050 1051 1052 1053 10540

1000

2000

Tor

que

[Nm

]

1048 1049 1050 1051 1052 1053 1054

10

11

Gea

r

1048 1049 1050 1051 1052 1053 10540

0.20.4

VE

B

1048 1049 1050 1051 1052 1053 10540

0.51

Neu

tral

1048 1049 1050 1051 1052 1053 10541000

1500

2000

RP

M

Time [s]

EngineGearbox

Figure 5.23: Gear shift sequence - shift up

66

5. Truck 5.4. Tests

5.4 Tests

A number of tests have been carried out in order to evaluate the two completedeveloped models against the available real data. The tests includes:

Fuel consumption Average fuel consumption test during highway driving.

Climbing capacity The models climbing capacity on known gradientscompared to the reference truck.

Acceleration Acceleration time of the truck including all gearshifts.

5.4.1 Fuel Usage

The fuel tests has been carried out at the available GIS data of Route 21from Holbæk to Copenhagen. Parameters like aerodynamic drag and rollingresistance have been tuned to match the real fuel consumption.

Reference truck 1st model 2nd model3.1 km/l 3.1 km/l 3.1 km/l

Table 5.4: Average fuel tests, Route 21. 24.7 tons, 85 km/h

5.4.2 Climbing Capacity

Both models are tested on the gradient near Varby at the E20. The mini-mum speed on the gradient has been compared to the real truck.

Reference truck 1st model 2nd model65 km/h 63.5 km/l 64.8 km/h

Table 5.5: Minimum speed test, E20. 24.7 tons, 85 km/h

5.4.3 Acceleration

Both models are tested in relation to acceleration from 0 km/h to 80 km/h,to compare the time used for gearshifts and acceleration on the real truck.

It should be noticed that the 1st model is not capable of shifting morethan 1 gears at a time, thus it takes more time for the 1st model to accelerate.It should also be taken into account, that the reference test includes somedisturbance due to the road where the real truck was tested.

67

5. Truck 5.5. Summary

Weight/Mode Reference truck 1st model 2nd model12 t/Eco 33.3 s 44.0 s 34.0 s12 t/Power 32.0 s 41.5 s 31.7 s24 t/Eco 43.5 s 56.5 s 42.0 s24 t/Power 35.5 s 52.0 s 36.0 s

Table 5.6: Acceleration test, 0 km/h - 80 km/h

5.5 Summary

Three real trucks has been examined and tested in regards of several pa-rameters. On the basis of these tests and promotional data, two modelshas been developed. The models are adapted to respond as the real trucks,specially in regards to torque, speed and fuel consumption.

The first developed model was based on the need of a feasibility study,and proved to be useful in tests of a simple controller.

The second controller is an improved version of the first model, speciallyin regards to fuel consumption, behavior of engine and gearbox complexity.

68

Chapter 6

Controller

This chapter is a description of the control strategy developed in this project,and of the implemented and tested controllers.

First of all, this part is linked together with the rest of the project asdepicted in figure 6.1. The controller includes reference data, two maininputs and one output.

Figure 6.1: Controller part of the project.

Reference data The controller uses a number of reference data to adjustthe shifting strategy, that includes a number of data of the truck,engine, weight, aerodynamic properties, etc. and some inputs fromthe driver whether the gearbox should optimize for power or economy.

Inputs The first main inputs are the current state of the truck, i.e. thespeed, engine speed, gear, etc. The other input is the road profilefrom the GPS/GIS system which the controller uses for predicting ifa gear shift is advantageous.

Output The output are the commands to be sent to the gearbox, (or thecomputer controlling the gearbox) if the gear shift strategy should bechanged.

69

6. Controller 6.1. Reference Data

The different controllers implemented in this project includes more orless of the above parameters.

6.1 Reference Data

The reference data are the inputs that the controller uses and which donot changing normally during driving. This includes parameters such asthe truck characteristics and reference values. These data are used to givea reference for the controller of when the gradient is too steep to climbusing the present gear, or if the truck can handle the gradient only by itsmomentum. Other reference data are the inputs from the user like thedesired reference speed, shifting strategy and Economy/Power mode.

6.1.1 Truck Data

The most important truck parameters are:

Weight The weight of the truck influences the rolling resistance negatively,but also contributes to a higher momentum.

Engine power/torque Torque the engine can produce i.e. which gradientthe truck can climb without making gearshifts.

Time constants How long does a gearshift takes, how much speed will thevehicle loss during a shift.

Gear ratios When is it most efficient/economic to shift from one gear ratioto another, compared to the profile of the torque curve.

Aerodynamic The aerodynamic parameters of the truck affects the nec-essary amount of torque to overcome the aerodynamic resistance.

6.1.2 Driver Inputs

Shifting strategy The driver is in some way given the possibility of de-ciding which program the controller should use, if it should shift mosteconomical or most powerful, or somewhere in between.

Reference speed The reference speed is also affecting the strategy sincemore speed entail more aerodynamic resistance, but also more mo-mentum.

70

6. Controller 6.2. Inputs

6.2 Inputs

6.2.1 Truck States

The inputs to the controller are provided from the truck itself, that meansdata like the present speed, the present RPM, etc.

Speed The speed should be kept at the reference speed, but when it goesbelow, the controller has to be affected, since the necessity for lookingfar ahead on the road is changed, if the truck is climbing a hill with40 km/h instead of the reference of 85 km/h.

Engine speed The current speed of the engine is important, to let thecontroller decides if it is advantageous to shift gear to produce moretorque.

Gear The current Gear is also important, since this affect the hill climbingcapacity of the truck.

6.2.2 Road Sequence

The road ahead is fed to the controller in the form of position and gradientdata. These data are combined with the other input data, and the differentrules in the controller decides when to change strategy.

6.3 Outputs

The decisions made by the controller can be transmitted to the truck in twoways, either as direct orders or as an adjustment of present strategies.

Direct orders Direct orders for a particular gear can be transmitted tothe gearbox when the controller decides from the map, that it wouldbe advantageous.

Max Gear Another solution is to change the maximum allowed gear touse. In some way it will give the same result as the above solution,but the advantage is that if the truck is not running at top speed,i.e. because of weather conditions, the flow on the road or alike, thesystem will not affect the gearbox.

Change limits A solution to move the limits of when to shift gear hasalso been implemented. This solution has the advantage that it isworking like parsing a suggestion to the gearbox and not a directorder. This gives a more noise resistant system because if the truckis not reacting exactly like the controller has predicted, it will stillshift when it reaches the new limit of shifting. No matter if its a little

71

6. Controller 6.4. Controllers

earlier or later. It can also be seen as a safer way of using the gearboxbecause the gear shift can never be ordered on too high RPM or alike.The gearbox will always wait to shift until it reaches the new desiredRPM limit which are also defined in between the safe limits.

6.4 Controllers

Three controllers have been implemented and tested in this project. Theyare all compared to the reference system, which is the normal gearbox con-trol. The three controllers are:

Simpel - Economy/Power The first controller is very simple. It makesuse of the difference in the Economy/Power mode by switching toPower mode, when the gradients of the road ahead increases above acertain limit.

Rule based for 1st model A very simple rule based controller is imple-mented for the 1st simple simulation model. When the gradient of theroad rises above a certain limit it changes the maximum allowed gear.

Rule based for 2nd model A more advanced rule based controller hasbeen developed for the 2nd model. This controller uses a numberof inputs to decided which shifting strategy should be used. Thiscontroller can also be adjusted by the driver to give more or less poweror better economy.

6.4.1 Normal - Reference

The reference performance for all the controllers, is the standard systemimplemented in the I-shift gearbox. This system is described in detail insection 5.1.2. Basically this system uses some predefined limits for the RPMof the engine, when these limits are reached either up or down a gearshiftis carried out. However the limits are not permanent, but are affected bythe throttle level and load on the truck. This function can be seen in figure5.6. The new controllers are evaluated up against this reference, however itshould be taken into account that this reference is not 100% correct since ithas not been possible to acquire the real data of the gearbox due to patentsecurity. The gearbox has been based of the result of different tests andpromotional data of the real truck and gearbox.

6.4.2 Simple - Economy/Power

The first simple controller to test is the use of the two different standardmodes, Economy or Power, normally selected by the driver on a small buttonbehind the gear lever. As described in section 5.1.2 the normal engine speed

72


where the gearbox shifts down is increased from 1050 to 1200 RPM, likewisethe limit for shifting up is increased from 1600 to 1700 RPM.

6.4.3 Rule Based for 1st Model

The first simple rule based controller is developed for a feasibility study,whether it is advantageous to use the GPS/GIS data to control the gearbox.It only includes one simple rule and is of the type Max Gear as describedin section 6.3.

The gradient of the road is compared to a simple calculation of theclimbing capacity of the truck by taking the weight and engine torque ofthe vehicle into account. If the gradient of the road on the actual positionis above a certain level, the gearbox is forced to shift one gear down. If thegradient exceeds a larger limit, the gearbox will shift two gears down. Thisis a very simple strategy but has been proven to give a result that shows thesystem is working.

1.1 1.2 1.3 1.4 1.5 1.6

x 104

0

0.02

0.04

0.06

0.08

0.1

Gra

dien

t [%

]

1.1 1.2 1.3 1.4 1.5 1.6

x 104

10

11

12

Position [m]

Gea

r

Figure 6.2: E20, Varby, gradient and gearshift strategy

On figure 6.2 the gradient on the road near Varby at E20 is shown, bythe blue curve. The red curve shows the maximum gear on the hill, meaningthat the gear sequence the truck should use up the gradient is 12-11-10-11-12.

6.4.4 Rule Based for 2nd Model

The 2nd rule based controller for this project is developed on the backgroundof several rules, used to improve the gearshift strategy with a number ofdifferent goals.

73


Unfortunately the physics do not allow optimizing a controller to giveboth optimal economy and optimal power, since these two requirementsare contradictory. If the most economic solution is preferred it is to thedetriment of the power. And opposite, if full power is preferred, it is to thedetriment of the fuel economy.

Mostly the normal controllers are based on giving the best fuel economy,thus the controller implemented here are mostly focused on maximizingpower for climbing steep gradients as fast as possible. Afterwards the areain between the two solutions has been investigated to give the driver theability of choosing between the performance criterions.

Most Power/Best Economy

The dynamics of a diesel engine gives a number of characteristics that cangive a number of simple rules of which gear the engine should use for deliv-ering the most torque, or the best economy [Jacobson, 2004]. These bound-aries are highly valuable for the gearbox controllers. In figure 5.13 the fuelconsumption when producing maximum torque is depicted and in figure 5.16the maximum torque is depicted. These curves can be used for deriving atwhich engine speed it is appropriate to shift gears compared to economy orpower. In figure 6.3 the delivered torque to the rearaxle in 11th, and 12th

800 1000 1200 1400 1600 1800 20001000

1500

2000

2500

RPM (12. gear)

Tor

que

12 gear11 gear

Figure 6.3: Torque output in 12th and 11th gear

gear is depicted, the RPM at the x-axis is refers to the 12th gear. The RPMof the 11th gear has been multiplied with a factor equal the difference ingear ratio between 11th/12th gear. The intersection between the two curvesgives the RPM at which a gear down should be performed, if maximumtorque is requested. The RPM at the intersection is 1477 RPM between the12th and 11th gear.

Similarly in figure 6.4 the function of torque delivered per fuel unit hasbeen plotted against RPM of the 11th gear and 12th gear. The RPM at

74


800 1000 1200 1400 1600 1800 20000.6

0.8

1

1.2

1.4

1.6

1.8

2

x 105

RPM (12. gear)

Tor

que/

fuel

12 gear11 gear

Figure 6.4: Economy in 12th and 11th gear

the x-axis again referring to the 12th gear. That means, where the lines arecross the shift down should be performed. The figure shows that the mosteconomic RPM to shift down from 12th to 11th gear is 1046. In table 6.1the similar up/down limits are shown.

Power EconomyGear Up Down Up Down1. 1878.1 - 1329.5 -2. 1894.0 1474.6 1341.5 1043.93. 1879.0 1459.7 1330.2 1033.84. 1882.2 1473.7 1332.6 1043.35. 1887.1 1470.7 1329.5 1041.26. 1871.9 1474.6 1325.1 1043.97. 1878.4 1480.4 1329.7 1047.98. 1894.4 1474.3 1341.7 1043.79. 1879.7 1459.4 1330.7 1033.610. 1879.8 1473.1 1334.4 1042.811. 1875.7 1468.4 1327.7 1039.612. - 1476.9 - 1045.5

Table 6.1: Power and Economy engine speed for the drive modes.Optimal shift up and down.

It is clear to see that the Economy mode is always lower that the Powermode. Which also complies to the result of using the Power/Eco button inthe real truck, which mainly increases the RPM in the Power mode.

It is also seen that a normal gearshift should always be performed be-

75


tween those limits. Never below the Economy limits and never above thePower limits, that will cause both worse fuel economy and less power. Theone exception to this rule will be during acceleration where some gears areskipped, thus RPM will go higher to accommodate a gearshift of two gears.A table similar to table 6.1 could be calculated for 2 or more gears in a shift.But for this controller only one gear has been taken into account.

Maximum Gradient

The truck is capable of handling a certain gradient, in every gear. If thegradient exceeds this limit, it should be considered if another gear should beselected. The maximum gradient to be handled by the truck is straight for-ward to calculate from the equations describing the resistance forces actingon the vehicle, described in section 5.3

Fdl = Fae + Fro + Fcl (6.1)

i.e. at maximum gradient the driveline force is equal to the sum of resis-tance forces (Aerodynamic, Rolling and Climbing). The total equation ofthe maximum gradient (with a minor simplification in the dependence ofgradient in the rolling resistance, causing an error of 0.1%).

θ = sin−1

Temax igirηgηr

rw− 0.5σcwAv2 − fmg

m · g

(6.2)

As example, for a speed of 85 km/h the maximum gradient the truckcan climb in top gear is 0.95%, and in 11th gear it can climb 1.48%. Allgradients smaller than the maximum climbable gradient in the top gear arenot important for the controller.

Truck Momentum

The next step to consider is the momentum of the truck. Some of thegradients in figure 6.5 are so small that the truck will force the gradientwith only a small decrease in the speed. Smaller than the decrease in speedby making a gearshift or smaller than the driver is willing to accept. Anestimate of the resulting decrease in speed can be calculated and if this ismore than the accepted limit, the limits for the gearbox can be changed toexpedite a shift down. The estimate can be computed from the momentumof the truck and the integral of the gradient.

Momentum of truck:p = mv (6.3)

where p is the momentum of the truck in [kg ·m/s] or [Ns], m is the mass ofthe vehicle, and v is the velocity in [m/s] . It is thus given, that the changein momentum gives the change in speed:

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0 20 40 60 80 100 120−5

0

5

Gra

dien

t [%

]

Position [km]

0 20 40 60 80 100 120

0

1

2

3

4

Gra

dien

t exc

eed

[%]

Position [km]

Figure 6.5: [Top] Gradient of the road between Linkoping toJonkoping. [Bottom] Gradients that exceeds the maximum climbablegradients of the truck in 12th gear. FM9-380HP, 40 tons.

∆p = m ·∆v (6.4)

From the 2nd law of Newton it is also known that:

F =∆p

∆t(6.5)

where F is the resulting force acting on the vehicle, and t is the time inseconds.

Combining equation 6.4 and equation 6.6 gives:

∆v =F ·∆t

m(6.6)

The fact that:∆t =

s

v(6.7)

where s is the distance in meters. Taking the integral of a gradient inregards to the distance gives a total expression for the loss of speed climbinga certain gradient:

∆v =

∫ gendgstart

F (s)ds ·mv

(6.8)

where gstart and gend are the beginning and end of the gradient.On figure 6.6 this result has been depicted. It can be seen that the speed

of the vehicle will drop with approximately 55 km/h on the steepest gradientif 12th gear is used and if a gearshift is introduced it can be decreased to

77

6. Controller 6.5. Summary

around 40 km/h. Now it is fairly straight forward to decide how muchthe speed is allowed to drop before a gearshift should be considered. This

0 20 40 60 80 100 1200

10

20

30

40

50

60

Est

imat

ed s

peed

dec

reas

e [k

m/h

]

Position [km]

12 gear11 gear

Figure 6.6: Estimated decrease in speed on steepest gradients be-tween Linkoping and Jonkoping, using 12th or 11th gear. FM9-380HP, 40 tons.

parameter could be decided by the driver, but tests has shown that therelationship between speed decrease and economy/power is not simple. Andtests should therefore clarify what the optimal limit for a speed decreaseshould be. These will be carried out in chapter 7. The 2nd rule basedcontroller is implemented in the MATLAB file road section calc.m whichcan be found in appendix B.

6.5 Summary

This chapter has dealt with 3(+ reference) different controllers, two sim-ple controllers, and one more advanced, based on rules derived from theadvanced model.

The first simple controller, based on the Economy / Power mode is verysimple and makes use of the fact that the engine produces a higher torqueat a higher RPM, but the economy is worse.

The second simple controller uses information about the gradient of theroad at that section it is driving of. If the gradient is above a certain limit,a shift down is imposed.

The last advanced controller also uses information about the gradient ofthe road, but it looks up the road, and estimates the loss of speed on theimminent gradient. If that loss of speed is more than an acceptable limit,the shifting strategy of the gearbox is changed.

78

Chapter 7

Tests and Results

This chapter describes tests and associated results of the different parts ofthe project. The test is divided in two main parts plus a summary in theend:

Road Information Test of the GIS, GPS and a very simple controller.This is mainly the parts that should be installed in a real truck tomake use of the system.

Controllers The two models are tested with different controllers to mea-sure the performance of using the improved system. Parameters likespeed, fuel consumption and gear shifts have been measured and com-pared to the reference model.

Summary A summary of the tests, to give a clear overview of the gainedperformance compared to reality and the difference of model 1 and 2.

7.1 Road Information

This part of the system is as described in chapter 4 mostly a feasibilitystudy, since some parts of the system are already installed and used innormal vehicles. This part is only superficial implemented to test whetherit is possible to supply a controller with road profile data, and the associatedtests are carried out in order to test the overall functionality. Thus accuracyof GPS, GIS, map matching algorithm etc. are not tested.

Test/Evaluation of this part of the project is carried out by combiningGIS data, GPS data and a very simple controller for the gearbox, and testwhether these parts can work together and produce a result that supportsthe possibility of using a 3D map for control of a gearbox.

The whole implementation is depicted in figure 7.1 where the test vehi-cle (car) is running along highway E47/E55 heading south, with a velocity

79

7. Tests and Results 7.1. Road Information

around 100 km/h. The green markers in the upper left plot are the actualGPS positions, and the black dots are the matched positions on the realblue highway. Based on this, the program finds the altitude and gradients

Figure 7.1: Program calculating the road sequence ahead of the ve-hicle

of the road in front of the vehicle, and plots this in a contour plot on thelower right plot.

The position of the vehicle is the black dot heading to the right, whichmeans up the hill.

Right above this plot, a small label indicates the maximum gear to be11th gear instead of the normal 12th gear in the vehicle, i.e. the programdecides it is more efficient to drive up this particular gradient in 11th gear.

The functionality of this part of the project is evaluated, the program iscapable of tracking the GPS position to a digital map, finding the gradientsof the road ahead of the vehicle, and based on this give a simple command tothe driver to shift down one or two gears. With the accuracy and implemen-tation time of this parts it is a very satisfactory result, and the possibilityof developing a real useful system seams possible.

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7. Tests and Results 7.2. Controllers

7.2 Controllers

A total of four controllers (1 reference, and 3 new improved) has been im-plemented in chapter 6. In this part the controllers has been tested againsteach other, to measure the gained performance. This section is divided intwo parts, first a comparison test and after that a detailed test of the finaladvanced controller implemented on the 2nd model.

7.2.1 Comparison Test

The comparison test includes 5 different test scenarios, including bothmodels and three controllers. All the test includes:

1st Model, reference Due to the minor differences between the 1st modeland 2nd model, both of the models are used as reference to the differentcontrollers.

1st Model, E/P controller The simple Economy/Power controller usedon the 1st model.

1st Model, simple controller The simple rule based controller derivedfor the 1st model.

2nd Model, reference Reference for the controllers applied to the 2ndmodel.

2nd Model, E/P controller The simple Economy/Power controller usedon the 2nd model.

2nd Model, simple controller The simple rule based controller derivedfor the 1st model, but used on the 2nd model

2nd Model, Advanced controller The advanced rule based controllerspecially derived for the 2nd model.

All of the controllers are tested on 5 different pieces on road. E20, includ-ing one large gradient, E47/E55 - a rather flat road. Route 21, includingtwo steep gradients. E4 real road data from Sweden, including more steepgradients tested in both directions.

81


E20

0 5 10 15 20 2520

30

40

50

60

70

80

90

Spe

ed [k

m/h

]

Position [km]

ReferenceE/PSimple Rule

Figure 7.2: E20 - 1st Model,85 km/t, 40 tons

0 5 10 15 20 2530

40

50

60

70

80

90

Spe

ed [k

m/h

]

Position [km]

ReferenceE/PSimple RuleAdvanced Rule

Figure 7.3: E20 - 2nd Model,85 km/t, 40 tons

Controller Min. speed Avg. speed Fuel usage Gearshifts1st Model [km/h] [km/h] [%]Reference 26.17 72.32 - 8

E/P 31.21 73.54 +0.18 10Simple Rule 33.27 74.24 +0.07 6

Controller Min. speed Avg. speed Fuel usage Gearshifts2nd Model [km/h] [km/h] [%]Reference 30.65 75.77 - 6

E/P 35.19 76.54 +0.06 6Simple Rule 40.84 79.32 +0.84 5

Advanced Rule 43.11 79.31 -0.14 6

CommentsDriving E20 east, from The Great Belt Bridge to Slagelse East, includesone very steep gradient near Varby. As seen in the figures 7.2 and 7.3, theminimum climbing speed can be improved and thereby the average speed.In one case the advanced controller on the 2nd model, it is possible to lowerthe fuel usage a little without using more gearshifts.

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Route 21

0 10 20 30 40 50 6020

30

40

50

60

70

80

90

Spe

ed [k

m/h

]

Position [km]


Figure 7.4: Route 21 - 1stModel, 85 km/t, 40 tons

0 10 20 30 40 50 6030

40

50

60

70

80

90

Spe

ed [k

m/h

]

Position [km]


Figure 7.5: Route 21 - 2ndModel, 85 km/t, 40 tons


E/P 65.48 82.20 +0.08 4Simple Rule 69.12 83.72 +1.39 12


E/P 65.83 83.74 -0.12 4Simple Rule 69.02 83.94 +2.06 10

Advanced Rule 69.61 84.13 +2.70 8

CommentsDriving Route 21 east, from Holbæk to Copenhagen, features three signif-icant gradients. As seen in the figures 7.4 and 7.5, the minimum climbingspeed can be improved and thereby the average speed. In one case, the E/Pcontroller on the 2nd model, features a lowered fuel usage. But in regardsto speed this solution is not superior.

83


E47/E55

0 10 20 30 40 50 6020

30

40

50

60

70

80

90

100

Spe

ed [k

m/h

]

Position [km]


Figure 7.6: E47/E55 - 1stModel, 85 km/t, 40 tons

0 10 20 30 40 50 6030

40

50

60

70

80

90

100

Spe

ed [k

m/h

]

Position [km]


Figure 7.7: E47/E55 - 2ndModel, 85 km/t, 40 tons


E/P 54.81 79.34 +0.35 8Simple Rule 60.14 82.46 +1.70 14


E/P 57.36 82.90 +0.40 6Simple Rule 60.71 83.53 +2.39 10

Advanced Rule 62.12 83.44 +0.88 6

CommentsDriving E47/E55 north, from Lyngby to Helsingør, features two significantgradients, and a number of smaller gradients on the limit of being significant.As seen in the figures 7.6 and 7.7, the minimum climbing speed can beimproved and thereby also the average speed, but not as much due to therather short gradients. All tests shows an increased fuel usage.

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E4 Linkoping - Jonkoping

0 20 40 60 80 100 120 14020

30

40

50

60

70

80

90

100

Spe

ed [k

m/h

]

Position [km]


Figure 7.8: E4 Linkoping -Jonkoping - 1st Model, 85km/t, 40 tons

0 20 40 60 80 100 120 14030

40

50

60

70

80

90

100

Spe

ed [k

m/h

]

Position [km]


Figure 7.9: E4 Linkoping -Jonkoping - 2nd Model, 85km/t, 40 tons


E/P 69.90 84.56 +0.36 8Simple Rule 74.25 84.37 +1.23 48


E/P 70.01 84.74 +3.20 10Simple Rule 74.40 85.00 +2.50 37

Advanced Rule 74.61 85.03 +3.54 12

CommentsDriving E4, from Linkoping towards Jonkoping, features a number of smallergradients. As seen in the figures 7.8 and 7.9, the minimum climbing speedcan be improved a little and also the average speed using the 2nd model.All tests shows an highly increased fuel usage compared to the gained per-formance of speed.

85


E4 Jonkoping - Linkoping

0 20 40 60 80 100 120 14020

30

40

50

60

70

80

90

100

Spe

ed [k

m/h

]

Position [km]


Figure 7.10: E4 Jonkoping- Linkoping - 1st Model, 85km/t, 40 tons

0 20 40 60 80 100 120 14030

40

50

60

70

80

90

100

Spe

ed [k

m/h

]Position [km]


Figure 7.11: E4 Jonkoping- Linkoping - 2nd Model, 85km/t, 40 tons


E/P 42.70 81.72 +0.36 22Simple Rule 36.95 81.43 +1.23 28


E/P 45.71 83.06 -0.76 20Simple Rule 39.86 83.22 -0.44 30

Advanced Rule 51.14 83.55 +0.34 18

CommentsDriving E4, from Jonkoping towards Linkoping, features two very steep gra-dients, and a number of smaller gradients. As seen in the figures 7.10 and7.11, the minimum climbing speed can be improved significantly and theaverage speed too. Speed is significantly increased by the advanced con-troller even the number of gear shifts is the lowest. Fuel usage is fluctuatingbetween the different controllers.

86


Evaluation

To give an overview of the average performance of the different controllers,all the results from the past test has been put together in table 7.1. The table

Model Min. speed Avg. speed Fuel usage Gearshiftsand Increase Increase Increase Increase

Controller [%] [%] [%] [%]1st - E/P 7.82 0.85 0.33 113.76

1st - Simp. Rule 9.05 1.31 1.00 419.162nd - E/P 7.59 0.44 0.87 180.38

2nd - Simp. Rule 8.69 0.91 1.30 512.672nd - Adv. Rule 16.81 1.09 1.86 195.40

Table 7.1: Combined results of tests, FM9-380, 40 tons.

shows that the results obtained using different controllers are of variablecharacteristics. It is hard to determine which of them are the best.

The E/P controller gives surprisingly positive results, taken into accountthat this controller is only using the road information to determine if thetruck is in hilly locations.

The Simple Rule controller also performs good but the drawback of thiscontroller is the high amount of gearshifts, 4 to 5 times as many gearshiftsas the normal controller.

The Advanced Rule controller gives a good average result. It gives thehighest minimum speed which are one of the main goals of this project, butit also gives the second best average speed improvement. The drawbacks arethe high fuel usage and high amount of gearshifts, close to twice as many asnormal.

The Advanced Rule controller has an advantage compared to the othercontrollers. It has more possibilities of being optimized and it takes moreparameters into account when deciding which gears to use. Therefore thiscontroller is further tested in the following section.

7.2.2 Detailed Test of Final Controller

The advanced rule based controller is tested in regards to a number of dif-ferent parameters to investigate how parameters as speed, and weight in-fluences the performance of the controller. Also the allowed decrease inspeed, to be determined by the driver is tested, to investigate speed and fuelconsumption. The highway E4 from Jonkoping to Linkoping, a distance of127 km has been used for testing the controller. This road is made of realmeasurements and includes a number of small and large gradients.

87


Reference Speed

The dependence of the vehicle speed has been investigated to see if thesystem performs equal at different speed or not. The speed has been variedfrom 80 to 90 km/h which are the normal range of highway cruising speedof trucks.

80 85 9025

26

27

28

29

30

Min

. spe

ed [%

]

80 85 901

1.05

1.1

1.15

1.2

Avg

. spe

ed [%

]

80 85 900

1

2

3

Fue

l usa

ge [%

]

Reference speed [km/h]80 85 900

50

100

150

Gea

rshi

fts [%

]

Reference speed [km/h]

Figure 7.12: Variation in vehicle cruising speed from 80 km/h - 90km/h. Driving Jonkoping to Linkoping, 40 tons, allowed speed drop5 km/h.

CommentsFrom the results in figure 7.12 it can be seen that the performance of thecontroller is affected by the reference speed. The increased minimum speedis higher when the reference speed is high, due to the increased momentumof the vehicle. The increased average speed is highest at low speed, due tothe larger potential of extra torque of the engine at that speed. The fuelusage is increased at all tests. Gearshifts are the same at low speed, butmore than doubled at high speed.

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Weight

The vehicle weight has been varied to investigate if the system performs bestif the truck is heavy or light. The weight of the truck has been varied from16 to 48 tons. Which are normal weight of trucks. (48 tons, is maximalweight in Denmark. 60 tons is maximal weight in Sweden which could havebeen used, due to the fact that the road section is Swedish. However it isnot normal only to use 380HP for 60 tons).

10 20 30 40 50−10

0

10

20

30

40

Min

. spe

ed [%

]

10 20 30 40 500

0.5

1

1.5

Avg

. spe

ed [%

]

10 20 30 40 500

0.5

1

1.5

2

2.5

Fue

l usa

ge [%

]

Weight [tons]10 20 30 40 50

100

150

200

250

Gea

rshi

fts [%

]

Weight [tons]

Figure 7.13: Variation in vehicle weight from 16 tons - 48 tons.Driving Jonkoping to Linkoping at 85 km/h, allowed speed drop 5km/h.

CommentsFrom the results in figure 7.13 it is clear that the largest potential of thesystem is at high vehicle weight. Fuel and number of gearshifts are fluctuat-ing but a small tendency in the results shows better performance in regardsto fuel despite of the increased use of gearshifts around 30 tons. It might bedue to some kind of match between 30 tons and 380 HP.

89


Allowed Speed Decrease

The controller uses a driver input to decide when to shift gears. If thepredicted speed loss is more than a specified limit, the controller forces agearshifts. This limit has been tested from 1 km/h below reference speed to20 km/h below reference speed.

0 5 10 15 205

10

15

20

25

30

Min

. spe

ed [%

]

0 5 10 15 200.4

0.6

0.8

1

1.2

1.4

Avg

. spe

ed [%

]

0 5 10 15 20−1.5

−1

−0.5

0

0.5

1

Fue

l usa

ge [%

]

Allowed speed drop [km/h]0 5 10 15 20

−50

0

50

100

150

200

Gea

rshi

fts

Allowed speed drop [km/h]

Figure 7.14: Variation in allowed speed drop from 1 km/h - 20km/h. Driving Jonkoping to Linkoping at 85 km/h, 40 tons.

CommentsFrom the results in figure 7.14 it can be seen that there is a clear relationshipbetween the performance of the system compared to the allowed speed drop.If a smaller speed decrease is allowed, the average and minimum speed isincreased, but to the detriment of the fuel usage and number of gearshifts.Likewise if a larger speed drop is allowed, the increase in speed is smallerbut the fuel usage and gearshifts is lowered. It is interesting to see that thefuel usage can be decreased with more than 1 % and gearshifts decreasedwith 25% and still the average speed is increased with more than 0.5% andthe minimum speed is increased with 8%.

90

7. Tests and Results 7.3. Summary

7.3 Summary

Road InformationThe tests shows that it is possible to use an integrated GIS/GPS system tofeed the gearbox controller with information about the road ahead of thevehicle. However it has proven to be difficult to procure a 3D map, and theresult of the GIS/GPS is therefore on the basis of that. No coinciding datahas been available of the road sections.

ControllersIt is clear that the performance of the vehicle can be changed using roadinformation as input to the controller. It is also clear from the test of theadvanced controller, that some kind of tradeoff between the wish for speedand economy has to be made.

The controller performance also changes when the reference speed andvehicle weight changes.

The differences between the performance of the 1st and 2nd model isnegligible, but it is hard to defend to use the 1st model on this basis. Dueto fact that large assumptions has been made, and the model is developedon the bases of weak foundations.

91

Chapter 8

Discussion

8.1 Road Information

This part of the project has been carried out mostly as a feasibility study. Itincludes simple working versions of GIS, GPS, Map Matching, Road Sequenceand a simple Controller for testing.

The system is tested on surrounding highways and the results describedin chapter 7 shows that the system is working as expected. The availableGIS and GPS data is interacting through a Map Matching algorithm anda controller gives a simple output to the driver of the vehicle to shift gearswhen the road profile requests it.

This part of the project has not been further developed, due to the fact,that many of the parts are already implemented in far more sophisticatedversions in the present GPS systems used in vehicles today. However theextension of the map from 2D to 3D has been investigated and procuring asuitable 3D map seems to be the largest task. The possibility of creating amap from available GPS data when driving on roads has been investigatedand shows positive results. An online global map updating function, wherevehicles measures and transmits data to a global map facility, seems possible.

The controller tested in this part is very simple, but should be extendedwith the functionality of the advanced controllers, described in chapter 6.

Implementing the advanced controllers would make it possible to maketests in real life by an open-loop solution in a truck (command send to driveronly). To test if the system is deciding the optimal way to handle gradientscompared to the defined control-actions. Later on the system could beimplemented in closed loop, controlling the gearbox directly.

93

8. Discussion 8.2. Model

8.2 Model

During the project, two models has been implemented to test the perfor-mance of the system. It was not possible to test the system on a real truck,instead the two models has been implemented and adjusted to reflect a realtruck as close as possible. Real data and tests on real truck has been carriedout in order to create enough reference data to implement a good modelbehaving like a real truck.

In the first attempt, a simple model was created based on simple equa-tions and basic knowledge of trucks. This model was used as a feasibilitystudy of the whole project to see whether the result of the implementedsystem reacted and responded like intended and described in the problemstatement.

The result of the first model was positive, and the new improved secondmodel was developed to make the model and achieved results as close aspossible to reality, to make it plausible that this system would performsimilar in real life.

This model is tested with a number of controllers, spanning from verysimple to advanced rule based controller. The result of these tests, describedin chapter 7, somehow reflects the expected results set in the beginning ofthe project.

The result shows that it is fairly easy to improve the average speed of adriving truck, and easy to improve the minimum climbing speed of trucks.However the amount of fuel used to achieve this result is fluctuating fromhigher fuel consumption than normal to lower fuel consumption than normal.It indicates that if you instead of using the system for getting the maximumpossible speed increase, tune the system for a smaller speed increase it isactually also possible to save fuel. For a 40 ton vehicle traveling at 85 km/hit is possible to decrease the fuel consumption with more than 1 %, decreasethe gearshifts with 25% and still maintain an average speed 0.5% higherthan normal. The minimum climbing speed on the steepest gradient is 8%higher than normal.

If this holds for a real truck the system should be very advantageousto install. The system will improve the constant speed of the truck, lowerthe driving time, lower the fuel consumption and improve safety on steepgradients by letting the truck move faster.

The forte of the implemented controllers is the question about safety.Often automatic systems reveals a safety issue if the system do not respondas intended, if the system is fed with wrong data or disturbances drowns thereal signals.

In this case the only problem that could arise, is an unintended gearshiftwhich can not harm anything. The controller is implemented in such a waythat it can only adjust some limits for shifting and not the shifting itself.Thus gearshifts will only be performed if the truck is actually responding as

94

8. Discussion 8.2. Model

the controller expects. If the controller decides that a gradient in the frontis too steep it will change the limits for shifting, but if there are no gradient,and the engine load and RPM are not showing any signs of a gradient, thegearshift will not be carried out. Similar if there is a gradient, and thesystem has not noticed it, the gearbox can always rely on its basic shiftingstrategy.

In regards to the cost of implementing this system, it should be comparedto the saved fuel and time using this system. If the system is capable ofsaving 1% fuel in average, which means more than 500 liters a year on astandard truck. With a cost of more than 1 e/liter, it means more than e500 saved a year.

The increased speed /decreased time is difficult to measure in money,since most of it probably would be to the benefit of the driver, but principally0.5% time is saved, and 0.5% saved salary of a truck driver a year could bemore than 20 hours, equals approximately 300 e.

The decreased number of gearshifts could save a visit on the workshop.Overall there should be enough gained savings to compensate the extraprice of the system. And finally the environment would be exposed to lesspollution.

The positive results of the project makes a strong case for proceedingwith an implementation of the system in a real truck. Implementation,would in the case of using the Volvo system, require an extension of theDynafleet system to include 3D maps, instead of the 2D maps used today.An amount of software including the rules developed in the controller partof this project should also be implemented in the onboard computer of thetruck.

95

Chapter 9

Conclusion

The objective of the project was to develop a system for automatic gearboxesto mimic the behavior of an experienced driver. This objective was intendedto be achieved using road information to improve the control of the gearbox.

The project has focused on two main areas, road information and asimulation model.

The road information part includes a feasibility study of controlling thegearbox, using an improved GIS/GPS system, extended with a 3D digitalmap as a reference to the road profile ahead of the truck.

The result of this work shows that it is possible to influence the be-havior of an automatic gearbox with the GIS/GPS system. However thelargest task lies in procuring a sufficient 3D map. A number of differentmap solutions has been investigated, from simple available maps to GPSmeasurement based maps.

This part of the system consists of the parts that should be installedin a real vehicle, to make it possible to use the system for reading theroad ahead of the vehicle, to decide what action to take to use the optimalsequence of gearshifts for climbing a certain gradient.

The other part of the project, the development of a simulation model,includes a number of controllers and a highly detailed simulation model ofa truck.

The model includes a sophisticated engine model based on the MVEM,an automatic gearbox, including shifting sequences and synchronization, adynamic vehicle model and a number of different controllers.

The result of the work concludes that it is possible to increase theaverage cruising speed of a truck with more than 1%, dependent of the roadprofile. As expected the system shows a tradeoff between increased speed

97

9. Conclusion

and fuel economy. However, it has proven to be possible to achieve both, ifthe speed is only increased with 0.5%, it is possible to save more than 1%fuel, decrease gearshifts by 25% and increase the minimum climbing speedon gradients with more than 8%, dependent of the road profile.

98

Chapter 10

Future Work

A number of ideas for the further work with this project which has not beenimplemented during the thesis work.

GIS Procuring a 3D map has proven to be a large task, future work couldinclude development of 3D maps by means of data or by means of anonline updating system, based on GPS measurements, as described insection 4.2.3

Controller A number of different controllers has already been imple-mented, however more rules or other types of controller are likely to beinvestigated. Tests has indicated that it is hard to find an optimum fora controller, the result is dependent of a lot of factors. The future workcould include the implementation of a MPC controller which is capa-ble of finding the optimal solution in regards to a number of weightparameters. A lot of the results from the advanced controller tests canbe used as background to determine these weight parameters.

Truck Implementing this system on a real truck will be the ultimate testand validation of the system.

Driving downhill The system could easily be adapted to calculate down-hill gradients too, to determine if the truck is capable of keeping thespeed down with the engine brake. If it is not possible it could forcea shift down to increase the performance of the engine brake, andthereby decrease the wear of the ordinary disc brakes.

99

Nomenclature

Abbreviations

ACC Adaptive Cruise Control

DEM Digital Elevation Model

DGPS Differential-GPS

EGR Exhaust Gas Recirculation

GCM Gross Combination Mass

GIS Geographical Information System

GPS Global Positioning System

IVSS Intelligent Vehicle Safety Systems

KMS Kort & Matrikelstyrelsen

MPC Model Predictive Control

MVEM Mean Value Engine Model

NAVSTAR-GPS NAVigation System with Timing And Ranging Global Po-sitioning System

PID Proportional-Integral-Derivative controller

RPM Revolutions Per Minute

SCR Selective Catalytic Reduction

TIS Transport Information System

UTM Universal Transverse Mercator Coordinate

VCADS Vehicle Computer Aided Diagnostic System

VEB Volvo Engine Brake

101

Nomenclature

Constants

αbr Cruise control parameter 0.01

αcc Cruise control parameter 0.01

ηr Rearaxle efficiency 0.97

ηc Turbo efficiency 0.73

κ Adiabatic constant, cp/cv 1.4

µd Dynamic friction coefficient 0.4

σ Air density 1.19kg/m3

τdbrCruise control - differentiation time constant 3s

τdcc Cruise control - differentiation time constant 3s

τengine Engine time constant 0.5s

τibrCruise control - integration time constant 10s

τicc Cruise control - integration time constant 10s

τturbo Turbo time constant 1s

τV EB Engine brake time constant 0.5s

A Vehicle front area 9.75m2

ad Drag constant −8.80 · 10−2 NmRPM

bd Drag constant −51.51Nm

cw Vehicle drag coefficient 0.6

f Rolling resistance coefficient 0.007

g Gravity 9.82m/s2

Hu Heating value of fuel 43kJ/kg

ir Rearaxle ratio 1 : 3.10

Jw Wheel inertia 32.9kgm2

kb Brake constant 20 · 103Nm

KpbrCruise control - proportional gain 0.2

Kpcc Cruise control - proportional gain 10

102

Nomenclature

Lth Stoichiometric air/fuel ratio 14.7

nr Number of crankshaft revolutions per stroke 2

ncyl Number of cylinders 6

nmax Engine maximum speed 2500RPM

pa Ambient pressure 1.013bar

R Gas constant 287 · 10−5

rw Wheel radius 0.52m

Rcl Clutch disk radius 0.3m

si Air charge per stroke constant 1.05

Ta Ambient temperature 293K

TV EBmax Maximal brake torque at maximum RPM 1360Nm

Vd Engine displacement 9.4L

Vref Reference engine displacement 1.275L

yi Air charge per stroke constant −0.13

Variables

α Longitudinal road gradient rad

ω Angular acceleration rad/s2

ηg Gearbox efficiency [0.99− 0.88]

ηi Indicated efficiency −ωw Wheel speed s−1

Φ Fuel/Air equivalence ratio −τc Turbo time constant s

τd Time delay for fuel injection s

a Total acceleration of vehicle m/s2

B Brake control signal [0; 1]

Cl Clutch factor [0, 1]

ev Volumetric efficiency −

103

Nomenclature

F Total force acting on vehicle N

Fn Force on clutch N

Fw Total force acting on wheels Nm

Fae Total Aerodynamic resistance N

Fcl Total climbing resistance N

Fdl Total force generated by the driveline N

Fro Total rolling resistance N

Frr Total opposing force (rolling, air and climbing resistance) N

fc Fuel consumption liter/s

gend End of gradient m

gstart Beginning of gradient m

ig Gearbox ratio [1 : 1− 14.94]

J Moment of inertia kgm2

Kengine Engine load [0; 1]

kstep Engine brake step [0; 3]

Kthrottle Position of throttle [0; 1]

m Total mass of vehicle kg

mf Fuel mass flow kg/s

map Port air mass flow kg/s

n Engine speed rpm

ng Gearbox rotational speed rpm

p Truck momentum kg ·m/s

Pb(n) Power supplied to load kW

pc Compressor outlet air pressure bar

Pf (n) Loss of friction kW

pi Intake manifold air pressure bar

Pexhx Power to drive turbo kW

104

Nomenclature

prc pc/pa −s Distance m

T Torque Nm

t Time s

Tc Compressor outlet air temperature K

Te Total engine torque Nm

Tg Torque delivered from gearbox Nm

Ti Intake air temperature K

Tcl Torque transmitted by clutch Nm

Tdrag Engine drag torque Nm

Tnormmax Maximal normal engine torque at certain RPM Nm

Tnorm Normal engine torque Nm

Tturbomax Maximal turbo torque at certain RPM Nm

Tturbo Extra turbo torque Nm

TV EB Engine brake torque Nm

v Vehicle speed m/s

105

Bibliography

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[Zogg, 2002] Zogg, J.-M. (2002). GPS Basics, Introduction to the system,Application overview. u-blox.

109

List of Figures

2.1 I-shift gear lever . . . . . . . . . . . . . . . . . . . . . . . . . 102.2 Flowchart of system implementation intended here including

Road Information, Truck Model and, Controller. . . . . . . . 12

3.1 Predictive Cruise Control . . . . . . . . . . . . . . . . . . . . 153.2 Application for GPS/GIS aids in vehicles, according to the

amount of detail available in digital maps. . . . . . . . . . . . 19

4.1 Road Information part of the project. . . . . . . . . . . . . . 214.2 Holux GM-210 GPS receiver . . . . . . . . . . . . . . . . . . . 224.3 Program for testing GPS . . . . . . . . . . . . . . . . . . . . . 234.4 Program for testing GPS and GIS . . . . . . . . . . . . . . . 244.5 TOP10DK 2D Highway theme of Søllerød municipality . . . . 254.6 Part of TOP10DK DEM theme, of Søllerød municipality . . . 254.7 GIS 3D Highway of Søllerød municipality . . . . . . . . . . . 264.8 GIS 2D Data of Sealand . . . . . . . . . . . . . . . . . . . . . 274.9 GIS 3D Data of Sealand . . . . . . . . . . . . . . . . . . . . . 284.10 2D GIS and GPS from E47/E55 test . . . . . . . . . . . . . . 284.11 2D Profile GIS and GPS from E47/E55 test . . . . . . . . . . 294.12 2D Profile of map created from GPS measurements at E47/E55 304.13 E4, Linkoping - Jonkoping, road profile. . . . . . . . . . . . . 314.14 Map matching algorithm. Raw GPS data . . . . . . . . . . . 324.15 Map matching algorithm. Matched data . . . . . . . . . . . . 324.16 Map matching algorithm . . . . . . . . . . . . . . . . . . . . . 324.17 Test of the map matching algorithm . . . . . . . . . . . . . . 334.18 Description of the road sequence in front of the vehicle . . . . 344.19 Program calculating the road sequence ahead of the vehicle . 35

5.1 Truck part of the project. . . . . . . . . . . . . . . . . . . . . 385.2 Volvo FM9 - 380 Strawtransport . . . . . . . . . . . . . . . . 385.3 Volvo FM9 - 300 Test truck at Volvo Truck Center Denmark

A/S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395.4 Volvo FM9 - 300 Turbo pressure. Dynamic response. . . . . . 40

111

LIST OF FIGURES LIST OF FIGURES

5.5 Speed and fuel tests at Varby - E20. Automatic - Solid,Manual - Dashed . . . . . . . . . . . . . . . . . . . . . . . . . 41

5.6 The effect of throttle and load on the gearbox strategy forshifting up. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

5.7 1st Model main parts. . . . . . . . . . . . . . . . . . . . . . . 445.8 Engine torque of a Volvo FM9, 380HP . . . . . . . . . . . . . 465.9 Engine brake torque of a Volvo FM9, 380HP . . . . . . . . . 475.10 Gear ratios of an I-shift VT2412B . . . . . . . . . . . . . . . 485.11 Gauges from the simulation model, similar to the gauges in a

Volvo Truck. . . . . . . . . . . . . . . . . . . . . . . . . . . . 515.12 Primary parts of the engine . . . . . . . . . . . . . . . . . . . 545.13 Fuel Function . . . . . . . . . . . . . . . . . . . . . . . . . . . 595.14 Maximum turbo pressure . . . . . . . . . . . . . . . . . . . . 605.15 Engine power . . . . . . . . . . . . . . . . . . . . . . . . . . . 605.16 Engine torque . . . . . . . . . . . . . . . . . . . . . . . . . . . 605.17 Engine efficiency ηi . . . . . . . . . . . . . . . . . . . . . . . . 615.18 Equivalence ratio θ . . . . . . . . . . . . . . . . . . . . . . . . 615.19 Engine dynamic response - Torque. It is seen that the re-

sponse with the fuel time delay is not remarkable slower thanthe response without the time delay. . . . . . . . . . . . . . . 62

5.20 Engine dynamic response - Efficiency. The efficiency is kepthigh by using a time delay in the fuel injection. . . . . . . . . 62

5.21 Gearbox shifting sequence . . . . . . . . . . . . . . . . . . . . 655.22 Gear shift sequence - shift down . . . . . . . . . . . . . . . . . 665.23 Gear shift sequence - shift up . . . . . . . . . . . . . . . . . . 66

6.1 Controller part of the project. . . . . . . . . . . . . . . . . . . 696.2 E20, Varby, gradient and gearshift strategy . . . . . . . . . . 736.3 Torque output in 12th and 11th gear . . . . . . . . . . . . . . 746.4 Economy in 12th and 11th gear . . . . . . . . . . . . . . . . . 756.5 [Top] Gradient of the road between Linkoping to Jonkoping.

[Bottom] Gradients that exceeds the maximum climbable gra-dients of the truck in 12th gear. FM9-380HP, 40 tons. . . . . 77

6.6 Estimated decrease in speed on steepest gradients betweenLinkoping and Jonkoping, using 12th or 11th gear. FM9-380HP, 40 tons. . . . . . . . . . . . . . . . . . . . . . . . . . . 78

7.1 Program calculating the road sequence ahead of the vehicle . 807.2 E20 - 1st Model, 85 km/t, 40 tons . . . . . . . . . . . . . . . 827.3 E20 - 2nd Model, 85 km/t, 40 tons . . . . . . . . . . . . . . . 827.4 Route 21 - 1st Model, 85 km/t, 40 tons . . . . . . . . . . . . 837.5 Route 21 - 2nd Model, 85 km/t, 40 tons . . . . . . . . . . . . 837.6 E47/E55 - 1st Model, 85 km/t, 40 tons . . . . . . . . . . . . . 847.7 E47/E55 - 2nd Model, 85 km/t, 40 tons . . . . . . . . . . . . 84

112

LIST OF FIGURES LIST OF FIGURES

7.8 E4 Linkoping - Jonkoping - 1st Model, 85 km/t, 40 tons . . . 857.9 E4 Linkoping - Jonkoping - 2nd Model, 85 km/t, 40 tons . . 857.10 E4 Jonkoping - Linkoping - 1st Model, 85 km/t, 40 tons . . . 867.11 E4 Jonkoping - Linkoping - 2nd Model, 85 km/t, 40 tons . . 867.12 Variation in vehicle cruising speed from 80 km/h - 90 km/h.

Driving Jonkoping to Linkoping, 40 tons, allowed speed drop5 km/h. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

7.13 Variation in vehicle weight from 16 tons - 48 tons. DrivingJonkoping to Linkoping at 85 km/h, allowed speed drop 5km/h. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

7.14 Variation in allowed speed drop from 1 km/h - 20 km/h.Driving Jonkoping to Linkoping at 85 km/h, 40 tons. . . . . . 90

113

List of Tables

5.1 Estimated maximum turbo pressure of FM9 . . . . . . . . . . 405.2 Speed and fuel tests at Varby E20. . . . . . . . . . . . . . . . 425.3 Test of acceleration 0 - 80 km/h. . . . . . . . . . . . . . . . . 435.4 Average fuel tests, Route 21. 24.7 tons, 85 km/h . . . . . . . 675.5 Minimum speed test, E20. 24.7 tons, 85 km/h . . . . . . . . . 675.6 Acceleration test, 0 km/h - 80 km/h . . . . . . . . . . . . . . 68

6.1 Power and Economy engine speed for the drive modes. Opti-mal shift up and down. . . . . . . . . . . . . . . . . . . . . . . 75

7.1 Combined results of tests, FM9-380, 40 tons. . . . . . . . . . 87

115

Appendix A

Models

SIMULINK diagrams of Models.

Appendix A.1 1st ModelAppendix A.2 2nd Model

117

A. Models A.1. 1st Model

A.1 1st Model

SIMULINK diagrams of 1st Model.

• Blue blocks includes Acceleration, Speed, RPM.

• Red blocks includes Torque.

• Green blocks includes Moment of inertia.

Appendix A.1.1 1st Model - MainAppendix A.1.2 1st Model - EngineAppendix A.1.3 1st Model - GearboxAppendix A.1.4 1st Model - Differential, brakes and wheels

118


A.1.1 1st Model - Main

119


A.1.2 1st Model - Engine

120


A.1.3 1st Model - Gearbox

121


A.1.4 1st Model - Differential, Brakes and Wheels

122

A. Models A.2. 2nd Model

A.2 2nd Model

SIMULINK diagrams of 2nd Model.

• Blue blocks includes Acceleration, Speed, RPM.

• Red blocks includes Torque.

• Green blocks includes Moment of inertia.

Appendix A.2.1 2nd Model - MainAppendix A.2.2 2nd Model - Engine - MainAppendix A.2.3 2nd Model - Engine - FuelAppendix A.2.4 2nd Model - Engine - TurboAppendix A.2.5 2nd Model - Engine - CrankshaftAppendix A.2.6 2nd Model - ClutchAppendix A.2.7 2nd Model - GearboxAppendix A.2.8 2nd Model - Differential, brakes and wheels

123


A.2.1 2nd Model - Main

124


A.2.2 2nd Model - Engine - Main

125


A.2.3 2nd Model - Engine - Fuel

126


A.2.4 2nd Model - Engine - Turbo

127


A.2.5 2nd Model - Engine - Crankshaft

128


A.2.6 2nd Model - Clutch

129


A.2.7 2nd Model - Gearbox

130


A.2.8 2nd Model - Differential, Brakes and Wheels

131

Appendix B

CD

The attached CD, includes the report, program code, SIMULINK models,and other relevant data.

B.1 Contents

Appendix B.1.1 Files for the report.Appendix B.1.2 Includes all files for the road information part.Appendix B.1.3 Includes all files for the two developed models.

B.1.1 Report

File Name Descriptionreport.pdf This report in PDF version

133

B. CD B.1. Contents

B.1.2 Road Information

GIS

Important files for the GIS part:

File Name Descriptione20.mat Road data, E20 Great Belt Bridge - Slagelse Easte47 e55.mat Road data, E47/E55 Lyngby - HelsingørJon Lin.mat Road data, E4 Jonkoping - LinkopingLin Jon.mat Road data, E4 Linkoping - Jonkopingrute21.mat Road data, Route 21 Holbæk - Folehaven

GPS

Important files for the GPS part:

File Name DescriptionOpenGPS.m Set up connection to USB portCloseGPS.m Close connection to USB portread gpsstring.m Read one GPS message from the receiverparse gpsstring.m Parse GPS message into usable datall2utm.m Convert Latitude/Longitude coordinates to UTM coordinatesmatch map.m Match found position to GIS mapsort map.m Sort GIS maps (used for GPS created maps)program 6.fig GIS/GPS program to be started from MATLAB GUIDEprogram 6.m Program code for program 6.fig

134

B. CD B.1. Contents

B.1.3 Truck Model

1st Model

Important files for the 1st model:

File Name Descriptionfirst model.mdl SIMULINK modelinit e20.m Run model on Highway E20 - Great Belt Bridge to Slagelse Eastinit e47 e55.m Run model on Highway E47/E55 - Lyngby to Helsingørinit rute21.m Run model on Highway Route 21 - Holbæk to Folehaveninit lin jon.m Run model on Highway E4 Linkoping to Jonkopinginit jon lin.m Run model on Highway E4 Jonkoping to Linkopingtruck data.m Data file, including all parameters for the truck model

2nd Model

Important files for the 2nd model:

File Name Descriptionsecond model.mdl SIMULINK modelsecond model report.mdl SIMULINK model without scopes, etc.init e20 new.m Run model on Highway E20 - Great Belt Bridge to Slagelse Eastinit e47 e55 new.m Run model on Highway E47/E55 - Lyngby to Helsingørinit rute21 new.m Run model on Highway Route 21 - Holbæk to Folehaveninit lin jon new.m Run model on Highway E4 Linkoping to Jonkopinginit jon lin new.m Run model on Highway E4 Jonkoping to Linkopingtruck data new.m Data file, including all parameters for the truck modelgear shift function.m Gear shifting sequenceroad sequence calc.m Advanced controller

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B. CD B.2. CD

B.2 CD

137

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