THE IMPACT OF ECOROLL ON FUEL CONSUMPTION - … · APS airprocessingsystem CC cruisecontrol CVT...

THE IMPACT OF ECOROLL ON FUELCONSUMPTION - USING LOOK AHEAD

MUSTAFA ABDUL-RASOOL

Master’s Degree ProjectStockholm, Sweden June 2011

XR-EE-RT 2011:016

THE IMPACT OF ECOROLL ON FUELCONSUMPTION - USING LOOK AHEAD

MUSTAFA ABDUL-RASOOL

Master’s Thesis at Automatic ControlSupervisor: Oskar Johansson

Examiner: Ather Gattami

XR-EE-RT 2011:016

AbstractEcoRoll reduces fuel consumption with small developmentcosts, since no additional hardware is required. It is a func-tion that enables a more efficient conversion of potential tokinetic energy, when travelling downhill. This is achievedby opening the powertrain, and let the engine run on idleto reduce engine losses. In this Master’s thesis, two controlstrategies were developed, where one is based on prevailingconditions and one utilizes Look-Ahead data. Compared toa vehicle with a conventional cruise control, the first strat-egy gave a fuel reduction of approximately 3.4% and theother 3.7%. This was simulated on the highway betweenSödertälje and Norrköping in Sweden.

Referat

EcoRoll är en funktion, med låga utvecklingskostnader, somreducerar bränsleförbrukning. Detta då den tillåter en effek-tivare konvertering av lagrad potentiell energi till kinetiskenergi under en nedförsbacke. Funktionen öppnar drivlinani nedförsbackar och låter därmed motorn gå på tomgång,vilket minskar motorförlusterna. I detta arbete har två oli-ka reglerstrategier utvecklats, där den ena är baserad pånuvarande tillstånd, medan den andra använder sig av in-formation om vägen framför fordonet, dvs. Look-Ahead. Si-mulering på vägen från Södertälje till Norrköping ger enbränslereducering på ungefär 3,4% för den första strateginoch 3,7% för den andra, vid jämförelse med ett likadantfordon med en traditionell farthållare.

Acknowledgements

The research presented in this Master’s thesis is the final project in achieving myM.Sc. Degree in Electrical Engineering at the Automatic Control department atthe Royal Institute of Technology, kth, in Stockholm, Sweden. The work has beencarried out at the Driving Assistance Software unit, neca, at Scania cv ab inSödertälje, Sweden.

I would like to start expressing my gratitude to the senior manager of ControlStrategy section, nec, at Scania, Magnus Staaf, who gave me the opportunity to dothis thesis and believed in my idea. Also, I would like to thank Andreas Renberg,the head of neca, for his review and feedback.

I owe my deepest gratitude to my supervisor at Scania, Oskar Johansson, for hisgreat inputs, patience, and guidance through this project. He made an effort evenduring his vacations. Many thanks to Maria Södergren who was my second supervi-sor. She followed the project continuously, giving tips and wise inputs. Thank youOskar and Maria! Furthermore, it is a pleasure to thank my examiner Dr. AtherGattami at kth, for his positive support and advice.

I am also indebted to all my colleagues from different departments at Scania,among them; Mikael Ögren, Anders Kjell, Peter Asplund, Magnus Svensson, NiklasLerede, Niklas Pettersson, and Olof Lundström, to mention some of them. They allhave contributed to this project by sharing invaluable knowledge or giving feedbackon the report. I would also like to express my gratitude to my colleague and friend,Kuo-Yun Liang, for the valuable and interesting discussions we have had together.

Most of all I would like to thank my parents for supporting and advising me. Iowe them my life for achieving this stage of life and study. Last but absolutely notleast, many thanks to my wonderful wife who encouraged me, reviewed the reportand made the time during the project great.

Mustafa Abdul-RasoolStockholm 2011

Contents

1 Introduction 7

2 Background 92.1 EcoRoll . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92.2 Look-Ahead . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92.3 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.3.1 Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112.3.2 Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112.3.3 Delimitations . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

2.4 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

3 Vehicle Model 133.1 Basic Model of Powertrain . . . . . . . . . . . . . . . . . . . . . . . . 13

3.1.1 Driving Resistances . . . . . . . . . . . . . . . . . . . . . . . 143.1.2 Traction Force . . . . . . . . . . . . . . . . . . . . . . . . . . 15

3.2 Important Parts of the Powertrain . . . . . . . . . . . . . . . . . . . 163.2.1 Engine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163.2.2 Gear Shifting . . . . . . . . . . . . . . . . . . . . . . . . . . . 183.2.3 Cruise Control and Downhill Speed Control . . . . . . . . . . 18

3.3 Modeling Software . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

4 Pre-study of EcoRoll 214.1 Possibility of Implementation . . . . . . . . . . . . . . . . . . . . . . 214.2 Safety Aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224.3 Road Topography and Strategies . . . . . . . . . . . . . . . . . . . . 22

4.3.1 The Studied Hills . . . . . . . . . . . . . . . . . . . . . . . . . 234.3.2 Activation Time of EcoRoll . . . . . . . . . . . . . . . . . . . 254.3.3 Constructed Simplified Hills . . . . . . . . . . . . . . . . . . . 25

4.4 Quadratic Cost Function . . . . . . . . . . . . . . . . . . . . . . . . . 264.5 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274.6 Discussions on the Feasibility Study . . . . . . . . . . . . . . . . . . 28

5 Conventional EcoRoll 315.1 Control Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

5.1.1 Input Signals to the Controller . . . . . . . . . . . . . . . . . 315.1.2 Accelerating Hill . . . . . . . . . . . . . . . . . . . . . . . . . 335.1.3 Decelerating Hill . . . . . . . . . . . . . . . . . . . . . . . . . 345.1.4 After Hill . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 345.1.5 A Low-Pass Filter . . . . . . . . . . . . . . . . . . . . . . . . 355.1.6 The Transitions between the States . . . . . . . . . . . . . . . 35

5.2 Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

6 EcoRoll utilizing Look-Ahead 396.1 Control Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

6.1.1 Speed Prediction . . . . . . . . . . . . . . . . . . . . . . . . . 396.1.2 Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

6.2 Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

7 The Sources of Saving Potential 477.1 Road Topography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 477.2 The Impact of the Nonlinear Fuel Map . . . . . . . . . . . . . . . . . 49

8 Sensitivity Analyses 518.1 Sensitivity Analyses of the Conventional EcoRoll . . . . . . . . . . . 51

8.1.1 Different Piston Displacements . . . . . . . . . . . . . . . . . 518.1.2 Rolling Resistance . . . . . . . . . . . . . . . . . . . . . . . . 528.1.3 Air Resistance . . . . . . . . . . . . . . . . . . . . . . . . . . 538.1.4 Mass Estimation . . . . . . . . . . . . . . . . . . . . . . . . . 538.1.5 CC and DHSC Set Speeds . . . . . . . . . . . . . . . . . . . 548.1.6 Best Case vs. Worst Case . . . . . . . . . . . . . . . . . . . . 55

8.2 Sensitivity Analyses of Look-Ahead EcoRoll . . . . . . . . . . . . . . 558.2.1 Different Piston Displacements . . . . . . . . . . . . . . . . . 568.2.2 Rolling Resistance . . . . . . . . . . . . . . . . . . . . . . . . 568.2.3 Air Resistance . . . . . . . . . . . . . . . . . . . . . . . . . . 568.2.4 Mass Estimation . . . . . . . . . . . . . . . . . . . . . . . . . 578.2.5 CC and DHSC Set Speeds . . . . . . . . . . . . . . . . . . . 588.2.6 Best Case vs. Worst Case . . . . . . . . . . . . . . . . . . . . 59

8.3 Validation in a HDV . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

9 Discussion 639.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 649.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

Bibliography 65

Appendix 65

A Parameter Values 67

List of Abbreviations

AMT automated manual transmission

APS air processing system

CC cruise control

CVT continuously variable transmission

DHSC downhill speed control

DP dynamic programming

ECU electronic control unit

GPS global positioning system

HDV heavy-duty vehicle

ICE internal combustion engine

PI proportional-integral

R&D research and development

1

List of Symbols

aER The estimated acceleration for an open powertrain.

Av Front area of the vehicle.

CaF A coefficient used in Michelin model for rolling resistance.

Cb A coefficient used in Michelin model for rolling resistance.

Cd Air resistance coefficient.

Cr Rolling resistance coefficient.

CrrisoF A coefficient used in Michelin model for rolling resistance.

decmax Maximum accepted deceleration.

Fair The force caused by air resistance.

Fbrake The braking force acting on wheels.

fcost The cost function.

Fdrive The driving force generated by the engine.

Fgrav The longitudinal gravitational force.

FICElossesThe total engine losses expressed as force losses.

Froll The force caused by rolling resistance.

Ftot The total forces acting on a HDV.

Ftrac The traction force on the wheels.

g The gravitational constant.

gnr Gear number.

if The gear ratio of the final drive.

it Transmission’s gear ratio.

3

CONTENTS

Mv The mass of the vehicle.

Mε The mass estimation error.

n An integer when multiplied with ∆p gives the distance from p to thepredicted position.

ncyl The number of cylinders in the engine.

nr Number of revolutions per cycle.

p Current position of the HDV.

∆p The distance between two positions.

qf The fuel consumption in [g/sec].

qfacc The accumulated fuel consumption in [liter].

qfaccCCThe accumulated fuel consumed by the reference HDV, during a simu-lation cycle.

qfaccERThe accumulated fuel consumed by a heavy-duty vehicle (HDV) equippedwith EcoRoll, during a simulation cycle.

qfaccsaveThe fuel saving of EcoRoll compared to the reference HDV.

qfinstThe instantaneous fuel consumption per revolution, [g/cycle].

rw Wheel radius.

Tc The output torque of the clutch to the gearbox.

tCC The time it takes for the reference HDV, to travel through the roadthat is used in simulation.

tchangeminThe lower time limit for remaining within a main state; opened orclosed powertrain.

Tdrag The drag torque, caused by engine’s internal friction.

tER The time it takes for a HDV equipped with EcoRoll, to travel throughthe road that is used in simulation.

Tf The output torque from the final drive.

TICE The torque out from the ICE.

T ∗ICE The demanded ICE torque.

TICElossesThe torque losses in the engine.

4

CONTENTS

tnewpredThe time period for a new start of prediction.

Tpump The coolant pump losses expressed in torque loss.

tsample The sampling time for speed prediction.

tsave The travel time savings of EcoRoll compared to the reference HDV.

v The current vehicle speed.

v0 Initial vehicle speed when entering the state Active.

v The time derivative of the vehicle speed.

v Prediction of speed.

vair The air speed.

vCCmargin A parameter specifying how much the speed may drop below CC speedwith an open powertrain.

vCCset The CC set speed.

vDHSCmargin Margin from DHSC set speed.

vDHSCset The DHSC set speed.

vISO The nominal speed where Michelin model is linearized around.

vmax Maximum speed where the EcoRoll can be active, when positive ac-celeration is estimated.

vmin Minimum speed where the EcoRoll can be active, when positive accel-eration is estimated.

voverspeed A parameter defining a downhill when the speed increases to its value.

vpredmax The maximum predicted achievable speed.

α The prevailing road inclination.

αCP The inclination corresponding to the HDV, without any fuel injected,keeping the desired speed with closed powertrain.

αER The inclination that lets the speed of the HDV being maintained withopen powertrain.

αlesssteep Inclinations where the HDV decelerates when the powertrain is open.

αsteep Inclinations where the HDV accelerates despite no fuel is injected.

αuphill All positive inclinations.

5

CONTENTS

β A weight coefficient for the cost function.

ηf The efficiency of final drive.

ηt The efficiency of the transmission.

ωc The angular speed on the output shaft of the clutch.

ωf The output angular velocity from the final drive.

ωICE Angular velocity of the ICE.

ωidle The angular velocity of the engine running on idle.

ωw The angular speed of the wheels.

ρair The air density.

ρfuel The density of the used fuel in [g/liter].

6

Chapter 1

Introduction

The technology behind hybrid vehicles is nowadays one of the main approaches inorder to reduce fuel consumption. The hybrid system enables the feature of regen-erative braking, i.e., the battery gets charged whenever the vehicle is braking. Thistechnology enables the energy to be utilized more efficiently. However, regenerativebraking is more suitable for city driving, with frequent braking. This makes thefunction less suitable for long haulage vehicles.

What feature can then be utilized on a highway? One answer is hills. Potentialenergy is stored while driving uphill, which will be converted into kinetic energywhen travelling downhill. Thus, the idea of EcoRoll was born in me; let the vehicleconvert the potential energy as efficiently as possible.

The idea is to let the vehicle roll with disengaged gear in downhill, with theengine running only on idle to power steering-, brake servo, etc. This was presentedto the R&D department at Scania cv ab, a Swedish heavy-duty vehicle (HDV) man-ufacturer, together with the thesis application. Apparently the idea was not new.However, unlike Volvo and Mercedes trucks, Scania has chosen different solutions.One solution is to decrease the engine speed by lowering the gear ratio, when only asmall amount of torque is needed, e.g., when travelling downhill. This reduces thelosses with a closed powertrain.

A study made by Anders Jensen at Scania [8] concludes that without usingany Look-Ahead data, the EcoRoll function reduces fuel consumption. However, itcould also have a negative impact due to the risk of a hill being too long and steep,where braking is needed before the end of the hill. In this case, it is more beneficialto go into fuel-cut off mode, but it requires Look-Ahead data to identify the lengthof the hill. As known so far, no HDVs with EcoRoll utilize Look-Ahead data.

The Ph.D. thesis [5] concludes that the fuel consumption can be reduced byapproximately 3%, but only on specially constructed road topographies. Otherwise,only 0.3% can be reduced on an authentic road. The results are generated froma control strategy based on dynamic programming (DP), which gives the optimalresult for the specific vehicle on the studied road. However, a deeper study onEcoRoll is needed for Scania to identify the potential of this functionality. Also,

7

CHAPTER 1. INTRODUCTION

to compare two control strategies, where one is based on actual circumstances andthe other on Look-Ahead data. Thus, this thesis studies EcoRoll with and withoutLook-Ahead data. The strategies are compared to conventional cruise control (CC),by simulations and validation on a HDV.

8

Chapter 2

Background

This chapter presents a background describing EcoRoll, Look-Ahead, and the pur-pose of this thesis. Also, previous related studies in this area are presented.

2.1 EcoRollThe concept of EcoRoll is to disengage the gear when traveling downhill. Its aimis to increase the benefit of the potential energy stored from driving uphill. This isconverted into kinetic energy that propels the vehicle when travelling downhill. Itis well known that energy conversions usually have losses in form of heat, friction,etc. One of the losses in a vehicle is the engine itself. It has friction that needsto be overcome. Furthermore, the friction increases with higher angular velocity.Therefore, the losses are decreased when disengaging the gear in a downhill. Thespeed is also increased further, since the impact of engine losses on the motion of thevehicle is eliminated, see Figure 2.1. By that the fuel consumption can be reduced.However, the internal combustion engine (ICE) cannot be turned off since it powersthe steering- and brake servo, etc, unless these are electronically powered systems.For HDVs, this is usually not the case. Hence, the ICE should be kept running atidle.

Since this thesis focuses on HDVs, and the servo is presumed not to be electron-ically powered, the ICE will run on idle when driving in EcoRoll mode.

2.2 Look-AheadAn experienced driver plans his driving by looking at the road ahead. Doing this,the correct gear can be selected early and the speed reduced before a downhill,providing fuel efficiency and better driving performance. However, this ability ismissing in the automated functionalities in vehicles such as the automatic gearboxand the CC. The solution is to use Look-Ahead data.

The idea of Look-Ahead is to use a global positioning system (GPS) for posi-tioning the vehicle and utilize stored data of the road ahead. The sky is the limit

9

CHAPTER 2. BACKGROUND

Figure 2.1: The graphs shows the behavior of two HDVs traveling down a hill.The darker graphs shows the speed and fuel consumption for a HDV equipped withEcoRoll, and the other two graphs corresponds to a conventional HDV.

for the possibilities of this technology. It creates great opportunities for improvingmost of the systems in a vehicle, regarding performance and fuel efficiency.

2.3 Problem Statement

The idea of EcoRoll is to reduce the fuel consumption by automatically disengagingthe gear in a downhill to let the vehicle roll freely, and let the engine run on idle.This raises some questions:

• How much fuel can be reduced by EcoRoll?

• Can the results be improved by taking advantage of Look-Ahead data?

• Are the results sensitive to different disturbances or configurations?

The aim of this thesis is to answer these questions. This section introduces thegoals of the study, the approach to reach them and the delimitations of this work.

10

2.3. PROBLEM STATEMENT

2.3.1 Goals

The main goal is to develop two control strategies for EcoRoll and study their fuelsaving potential. The first strategy is based on prevailing conditions, while thesecond uses Look-Ahead data.

It is of course important to analyze the sensitivity of the results for robustness.Sensitivity analysis is done to the following areas:

• Rolling and air resistance models and their parameters.

• Differences in vehicle mass estimation.

• Different road topographies.

• Engines with different characteristics and piston displacements.

Another goal is to validate the results by driving a HDV, manually requestingdisengaged gear when it seems beneficial. A computer is connected to log data, suchas fuel consumption. Therefore, to get a reasonable comparison, the vehicle param-eters are chosen according to an available truck that will be driven. Furthermore,the same road topography that is simulated will be driven, in order to be able tocompare the results.

2.3.2 Approach

The study is divided into four phases; pre-study of EcoRoll, conventional EcoRoll,EcoRoll utilizing Look-Ahead data and result analysis. Each phase complementseach other.

Pre-study: A feasibility study is done in order to understand when it is beneficialto activate EcoRoll. In order to develop a reasonable control strategy, differentsimplified downhill slopes are studied where EcoRoll is activated in different partsof the hill.

Conventional EcoRoll: The aim of studying the conventional EcoRoll is to iden-tify its potential to reduce fuel consumption and its limitations.

Look-Ahead EcoRoll: The identified limitations of the conventional EcoRoll areused to create a control strategy that overcomes these limitations by using Look-Ahead data.

Analyses: The results are analyzed to study the sensitivity for different distur-bances and parameters, e.g., wind or different road topographies. Also, in order tovalidate that the results are reasonable, a HDV is driven and data is logged. Thelogged data is then compared to the simulation results.

11

CHAPTER 2. BACKGROUND

2.3.3 DelimitationsSeveral functions could require a closed powertrain to ensure the most efficientoperating points with respect to fuel consumption. An example of this is the airprocessing system (APS). The impact of these systems will not be considered in thebasic Simulink model. Instead, these factors will be taken into account when theresults are validated in the truck.

The position of the HDV received from the GPS is assumed to be accurate andcorrect in all conditions. However, other modeling assumptions will be presentedclearly in their respective section.

2.4 Related WorkThere are already patents in this area by different manufactures, among them isVolvo which has had several since 2001. Some of these patents treat EcoRoll both foruse with CC and with gas pedal, while others treat improvements of said strategies.Anders Fröberg [5] has done a study in cooperation with Scania. Here, two controlstrategies were compared. One was based on current slope where EcoRoll wereactivated between two predefined angles. The second utilizes DP with Look-Aheaddata. DP with an infinite horizon gives the optimal result regarding fuel efficiency,but is a processor intensive strategy. Another study, made at Scania by AndersJensen [8], compares EcoRoll with Scania’s LowRev. The concept of LowRev is todesign the HDVs such that the engine runs at maximum of 1000 rpm when drivingat 80 km/h and when the driving resistance is small [3]. The conclusion was thatthe best option is to combine EcoRoll and LowRev by using Look-Ahead data, sincethe functionalities have advantages in different hills.

EcoRoll has also been studied for other circumstances. A Master’s Thesis byArvid Rudberg [2] studied a fuel efficient deceleration to reach a speed limit decrease.EcoRoll was the most fuel efficient way to decelerate, but caused an increased traveltime. Since this deceleration is slower than braking, it needs to start earlier whichcan affect the vehicles behind. Therefore EcoRoll, engine braking and brakes arecombined to find an optimum regarding both fuel efficiency and driving time.

12

Chapter 3

Vehicle Model

The powertrain of a HDV consists of an engine, clutch, transmission, propeller shaft,final drive, drive shafts, and wheels, depicted in Figure 3.1. It is important thateach part is modeled such that it is able to show reasonable results for the specificsubject that is studied but at the same time not being too complex. A basic modelof the longitudinal propulsion of the vehicle is well described in Vehicular Systems[10, ch. 8]. This will serve as premise for the Matlab Simulink model used in thisstudy.

Figure 3.1: An overview of the main components a powertrain consists of.

3.1 Basic Model of PowertrainAs a start, an overview of the vehicle model will be presented followed by a deeperdescription of the important parts for this study. All parameter values for thevehicle model, that are used for this study, are given in Table A.1 in Appendix A.

The longitudinal motion of the vehicle is described by Newton’s second law,

Mvv = Ftrac − Fair − Froll − Fgrav, (3.1)

13

CHAPTER 3. VEHICLE MODEL

where Mv is the HDV mass, v its acceleration, and Ftrac, Fair, Froll and Fgrav theforces acting on the vehicle. The forces are visualized in Figure 3.2 and discussedin following subsections.

Figure 3.2: The longitudinal forces acting on a HDV.

3.1.1 Driving ResistancesThe gravitational force is given by

Fgrav = Mvg sin (α) , (3.2)

where g is the acceleration caused by the gravity and α the current inclination,defined positive for an uphill, see Figure 3.2.

The air resistance increases quadratically to the difference between vehicle speedand air speed,

Fair = 12CdAvρair (v − vair)2 , (3.3)

where Cd is the air force coefficient, Av denotes the front area of the vehicle, ρairthe air density, v the vehicle speed and vair the air speed. However, the rolling re-sistance is more difficult to model. Scania has previously noticed problems with themodels used today; calculations and simulations do not match the measurements.Therefore, a Master’s Thesis [6] studied this issue and developed a new model. Themodel is however too complex for this work, therefore Michelin’s rolling resistancemodel is used,

Froll = Mvg√1 + rw

2.7

(CrrisoF + Cb (|v| − vISO) + CaF

(v2 − v2

ISO

)), (3.4)

where rw is the wheel radius, vISO the nominal speed and CrrisoF , Cb and CaF arecoefficients.

14

3.1. BASIC MODEL OF POWERTRAIN

Since Michelin is a company that develops and manufactures tires, their model isassumed to be sufficient for the purpose of this study. However, in order to considerthe deviation of the model from real measurements, a sensitivity analysis is donein Chapter 8. This is achieved by comparing the results from Michelin’s model toanother model. The chosen model is:

Froll = MvCrg cos (α) , (3.5)

where Cr is a coefficient and α the current road inclination.

3.1.2 Traction ForceThe traction force Ftrac is the force acting on the wheels generated by the engine,Fdrive, and brakes, Fbrake:

Ftrac = Fdrive − Fbrake. (3.6)

The torque generated by the ICE TICE is transferred through the powertrainwith different gear ratios ending in the wheels, which gives a force Fdrive that setsthe HDV in motion.

The engine characterization is described deeper in the next subsection. In mean-time consider it as a black box with the torque, TICE , and the angular velocity,ωICE , as outputs to the powertrain. Furthermore, it uses the demanded torque,T ∗ICE , as an input. The angular velocity of the ICE and wheels are related to each

other with a factor defined by the current gear ratio and final drive, see equation(3.8) and (3.9). The clutch is assumed to be stiff. Therefore the torque and angularvelocity from the ICE are the same that is delivered to the gearbox,{

Tc = TICEωc = ωICE

, (3.7)

where Tc is the output torque of the clutch to the gearbox, and ωc is correspondingangular velocity.

The transmission is a gearbox with different gear ratios denoted by it(gnr), wheregnr is the gear number. Each gear has its efficiency, ηt(gnr).

The next part is the final drive that is connected through the propeller shaft.The propeller shaft is assumed to not have any friction. Furthermore, the final driveis a fix ratio if designed such that the engine angular velocity is within desiredoperating points. The efficiency of the final drive is denoted by ηf . The obtainedfinal drive torque Tf , and its angular velocity ωf are given by Tf = TICEitif − |TICEitif (1− ηtηf ) |

ωf = ωICEitif

. (3.8)

The wheels are connected through drive shafts. They are also assumed to beideal. It is also assumed that the two wheels on the shafts have the same speed.

15


Therefore, the shafts can be modeled as one shaft, and the conversion betweenangular velocity of the wheel to vehicle speed is thereby given by

v = rwωw = rwωf = rwωICEitif

, (3.9)

where ωw is the angular speed of the wheels.The forces acting on the wheel where described in (3.1), where Ftrac is given by

(3.6), which is the difference between Fdrive and Fbrake. Fdrive is Tf given in (3.8)divided by rw:

Fdrive = Tfrw

= 1rw

(TICEitif − |TICEitif (1− ηtηf ) |) . (3.10)

HDVs have in exception of the usual service brakes, different auxiliary brakesystems, e.g., a retarder and an exhaust brake. The auxiliary brakes are oftenused in HDVs in order to minimize the wear of the service brakes, but also to avoidbrake fading when the service brakes are used extensively and continuously. Sincesimulations are done on highways, a model of the retarder is enough for this study.It is modeled as a desired braking torque from the transmission through the finaldrive,

Fbrake = Tbrakeifrw

. (3.11)

Finally, the HDV system from engine to vehicle motion is described by:

v = rwωICEitif

v = 1Mv

(Ftrac − Fair − Froll − Fgrav) =

= 1Mv

(( 1rw

(TICEitif − |TICEitif (1− ηtηf ) |)− Tbrakeifrw

)−

− 12CdAvρairv

2 − Mvg(CrrisoF + Cb (|v| − vISO) + CaF

(v2 − v2

ISO

))1000

√1 + rw

2.7

−

− Mvg sin (α))

.

(3.12)

3.2 Important Parts of the Powertrain

3.2.1 Engine

Since the engine losses TICElossesare central for this work, it is necessary to look

deeper into its characteristics. There is the so called drag torque Tdrag, which is theinternal friction caused by moving parts in the engine. The drag torque increasesby increased engine angular velocity. Another loss is the coolant pump Tpump that

16

3.2. IMPORTANT PARTS OF THE POWERTRAIN

is cooling the engine. The higher angular velocity the engine operates at, the morethe engine needs to be cooled, which increases the losses,

TICElosses= Tdrag + Tpump. (3.13)

A total fuel map based on measurements is used to calculate the fuel consump-tion. An example of a typical fuel map for an ICE is shown in Figure 3.3. Thefuel map has TICE and ωICE as inputs and returns the fuel consumption qf in[g/sec]. An accumulated fuel consumption qfacc , and an instantaneous consumptionper revolution qfinst

are then given by:qfinst

= 2πnrncylwICE

qf [g/cycle]

qfacc = 1ρfuel

∫qfdt [liter]

, (3.14)

where nr is number of revolutions per cycle, ncyl is number of cylinders in engine,and ρfuel denotes the density of the fuel that is used.

0

500

1000

1500

2000

2500

−20

0

20

40

60

80

100

−20

0

20

40

60

80

100

engine speed [rpm]

Fuel Map

normalized torque [%]

norm

aliz

ed fuel consum

ption [%

]

Figure 3.3: An authentic example of a typical fuel map for an ICE.

There is a limit of how much torque the engine can deliver. The amount variesfor different angular velocities. The engine has an inertia, which limits the speed of

17


a change in torque. However, the dynamics of the vehicle is significantly slower thanthe dynamics of the engine. Therefore, the inertia of the engine can be neglected.

3.2.2 Gear Shifting

A gear shift is assumed to take one second, during which no torque is deliveredfrom the transmission to the wheels. Therefore, the vehicle motion described in(3.1) becomes,

v = 1Mv

(−Fair − Froll − Fgrav) =

= 1Mv

−12CdAvρairv

2 − Mvg√1 + rw

2.7

CrrisoF + Cb (|v| − vISO) + CaF(v2 − v2

ISO

)1000 −

− Mvg sin (α)) .

(3.15)However, the dynamics for the angular speed of the ICE during the gear shift isnot regarded. A request for a gear shift is a very complicated action in the currentautomated manual transmission (AMT). Therefore, a basic shifting model is donebased only on the engine’s angular velocity, which is specific for each gear ratio.

When EcoRoll is activated, the gearbox is set to neutral. Thus, no torque isdelivered from the ICE, and is modeled as in (3.15). Furthermore, the engine isrun on idle speed ωidle, where the standard speed is 500 rpm for 6-8 cylindricalengines. When disengaging the powertrain, the drop of ωICE to ωidle is not doneinstantaneously. Likewise, when the powertrain is to be engaged, the increase ofωICE does also require time and fuel. However, these dynamics are not regardedsince the fuel consumption needed to engage the gear is assumed to be small andcan thus be neglected, compare the discussion around (3.13). Besides, the injectedfuel to increase ωICE before engaging the powertrain, is compensated when thepowertrain is disengaged, since no fuel is injected when ωICE is decreased.

3.2.3 Cruise Control and Downhill Speed Control

Due to the mass, the HDVs have more advanced functionalities for maintaining speedthan cars. A HDV is usually equipped with a traditional CC, which maintain thespeed according to the speed reference set by the driver. However, the CC does notuse any brakes. And due to the large mass of a HDV, it can accelerate rapidly whentravelling downhill. Therefore, a downhill speed control (DHSC) has been developedfor HDVs. It enables the driver to set a maximum speed that the HDV is allowed toreach.

In this study, it is assumed that the driver always uses the CC and DHSC, wherethe CC is a proportional-integral (PI) controller. Hence, the CC is the driver model.

18

3.3. MODELING SOFTWARE

3.3 Modeling SoftwareMatlab Simulink is the simulation software that is used. It is a simulation andmodel-based design software for dynamic and embedded systems [9]. It also has apowerful tool, Matlab Stateflow, which is especially suitable for the control strategythat is developed. This, as the control strategy is based on rules defining transitionsbetween two discrete states; either open or close the powertrain.

19

Chapter 4

Pre-study of EcoRoll

An interesting part of EcoRoll is that it is possible to implement in a vehicleequipped with an automatic gearbox, only by upgrading the software. There isno need for any hardware changes, which is discussed in the following section. Fur-thermore, it is important to consider possible safety risks and advantages whenimplementing a new function. These aspects are discussed briefly in this chapter,but are only guidelines for future work since the purpose of this thesis is to studythe fuel consumption. However, this chapter is studying hills with different slopes,in order to determine when it is beneficial to open the powertrain. This chapter isconcluded with a summary and a discussion of the results.

4.1 Possibility of Implementation

Unlike cars, the automatic HDVs are often equipped with an AMT. The concept ofan AMT is a manual gearbox that is automatically controlled by a electronic controlunit (ECU) with actuators and sensors. The typical automatic gearbox, continuouslyvariable transmission (CVT), that is used in cars is rarely used in HDVs. The mainreason is that a CVT has lower efficiency than a manual transmission. However, theAMT matches or even improves the efficiency of the manual transmission [7], henceit is preferred.

When a gear change is demanded, a signal is sent to the clutch to open thepowertrain between the ICE and the gearbox in order to be able to disengage thegear, see Figure 3.1. Then, the clutch is engaged. Engaging the new gear is done bytorque control; the engine speed is synchronized with the powertrain angular veloc-ity, regarding the new gear ratio. However, the angular velocity of the powertrainis directly depended on vehicle speed, which can be changed during the gear shift,due to the environmental forces (3.2), (3.3) and (3.4). So, a good prediction of thevehicle speed is necessary.

Thus, disengaging a gear requires only a request by existing signals. Therefore,EcoRoll only needs software implementation, and no extra hardware is needed.

21

CHAPTER 4. PRE-STUDY OF ECOROLL

4.2 Safety Aspects

Engine stops and slippery roads are possible risks for EcoRoll. If the engine suddenlystops during activated EcoRoll, the steering servo will be turned off. This can besolved by either closing the powertrain to help the engine to start rotating again, andthereby turning on the steering servo, or by powering the servo electrically. Besides,an electrical steering servo as such, is more fuel efficient than a conventional one [11].However, this is a large change that initially could have high costs, while the firstsolution of closing the powertrain is just a matter of control signals. It dependsthough on how the powertrain has been opened. It is easy to close the clutch bya control signal, but a disengaged gear requires a controlled engine speed, whichis impossible with the engine turned off. Due to possible lubrication problems,disengaging gear may be preferable to clutch opening. If so, a system for detectingwhen the engine is turned off during activated EcoRoll, and that it tries to start itagain, should be developed.

The brake system on the other hand are, for HDVs, based on air pressure. Ifthe tanks already have high pressure, the brakes will work even though the engineis off. However, the APS that charges the tanks is dependent on a running engine.Therefore, long use of brakes drops the pressure. If no action is taken the HDV willremain unable to brake.

On slippery roads, it is important to not use the auxiliary brakes. This, sincethese brakes are acting only on the driving axles. The EcoRoll in Volvo trucks isactivated only if the retarder is in automatic mode [1]. This is necessary though,as the activation of EcoRoll results in an increased acceleration. This, since theincreased speed needs to be braked if the maximum speed is reached. However adisengaged powertrain is optimal to avoid skidding during a slippery turn, accordingto vehicle dynamics [10, ch. 12.3]. The reason is that the tires can take maximumside force when no longitudinal force is acting on them. Otherwise, e.g., when enginebraking with closed powertrain, the ability to take side force is limited even more.This may give unbalance between wheels, that causes the skid in a slippery turn.Low speed is thus required before the turn, and thereby it is more optimal to havea closed powertrain and slow down the vehicle speed before the turn, and open thepowertrain only during the turn.

4.3 Road Topography and Strategies

The most important part of the feasibility study is to identify the characteristicsof a hill that needs to be fulfilled, such that it is advantageous to activate EcoRoll.Furthermore, it can also be more or less efficient to activate EcoRoll before, in andafter a downhill. This section will discuss different hills and strategies followed bya section where the simulation results are presented and discussed.

22

4.3. ROAD TOPOGRAPHY AND STRATEGIES

4.3.1 The Studied Hills

There are three different downhill slopes that are of interest; an ideal, steeper, andless steep hill. These hills are defined and described here and used for the study innext section.

Ideal Downhill

The definition of an ideal downhill for EcoRoll in this work is a hill with a slopesuch that the sum of the environmental forces is zero,

Fgrav + Froll + Fair = 0, (4.1)

i.e., the vehicle with an open powertrain can keep its speed constant. This hillis interesting since a fuel reduction for this situation indicates that the reductionwould be even greater for an accelerated HDV with an open powertrain. However,that is not obvious for all accelerating situations. This will be described in thefollowing subsection.

If the powertrain is closed in the ideal hill, the drag torque of the ICE is added asa resistance force and thereby the vehicle decelerates if no more fuel is injected. Theadditional fuel is needed since the drag torque increases for higher angular velocityas described in Section 3.2.

The inclination of an ideal downhill with activated EcoRoll, αER, is derivedusing (4.1), where the gravity force is given in (3.2). The resulting expression isthen,

αER = − arcsin(Froll + Fair

Mvg

). (4.2)

To get corresponding inclination for the closed powertrain, αCP , the losses ofthe ICE is added to (4.1) obtaining

FICElosses+ Fgravity + Froll + Fair = 0, (4.3)

where FICElossesis the engine losses given by an engine specific table, see Section 3.2.

The ideal inclination for a closed powertrain is expressed as:

αCP = − arcsin(FICElosses

+ Froll + FairMvg

). (4.4)

Obviously a hill with inclination αCP is steeper than αER. Thereby, if thecondition for α in,

αCP < α < αER, (4.5)

is fulfilled, the vehicle accelerates when EcoRoll is activated and decelerates whenthe powertrain is closed.

23


Steeper Downhill

Here, the negative slope αsteep is larger than αCP ,

αsteep < αCP . (4.6)

Therefore, the HDV will accelerate with a closed powertrain even though no fuel isinjected. According to the PhD Thesis [5], it is always more beneficial to close thepowertrain, since the vehicle accelerates even though it enters fuel cut-off mode.This is though not obvious, since by opening the powertrain the acceleration be-come even higher. With the increased speed, the fuel consumption is decreased perdistance, since the fuel consumption of an engine running at idle is constant pertime interval. EcoRoll eliminates the drag losses from the ICE, which means thatEcoRoll is activated longer, while a conventional HDV will need to deliver torquesooner, seen in Figure 2.1.

However, the problem occurs when the length of the hill is not known, sincethe speed will increase more with activated EcoRoll and the maximum speed set bythe DHSC could be reached earlier and the HDV will then brake. Increased brakingmeans more losses.

Less Steep Downhill

Due to a smaller negative slope, αlesssteep ,

αER < αlesssteep < 0, (4.7)

the HDV will decelerate even if the powertrain is open. Here, it is interesting tostudy whether it is beneficial to accept some deceleration by EcoRoll mode followedby a peak in torque from the ICE to maintain the speed. If the required torque peakis brief the accumulated fuel consumption could still be small. However, the timeis increased.

It is also interesting to study the advantage of activating EcoRoll in such hills, ifthe current speed is above the set speed, and let the vehicle decelerate slowly downto the set speed.

Uphill

Despite the inclination, αuphill, being positive,

αuphill > 0, (4.8)

the EcoRoll mode could be beneficial in specific situations. As in Less Steep Hill,when the current speed is above the CC set speed, the drag torque from ICE iseliminated on the vehicle motion with activated EcoRoll, even though the gravityforce is opposite to the speed direction,

FICElosses+ Fgravity + Froll + Fair > Fgravity + Froll + Fair > 0. (4.9)

Thereby, the deceleration is still lower than with a closed powertrain.

24

4.3. ROAD TOPOGRAPHY AND STRATEGIES

4.3.2 Activation Time of EcoRoll

According to [5], it is beneficial to activate EcoRoll only when the inclination ofthe hill fulfills (4.5). Even so, it is still interesting to study hills with inclinationsoutside the given range. So in this phase of the study, EcoRoll will be activatedeven in hills with other slopes.

Another aspect is to study where in the hill it is beneficial to activate EcoRoll.Of course, during the hill is the first thing that comes in mind, call the segmentIn Hill. When the vehicle is accelerated during the hill, it is interesting to studythe benefit of decelerating with EcoRoll after the hill until CC set speed is reached,With AfterHill.

There are studies within Look-Ahead where the speed is reduced before a down-hill to decrease the need of braking. An attendant question is whether it is moreefficient to reduce the speed before the hill with EcoRoll, ER BeforeHill, or withclosed powertrain, CP BeforeHill.

4.3.3 Constructed Simplified Hills

The simplified hills are 15 km long and consist of three parts with equal lengths, seeFigure 4.1. The first part is plane followed by a downhill, and in order to maintainstationary conditions, the last part is also plane. The slope of the second part isvaried to study the impact of different inclinations. The steepest hill is constructedalso with a short version in order to study the influence of the length of hill.

Figure 4.1: The constructed simplified hill. Note that the inclination is small, butseems to be high due to scaling. The inclination is -0.98%, corresponding to αERfor a HDV driving at 80 km/h and a weight of 40 tonnes.

25


The first part makes it possible to study the BeforeHill function. The last partenables study of the AfterHill function. It also allows both the vehicle that isequipped with EcoRoll and the reference vehicle to reach the CC set speed, to getcomparable results.

An even more simple hill was constructed without any plane part, only a constantslope. Here, it is chosen to study the reduction of fuel consumption when travellingin an inclination of αER.

4.4 Quadratic Cost FunctionThe control strategies are based on rules rather than a cost function. However,since the reduction of the fuel consumption usually increases the travel time, a costfunction is used to regard both the travel time and fuel consumption, in order todetermine a fair result.

According to [4], a quadratic cost function is preferred to a linear cost function.This, since the quadratic function values points of the same distance to the originequal. The origin is though not achievable, since it means that the HDV travelswith infinity speed by no fuel consumption. However, the aim is to move in thisdirection. The quadratic cost function is given by,

fcost = β

(tERtCC

)2+ (1− β)

(qfaccER

qfaccCC

)2

, (4.10)

where travel time and accumulated fuel consumption, for the HDV equipped withEcoRoll, are normalized by corresponding time and fuel consumption for a referenceHDV with conventional CC. Furthermore, β is a weighting parameter. In [4], β isdetermined such that it is optimal to drive in constant speed on plane road. Thevalue of beta, for a CC set speed of 80 km/h, is determined in [4] to be

β = 0.4. (4.11)

It is worth to mention that a decreased fuel consumption for EcoRoll does not in-crease the travel time, while it usually does in a conventional HDV, see Section 4.3.1.However, the cost function is based on an increased time when fuel is reduced, butsince EcoRoll is compared to a conventional HDV, (4.10) is a reasonable cost func-tion.

The results will be presented in percentage, where a negative result correspondsto saving when EcoRoll is utilized,

fcost% = 100 (fcost − 1)tsave = 100

(tERtCC− 1

)qfaccsave

= 100(qfaccER

qfaccCC

− 1) . (4.12)

26

4.5. SIMULATION RESULTS

4.5 Simulation ResultsFor the studied vehicle with parameters according to Table A.1, the ideal slopes arecalculated according to (4.2) and (4.4). The results are:{

αER = −0.0098 rad ≈ −0.98%αCP = −0.0116 rad ≈ −1.16% . (4.13)

The fuel saving on a hill with the constant slope αER is as much as 73% withoutany change in travel time. The result is amazing! However, that is for an ideal hill,which is only a small part in authentic roads.

A simulation is made where two vehicles, a conventional vehicle and one equippedwith EcoRoll, driving through the simplified hills, see Figure 4.1. The results pre-sented in Table 4.1 is for when the EcoRoll is activated only during the segment InHill. The first column gives the slope of the second part of the hill. The cost insecond column is calculated according to (4.10), based on the time- and fuel savingresults presented in column three and four. A negative value indicates reduction oftime or fuel respectively.

To study the impact of the length of a hill, a shorter hill of the steepest hill werealso studied.

Table 4.1: The results of a HDV equipped with EcoRoll using the function In Hill,i.e., opening the powertrain when the HDV is in the downhill. A Negative signindicates a saving compared to a reference vehicle equipped with a conventional CC.

Slope Cost Time Fuel-0.78% -3.06% 2.94% -4.65%-0.88% -8.06% 1.35% -7.94%-0.98% -7.27% 0.01% -6.26%-1.08% -6.01% -1.15% -4.34%-1.18% -4.78% -1.98% -2.71%-1.28% -2.47% -1.46% -1.10%-1.38% -0.33% -0.79% 0.25%-1.48% 0.18% -0.32% 0.36%-1.48% short -1.53% -0.29% -1.09%

Table 4.2 shows the simulation results using the With AfterHill function. Hillsthat does not give any acceleration are not of interest for this function and aretherefore omitted. The results of using the Only AfterHill function is presentedin Table 4.3. Here only hills where the HDV reaches, at least nearly, the DHSC setspeed are of interest.

The last study is the Before Hill function on the steepest hill where the DHSCset speed is reached. Here are CP BeforeHill and ER BeforeHill combined withOnly AfterHill, and compared with each other, see Table 4.4.

27


Table 4.2: The results of a HDV equipped with EcoRoll using the function WithAfterHill, meaning that the powertrain is opened both in the hill and after the endof the hill, until CC set speed is reached again. However, this study requires a slopegiving an acceleration. Therefore, some hills are omitted.

Slope Cost Time Fuel-1.08% -6.39% -1.16% -4.67%-1.18% -5.56% -2.01% -3.38%-1.28% -3.27% -1.49% -1.75%-1.38% -1.27% -0.83% -0.51%-1.48% -0.76% -0.36% -0.39%-1.48% short -2.21% -0.33% -1.64%

Table 4.3: The results of a HDV equipped with EcoRoll using the function OnlyAfterHill, i.e., the powertrain is only opened after the end of the hill. This isstudied for steep slopes where the DHSC set speed is reached in the hill.

Slope Cost Time Fuel-1.28% -0.47% -0.01% -0.39%-1.38% -0.88% -0.03% -0.71%-1.48% -0.94% -0.04% -0.76%-1.48% short -0.46% -0.02% -0.37%

4.6 Discussions on the Feasibility Study

The ideal hill, with the 73% fuel saving, indicates that large losses in the ICE canbe reduced by opening the powertrain. However, such hills are rare on authenticroads. Thus, a real indication of fuel saving for a HDV in duty can only be obtainedby constructing a good control strategy and simulate on known data of an authenticroad. These simulations are done for the two EcoRoll strategies that are presentedin Chapter 5 and 6.

The results in Table 4.1 show that it is advantageous to activate EcoRoll evenfor steeper slopes than αCP . However, the limit of how steep the hill can be tobe beneficial to open the powertrain, is dependent on the length of the hill andthe difference between CC set speed and DHSC set speed. That is proved by acomparison of the regular and short hill with inclination -1.49%. The HDV does notreach the DHSC set speed when travelling down the short hill, while it does reach itin the regular one. In the table, both fuel and time is saved in the short hill usingEcoRoll compared to conventional CC. On the longer hill, only time is saved withEcoRoll due to higher acceleration, but the fuel consumption is even larger.

28

4.6. DISCUSSIONS ON THE FEASIBILITY STUDY

Table 4.4: In too steep and long hills, it is beneficial to decrease the speed beforethe start of the hill to avoid braking. This table compares two ways of decreasingthe speed before a hill; with closed powertrain (CP) and open powertrain (ER). Itis tested in combination of With AfterHill or Only AfterHill.

Slope Cost Time Fuel

With AfterHill-1.48% -0.76% -0.36% -0.39%-1.48% ER BeforeHill -5.95% 1.07% -5.84%-1.48% CP BeforeHill -4.82% 1.01% -4.81%

Only AfterHill-1.48% -0.94% -0.04% -0.76%-1.48% ER BeforeHill -5.42% 2.40% -6.34%-1.48% CP BeforeHill -4.61% 2.35% -5.58%

Comparing the InHill and With AfterHill (Table 4.1 and 4.2), the latter hasbetter results in all different hills regarding both fuel and time. Some hills arehowever not included in Table 4.2, since the negative inclination is not high enoughto get the HDV to accelerate by activating EcoRoll, and thereby no deceleration isneeded.

It is already shown that the function In Hill is beneficial, unless the HDV doesreach the DHSC set speed. Furthermore, adding AfterHill increases the savingsfor HDV that reaches higher speed than the given CC speed, which is the case whenreaching the DHSC set speed. It can be concluded that Only AfterHill should be usedfor hills where the DHSC set speed is reached. The results are presented in Table 4.3.Comparing the results for the hill with the inclination -1.48% and regular length,the best results where, as expected, reached using Only AfterHill, regarding fuelsaving and total cost.

As mentioned earlier, an avoidable braking is considered as a loss, which isdesired to be reduced. By decreasing speed before a steep hill, braking can bedecreased or even eliminated. By that, fuel is saved at the expense of increasedtravel time. However, comparing Table 4.3 and 4.4, shows that the total cost isreduced radically. With respect to fuel consumption, it is even better to reducethe speed by activating EcoRoll before a hill rather than reducing it with a closedpowertrain. However, activating EcoRoll in the segment BeforeHill shows betterresults when it is combined with With AfterHill than Only AfterHill, since for thestudied hill, the DHSC set speed is not reached when the speed is reduced beforehill.

Another observation from the results is that neither the time nor the fuel savingsare linear for a linear variation of inclination. This is mainly caused by the HDVmotion being affected by two components of the environmental forces that are non-linearly dependent on the speed, see the equations (3.3) and (3.4). Therefore, theacceleration is nonlinearly varied during a slope with constant inclination, meaningthat the variations of the speed and the time are also nonlinear. As mentioned

29


earlier, for open powertrain, the fuel consumption decreases with increased speed.Therefore, the fuel savings are also nonlinear.

30

Chapter 5

Conventional EcoRoll

The decisions of the conventional EcoRoll are rules based on prevailing conditions.The strategy is described in this chapter, followed by simulation results. The simula-tions are done for two HDVs, a conventional HDV and one utilizing EcoRoll function-ality. The HDVs were simulated to drive through two different roads; the highwayfrom Södertälje to Norrköping and from Linköping to Jönköping, in Sweden. All val-ues of the parameters of the control strategy are given in Table A.2 in Appendix A.

5.1 Control Strategy

The control strategy consists of rules for when EcoRoll should be activated. Therules considers the results from the feasibility study, based on prevailing road in-clination and vehicle speed, and on estimated acceleration of the HDV with openpowertrain.

The strategy has two different main states; Active and Inactive, see Figure 5.1.The active state has three sub states for different conditions; Accelerating Hill,Decelerating Hill and After Hill, see Figure 5.2. The EcoRoll is active when beingin any of these sub states. The differences between the states are the conditionsdefined by transitions and from which state it is able. However, all conditions canbe defined by only using the main states with two transitions, but dividing in substates provides better visualization and easier understanding. The transitions andtheir conditions are described below. However, the signals that the controller isbased on should be described first.

5.1.1 Input Signals to the Controller

This study is meant to indicate the achievable result when driving with EcoRollin reality. Therefore, the signals into the controller should be available in the ECUwhere it could be implemented in the future. The controller is based on five signals;current speed, CC set speed, DHSC set speed, inclination and estimated accelerationof the HDV with open powertrain. The set speeds, current speed and inclination are

31

CHAPTER 5. CONVENTIONAL ECOROLL

Figure 5.1: The main states of the controller; Active and Inactive, i.e., opened orclosed powertrain. A transition occur when some specific conditions regarding speedand acceleration are fulfilled.

available through different systems. However, the acceleration is not known, normeasured. Even though the HDV is equipped with an accelerometer, the accelerom-eter measures the current acceleration regardless of the powertrain being open orclose. The desired acceleration is for a HDV with open powertrain aER. Therefore,it should be estimated, e.g., by dividing the environmental forces by the vehiclemass,

aER = −Froll + Fair + FgravMv

. (5.1)

However, the aim is that the controller should be ready for implementation in aHDV. Therefore, the estimation of the acceleration should either be based on anestimation of the components in (5.1) or on measured signals. A drawback with thefirst case is that it requires accurate models of the environmental forces.

For the second case, the current acceleration can be measured by an accelerome-ter. Thus, the total force Ftot acting on the HDV can be calculated. Ftot correspondsto the force caused by the engine and brake (Ftrac) with subtraction of the environ-mental forces,

Ftot = Ftrac − Fair − Froll − Fgrav. (5.2)The total environmental forces can then be estimated by subtracting Ftrac fromFtot. Hence, the estimation of aER is finally obtained by dividing the resulting forceby Mv,

aER = Ftot − FtracMv

. (5.3)

This method is used since all parameters in (5.3), i.e., Ftot, Ftrac, and Mv caneither be measured or estimated by using already existing signals in HDVs. Thisenables the strategy being implemented in a HDV for future work.

32

5.1. CONTROL STRATEGY

Figure 5.2: The state Active consists of several sub states depending on the prefer-ences of the current circumstances. For instance, the sub state After Hill is enteredonly if conditions in Algorithm 3 are fulfilled and the prior active sub state is Ac-celerating Hill. This, since the powertrain is desired to still be open only after anaccelerating hill. The solid lines corresponds to the main required transitions, wherethe dashed and dotted lines are added to improve the controller, taking in accountthe interaction between the states.

5.1.2 Accelerating HillAn accelerating hill is a hill where the vehicle accelerates if the EcoRoll is activated.Although, this is desirable since the HDV accelerates with low fuel consumption, thelimitation is when the DHSC set speed is reached. However, a maximum speedvmax with margin from the DHSC set speed vDHSCmargin is declared. It is no longerpossible to activate EcoRoll, if the HDV reaches the maximum speed and has apositive acceleration.

The margin is set for two reasons. The first one is for the time elapse to engagingthe gear, before reaching the DHSC set speed. The second is since it is, accordingto the feasibility study, more beneficial to not activate EcoRoll when it is known

33


that the DHSC set speed is going to be reached. However, Look-Ahead data is notavailable for this control strategy, but it can be considered that the risk is high toreach DHSC set speed.

Imagine a large uphill which lets the HDV decelerate despite that maximumtorque is delivered. The speed can decelerate radically, depending on engine’s powerrate and mass of the HDV. So, if there is no lower speed limit, and an acceleratinghill is followed by this large uphill, the EcoRoll will be activated no matter howsmall this acceleration could be. This gives longer travel time. Therefore, a lowerspeed limit, vmin, is another condition for this state.

The conditions for Accelerating Hill are summarized in Algorithm 1.

Algorithm 1 Accelerating hillvmax = vDHSCset − vDHSCmargin

vmin = vCCset − vCCmargin

if aER ≥ 0 && v < vmax && v > vmin thenreturn open powertrain

end if

5.1.3 Decelerating Hill

If the downhill is not steep enough, the HDV will decelerate with open powertrain.However, it could still be advantageous to utilize the benefit of EcoRoll’s fuel saving.It is proved in the pre-study that fuel saving is more than the time loss, according tothe cost function (4.10). However, the conditions have to be strict since much speedreduction is not preferable. Therefore, a maximum deceleration limit decmax is set.Furthermore, unlike the Accelerating Hill, the negative inclination condition shouldbe explicitly defined. This, since a deceleration could be caused by an uphill, whichis not preferred if the initial speed before entering the Active state v0 is below the CCset speed. However, if the state is already entered, the speed is allowed to decreasebelow the CC set speed by a margin of vCCmargin . The conditions for DeceleratingHill are finally summarized in Algorithm 2.

Algorithm 2 Decelerating hillif aER < 0 && aER > decmax && α < 0 && v0 > vCCset thenreturn open powertrain

end if

5.1.4 After Hill

At the end of an accelerating hill, the speed of the HDV is above the CC set speed.So, deceleration is necessary after the hill. From the pre-study it was shown that itis always (unless the speed is not too low, which usually is not the case on highways)

34


more advantageous to decelerate by activating EcoRoll than by engine braking, bothregarding travel time and fuel consumption. The condition for this sub state is thenan estimated negative acceleration with open powertrain, and speed above the CCset speed, see Algorithm 3.

Algorithm 3 After hillif aER < 0 && v > vCCset thenreturn open powertrain

end if

5.1.5 A Low-Pass Filter

The gearbox requires time to engage and disengage the gear. Therefore, a lower timelimit, tchangemin

, is required to remain within a main state. So, if the conditions toactivate EcoRoll are fulfilled, the controller will first check that it has been locatedin Inactive mode for at least tchangemin

. Since, the state Active consists of severalsub states, another sub state, Wait, is placed there, in order to collect from othersub states that requests to deactivate EcoRoll, and then check that the lower timelimit has elapsed. This time limit filters rapid decision changes, which may happendue to that the HDV does not know anything about the road ahead.

5.1.6 The Transitions between the States

The transition from the state Inactive to Active, consists unfortunately of two parts,see Figure 5.1 and 5.2. This depends on whether Algorithm 1 or Algorithm 2that has fulfilled conditions. Therefore, there are two inputs in the detailed Fig-ure 5.2. Furthermore, it can be seen, in same figure, that all sub states have to gothrough the sub state Wait if closed powertrain is demanded, which was describedin Section 5.1.5. As mentioned before, it is beneficial to activate EcoRoll after anaccelerating hill. Therefore, a transition goes from Accelerating Hill to After Hill.

Besides the solid arrows, that are the basic part of the controller, there aredashed and dotted transition arrows. The dashed arrows were added, betweenAccelerating Hill and Decelerating Hill, since inclination of a hill may vary suchthat some parts of it accelerate the HDV while other parts decelerate it. Moreover,the dotted arrows are added from the sub state Wait to give the controller abilityto undo a decision when it occurs within tchangemin

. This, since it is unfavorable,from the driving performance point, to instead let the powertrain close first andopen again after additional tchangemin

, when the controller already wanted to undothe decision of closing powertrain within the first tchangemin

.Note that conditions for some transitions may occur simultaneously. Therefore,

a prioritization of which transition is preferred if this happens should be chosen.This is given by the number in the beginning of the arrow in Figure 5.2, where 1

35


gives the highest priority. The priorities are chosen such that EcoRoll is activatedmaximum possible time.

5.2 SimulationsThe control strategy that has been described in the previous section is used insimulation of an HDV in two roads; Södertälje-Norrköping and Linköping-Jönköping.This is compared to a reference HDV, and based on the cost function (4.10) theresults are presented in Table 5.1. The results of Södertälje-Norrköping are amazing.However, even though simulations on Linköping-Jönköping also give positive results,the difference between the results are large.

The simulations can be compared in Figure 5.3 and 5.4. The figures show thespeed of both HDVs (the one with EcoRoll and the reference), the road topographyand the control signal. Value one on the control signal indicates a request to openthe powertrain. Comparing the speed graphs and the road topographies, it can beseen that the large difference in results can be explained by the amount of slopes.Södertälje-Norrköping has a lot more slopes that can be utilized by EcoRoll. Furtheranalyze of road topography is made in Chapter 7. Moreover, different disturbancesare added to analyze the sensitivity in Chapter 8. Prior to these, another strategyis developed in the next chapter, utilizing Look-Ahead data in order to improve theresults.

Table 5.1: The simulation results using the conventional EcoRoll.

Road Cost Time FuelSödertälje-Norrköping -4.2648% -0.2943% -3.4164%Linköping-Jönköping -0.8622% -0.1572% -0.6157%

36

5.2. SIMULATIONS

0 2 4 6 8 10 12

x 104

60

80

100

distance [m]

speed [km

/h]

vCC

set

vDHSC

set

HDV with EcoRoll

HDV with CC

0 2 4 6 8 10 12

x 104

0

50

100

150

distance [m]

altitude [m

]

0 2 4 6 8 10 12

x 104

0

0.5

1

distance [m]

contr

ol sig

nal

Figure 5.3: Simulations of the conventional EcoRoll, traveling from Södertälje toNorrköping.

0 2 4 6 8 10 12 14

x 104

70

80

90

100

distance [m]

speed [km

/h]

vCC

set

vDHSC

set

HDV with EcoRoll

HDV with CC

0 2 4 6 8 10 12 14

x 104

0

100

200

300

distance [m]

altitude [m

]

0 2 4 6 8 10 12 14

x 104

0

0.5

1

distance [m]

contr

ol sig

nal

Figure 5.4: Simulations of the conventional EcoRoll, traveling from Linköping toJönköping.

37

Chapter 6

EcoRoll utilizing Look-Ahead

The main reason to develop a strategy that utilizes Look-Ahead data, is the abilityto identify hills where DHSC set speed can be reached with activated EcoRoll. This,in order to minimize fuel consumption even further.

To get results that are comparable with the previous strategy, the structure ofthe controller and its parameters will be held the same as much as possible. However,some modifications are done, where the main change is the speed prediction.

6.1 Control Strategy

This strategy predicts the speed of the downhill ahead. Based on the predictedachievable speed, the controller makes a decision; whether to open the powertrain ornot. The main states are the same as before, see Figure 5.1, but with modificationswithin the states. However, the speed prediction is calculated in parallel to thesestates. The prediction is described in the following section, followed by presentingthe modifications of the algorithm.

6.1.1 Speed Prediction

In addition to the required signals that where described in Section 5.1.1, the dataof the topography ahead should be available, and a signal of the current positionreceived from, e.g., a GPS. Based on the known current position, inclination andthe inclination of the road ahead, the environmental forces that will act on the HDVcan be predicted using models like in (3.2), (3.3) and (3.4), to calculate aER byusing (5.1). However, the available data for the topography is discontinuous, with adistance of ∆p between known points. It is assumed that ∆p is small enough, givingneglected dynamics between two positions. Therefore, the acceleration between twopositions is assumed to be constant. With this background, the speed for nextposition, p+ (n+ 1) ∆p, is given by

v (p+ (n+ 1) ∆p) = v (p+ n∆p) + ∆v (p+ n∆p) , (6.1)

39

CHAPTER 6. ECOROLL UTILIZING LOOK-AHEAD

where p is the current position for the HDV, n an integer when multiplied with ∆pgives the distance from p to the predicted position and

∆v (p+ n∆p) = aER(p+ n∆p) ∆pv (p+ n∆p) . (6.2)

Note that the hat on a variable denotes that it is a prediction.A new prediction is started frequently with a time period, tnewpred

, see Figure 6.1.This, by calculating v (p+ (n+ 1) ∆p) with a sampling time, tsample, where n isincreased by one for each sample. This means that the speed is predicted for adistance of ∆p tnewpred

tsample[m]. Let, e.g., ∆p = 12 m, tsample = 0.01 s and tnewpred

= 1s, the prediction is then obtained for 1200 meters ahead.

Obviously, the speed increases when traveling downhill, and the controller needsto know the maximum predicted achievable speed, vpredmax . This is determined bycomparing v (p+ (n+ 1) ∆p) with v (p+ n∆p) in each step, if v (p+ (n+ 1) ∆p) >v (p+ n∆p) set v (p+ (n+ 1) ∆p) as new value of vpredmax . For this application, thisapproach is a robust way to determine the maximum value, since the calculationsare time discrete.

The Definition of a Downhill

A downhill is characterized by an increased speed followed by speed reduction, seeFigure 2.1. However, small deviations from the CC set speed are not of interest fora large downhill where DHSC set speed is reached. Therefore, the small deviationsare filtered by defining the start of a downhill, which is when the speed is increasedabove CC set speed with a margin of voverspeed. Then the acceleration decreases,followed by a deceleration, where the downhill ends. Finally, after some time, thespeed reaches the CC set speed again. So, an increased speed above the DHSC setspeed happens before the deceleration starts.

The Procedure of Prediction

As mentioned previously in this section, when tnewpredis elapsed, a new prediction

is done. Within this time, the predictor looks for a downhill that is character-ized as presented in the definition of a downhill. Data is saved when the downhillcharacterization is found, otherwise deleted.

The Figure 6.1 presents the procedure of speed prediction, downhill determina-tion and data collection.

6.1.2 Algorithm

The risk that was taken in the previous strategy was to accelerate too much andreach the DHSC set speed. Therefore, the sub state Accelerating Hill in Figure 5.2,is the one that needs to be reconstructed by adding the condition that vpredmax

should be less than vDHSCset to enter this mode, see Algorithm 4. By this, the

40


Figure 6.1: The procedure of the speed prediction. Speed prediction is calculatedduring the whole period, while the sub states identifies the downhill and store data.

controller will not open the powertrain if it estimates that the HDV acceleratesbased on prevailing conditions and predicts that DHSC set speed will be reached forthe current downhill. However, if the estimation of acceleration fulfils conditions forAlgorithm 2 corresponding to decelerating hills, the speed prediction is not takeninto account.

Algorithm 4 Accelerating Hill with Look-Aheadvmax = vDHSCset − vDHSCmargin

vmin = vCCset − vCCmargin

if aER ≥ 0 && v < vmax && v > vmin && vpredmax < vDHSCset thenreturn open powertrain

end if

41


A problem occurs when a decelerating hill, where the speed is accepted to de-crease below CC set speed, is followed by an accelerating hill where vDHSCset isreached. This, since the controller will choose to close the powertrain when thespeed has decreased to vmin = vCCset − vCCmargin , and the CC will then request ahigh peak torque to maintain the set speed regardless of the downhill ahead. This,is not efficient from a fuel consumption point of view. A solution is therefore tolet the controller to set the reference speed for the CC. This enables the controllerto decrease the speed reference when traveling down an accelerating hill, wherevDHSCset is going to be reached. By this, the CC will not cause a torque peak forthe described scenario. Furthermore, since a high acceleration is predicted, the HDVwill accelerate regardless of how much the speed reference is decreased. However,this solution requires some changes in the structure of the controller.

The structure changes are regarding how to change speed reference when closingthe powertrain. Firstly, the state Inactive is divided into two sub states; OrdinaryCC and Decreased Reference, see Figure 6.2. The state Ordinary CC corresponds tothe previous Inactive, where the powertrain is closed and the CC has the set speedas reference. However, Decreased Reference also requests closed powertrain butalso decreases the speed reference of the CC. Note that there is no reference speedexplicitly given in the main state Active. This, since the value of the reference speeddoes not matter when the powertrain is open. The transitions that are modifiedcompared to the previous strategy is shown in Figure 6.2 with thicker arrows.

Now, there are two outputs from the sub state Wait to the main state Inactive.One pointing to the sub state Ordinary CC with same time condition as before, andthe other one pointing to Decreased Reference, where vpredmax > vDHSCset shouldalso be satisfied in addition to the time condition. Of course, when the conditionsfor the transition to Decreased Reference are satisfied, also the condition for thetransition to Ordinary CC is fulfilled. Therefore, due to the transition conflict, aprioritization is given to the transition to Decreased Reference.

6.2 Simulations

The control strategy of Look-Ahead EcoRoll is implemented in Matlab Simulinkand simulated in the same way as for the conventional EcoRoll. The results of sim-ulating on the roads Södertälje-Norrköping and Linköping-Jönköping are presentedin Table 6.1. Corresponding graphs of speeds, altitude and control signal are shownin Figure 6.3 and 6.4 respectively. The cost and fuel savings are improved. However,the travel time increases since sometimes it is chosen not to open the powertrainduring downhill. In these situations, the acceleration is slower.

The situations where the powertrain is chosen to remain closed is when thecontroller predicts that the speed of the HDV will reach the DHSC set speed inthe current downhill. This is the main idea of using Look-Ahead data instead ofconventional EcoRoll; to improve fuel savings. There are several of these steep hillson both of the roads that are used in the simulations. One such hill is presented in

42

6.2. SIMULATIONS

Figure 6.2: An overview of the states of the controller that utilizes Look-Aheaddata. Compared to the conventional EcoRoll, seen in Figure 5.1 and 5.2, a substate is added in the Inactive state decreasing the speed reference. The thickestarrows correspond to the additional transitions, compared to the previous strategywithout Look-Ahead.

Figure 6.5, showing the difference of the control strategies.

Table 6.1: The simulation results using Look-Ahead EcoRoll.

Road Cost Time FuelSödertälje-Norrköping -4.5648% -0.1972% -3.7427%Linköping-Jönköping -1.0264% -0.0468% -0.8276%

43


0 2 4 6 8 10 12

x 104

60

80

100

distance [m]

speed [km

/h]

vCC

set

vDHSC

set

HDV with EcoRoll

HDV with CC

0 2 4 6 8 10 12

x 104

0

50

100

150

distance [m]

altitude [m

]

0 2 4 6 8 10 12

x 104

0

0.5

1

distance [m]

contr

ol sig

nal

Figure 6.3: Simulations of Look-Ahead EcoRoll through Södertälje-Norrköping.

0 2 4 6 8 10 12 14

x 104

60

80

100

distance [m]

speed [km

/h]

vCC

set

vDHSC

set

HDV with EcoRoll

HDV with CC

0 2 4 6 8 10 12 14

x 104

0

100

200

300

distance [m]

altitude [m

]

0 2 4 6 8 10 12 14

x 104

0

0.5

1

distance [m]

contr

ol sig

nal

Figure 6.4: Simulations of Look-Ahead EcoRoll through Linköping-Jönköping.

44

6.2. SIMULATIONS

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4

x 104

70

80

90

100

distance [m]

speed [km

/h]

vCC

set

vDHSC

set

HDV with EcoRoll

HDV with CC

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4

x 104

0

20

40

60

distance [m]

altitude [m

]

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4

x 104

0

0.5

1

distance [m]

contr

ol sig

nal

(a) Look-Ahead EcoRoll does not open the powertrain when it knows that the DHSC set speed isgoing to be reached.

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4

x 104

70

80

90

100

distance [m]

speed [km

/h]

vCC

set

vDHSC

set

HDV with EcoRoll

HDV with CC

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4

x 104

0

20

40

60

distance [m]

altitude [m

]

1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4

x 104

0

0.5

1

distance [m]

contr

ol sig

nal

(b) The conventional EcoRoll does not know the topography ahead. Therefore, when it estimates apositive acceleration it takes the risk of opening the powertrain.

Figure 6.5: The graphs show the main difference between the control strategies ofconventional EcoRoll and Look-Ahead EcoRoll. Since Look-Ahead EcoRoll predictsthe speed ahead, it knows that the DHSC set speed will be reached. Therefore, itchooses not to open the powertrain

45

Chapter 7

The Sources of Saving Potential

The simulation results in Chapter 5 and 6, are amazing for the road Södertälje-Norrköping. This raises interest for studying the amount of contribution that comesfrom the nonlinearity of engine fuel map. However, the fuel savings when travelingLinköping to Jönköping were much less. Therefore, the first section studies thetopography of the roads, while the next section discusses the impact of the engine’snonlinearity.

7.1 Road Topography

Due to the large differences between the two topographies that where simulated, it isinteresting to study the content of inclinations for each topography. A study of theportion of the inclinations were made for both roads. These are then compared toeach other, see Figure 7.1. How much of the road consists of a particular inclinationis presented in percentage.

The topography data is an array consisting of inclinations for every ∆p meter.The portion is calculated by summing up number of elements in the array thatconsists of a specific inclination (with some tolerance), and then dividing by thetotal number of elements.

From Figure 7.1, it can be seen that the road Linköping-Jönköping consist moreof the small slopes than Södertälje-Norrköping. Furthermore, the road Södertälje-Norrköping has a larger portion of inclinations that are more negative than -0.5%,and in particular slopes between αER and αCP . Therefore, Södertälje-Norrköpinggives better results. The portion between αER and αCP is integrated for both roadsand presented in Table 7.1. However, even though the strategies utilizes otherslopes, this can give some indications of the size of the impact the road topographyhas on the results. This, since it is known that these inclinations give positive resultsfor EcoRoll, where length of hill should be regarded for more negative inclinations.

The corresponding fuel savings for αER, in Table 7.1, is based on the resultfrom the feasibility study showing that the fuel saving in a slope of αER is 73%.However, this is only true if the HDV has a speed of 80 km/h. Furthermore, the

47

CHAPTER 7. THE SOURCES OF SAVING POTENTIAL

−4 −3 −2 −1 0 1 2 3 40

0.2

0.4

0.6

0.8

1

1.2

1.4

Slope/%

Perc

ent/%

Slope Portion

Södertälje−Norrköping

Linköping−Jönköping

αCP

αER

Figure 7.1: The portion of inclinations for the two highways. The vertical dashedlines mark the inclinations αER and αCP .

Table 7.1: How much a road consists of an inclination and its corresponding fuelsavings. The fuel savings when traveling in a slope of αER is 73%, assuming thatthe HDV speed is 80 km/h. For αER ≤ α ≤ αCP it is also assumed that it gives73% fuel savings, just to get some indication.

Road Topography Slope/Control Strategy Portion Fuel

Södertälje-Norrköping

αER 0.2625% -0.1933%αER ≤ α ≤ αCP 4.3513% -3.2036%

Conventional EcoRoll - -3.42%EcoRoll with Look-Ahead - -3.74%

Linköping-Jönköping

αER 0.1379% -0.1016%αER ≤ α ≤ αCP 1.2020% -0.8849%

Conventional EcoRoll - -0.62%EcoRoll with Look-Ahead - -0.83%

48

7.2. THE IMPACT OF THE NONLINEAR FUEL MAP

case is not the same for αER ≤ α ≤ αCP but to get some indication, even here theportion is multiplied by -0.73. The negative sign indicates that fuel consumption isreduced. Based on the pre-study results, it can be determined that this assumptionis an overestimation; the steeper the slope is, the less fuel savings are obtained, seeSection 4.5 and 4.6.

Comparing the results in table 7.1, most of the large differences in fuel savingscan be explained. The table shows that the road Linköping-Jönköping consists lessthan third of the interesting slopes as Södertälje-Norrköping. Therefore, EcoRollcan be less utilized when traveling from Jönköping to Linköping. However, theresults of Södertälje-Norrköping show that fuel savings are not only obtained bythe inclinations of αER ≤ α ≤ αCP , despite the fuel savings from these inclinationsare over estimation. This, due to several reasons. Firstly, the strategies utilize evenother inclinations. Also, the portion of inclinations does not consider the position ofa specific inclination. Depending on whether an inclination is located after a moreor less positive or negative inclination, the speed of the HDV can have differentspeed, and thus different amount of fuel may be saved.

7.2 The Impact of the Nonlinear Fuel MapThe fuel map of an ICE, see Figure 3.3, is usually nonlinear. Hence, some operatingpoints are less efficient than others. This means that it is better to avoid driving insome specific speeds [4]. Thus, if 80 km/h is one of the inefficient operating pointsfor the studied ICE, the results would be misleading. This, since other ICEs that donot have the same inefficient operating point will get less benefit of EcoRoll.

The fuel map depends on the angular velocity of the engine and delivered torque.Therefore a linearization would be according to

qfinst= c1TICE + c2ωICE + c3, (7.1)

where c1, c2 and c3 are coefficients determined by using least square method. How-ever, since the fuel map matrix that is used gives the fuel consumption in mass pertime instead of mass per cycle, a cross term between the torque and angular speedshould be regarded. Hence, following linearization model is used:

qfinst= c1TICE + c2ωICE + c3TICEωICE + c4, (7.2)

where the coefficients are determined by least square method. However, the operat-ing points between an open and closed powertrain are not close to each other. Forthis application, it is important that the linearization is good enough close to ωidle.Therefore, a higher cost were given to these points when using least square method.

Figure 7.2 shows a part of a simulation on the road Södertälje to Norrköpingusing the conventional EcoRoll. The graphs correspond to the fuel consumption,where the dashed one is determined by the linearized function, and the solid oneby the fuel map matrix. From the total results, that are presented in Table 7.2,it can be concluded that approximately 0.9% fuel savings correspond to the ICE

49

CHAPTER 7. THE SOURCES OF SAVING POTENTIAL

nonlinearity, which may vary from an engine to another. The impact of variedengine displacements with different characteristics are studied in the next chapter.

Table 7.2: A study of how much impact the nonlinearity of fuel map have on theresults.

Södertälje-NorrköpingFuel map Cost Time FuelLinearized -3.2471% -0.2943% -2.5423%Original -4.2648% -0.2943% -3.4164%

0 100 200 300 400 500 600 700 8000

0.2

0.4

0.6

0.8

1

time [s]

fuel consum

ption [%

]

Comparison between original and Linearized Fuel Map

linearized

original

Figure 7.2: A comparison between linearized and original fuel map. It can be seenfrom the graph that the linearized fuel map do correspond well to the original fuelmap, with some over and under estimation on extreme values.

50

Chapter 8

Sensitivity Analyses

Sensitivity analyses are done in order to understand how much the results can varyfor different disturbances in environmental forces or different vehicle preferences,such as different engine or transmission ratios.

These analyses are first presented for the conventional EcoRoll, and then for theEcoRoll that utilizes Look-Ahead data. However, the simulation results obtainedin Chapter 5 and 6, showed large differences in fuel saving potential, between driv-ing from Södertälje to Norrköping and from Linköping to Jönköping. Therefore,the sensitivity analyses are done for both roads, but with focus on the reference,Södertälje-Norrköping.

8.1 Sensitivity Analyses of the Conventional EcoRoll

The results of the conventional EcoRoll when traveling from Södertälje to Nor-rköping were amazing. However, it cannot be claimed that this strategy reducesthe fuel consumption about 3.4%. This, since the results varied a lot between twodifferent highways. This section will therefore study the sensitivity of different mod-eling and disturbances. This is concluded with a presentation of the best and worstresults in order to see how much the result of fuel reduction may vary.

8.1.1 Different Piston Displacements

It was shown in Section 7.2 that approximately 0.9% out of 3.4% fuel savings cor-respond to engine characteristics. Another aspect is to study other engines withdifferent piston displacements; 9, 13, and 16 liters. Previous simulations have beenbased on the 13 liters engine. Simulations of the other engines gives the results inTable 8.1. From the results, it seems that the characteristics of the engines givequite similar final results regarding the topography of Södertälje-Norrköping. How-ever, Linköping-Jönköping gives different result when using the 9 liters ICE. Thiscan have several reasons. One reason could be that different engine capacities letsthe HDV manage to climb an uphill with different final speed, giving different cir-

51

CHAPTER 8. SENSITIVITY ANALYSES

cumstances for EcoRoll. Another reason could be the characteristic of the engine’sfuel map.

Table 8.1: Sensitivity analysis of the results comparing different piston displace-ments, using conventional EcoRoll.

Södertälje-Norrköping Linköping-JönköpingPist. displ. Cost Time Fuel Cost Time Fuel

9 liters -4.0359% -0.2443% -3.2535% -1.1804% -0.0827% -0.9329%13 liters -4.2648% -0.2943% -3.4164% -0.8622% -0.1572% -0.6157%16 liters -4.2336% -0.2702% -3.4061% -0.9052% -0.1711% -0.6424%

8.1.2 Rolling Resistance

As described in Section 3.1.1, the rolling resistance can be modeled in several ways.In this chapter, two different models are studied; (3.4) and (3.5).

A typical value of the coefficient Cr in (3.5) of a HDV on dry asphalt is between0.006 and 0.01 [10]. Simulating with both extreme values gives the results shown inTable 8.2. The table includes also a comparison to the results when Michelin’s modelwere used. It can be seen that Michelin’s model gives the best results regardingreduction of fuel consumption. However, this does not mean that this model isclosest to reality.

Table 8.2: Sensitivity analysis of the results to different rolling resistance models,using conventional EcoRoll.

Södertälje-Norrköping Linköping-JönköpingModel Cr Cost Time Fuel Cost Time FuelMichelin - -4.2648% -0.2943% -3.4164% -0.8622% -0.1572% -0.6157%Other 0.006 -3.7246% -0.2465% -2.9842% -0.7178% -0.1923% -0.4712%Other 0.01 -1.9015% -0.1993% -1.4625% -0.5121% -0.1286% -0.3417%

There are two explanations of the differences in the results. Firstly, differentresistance forces give another ideal inclination αER, see (4.2). This gives the consis-tency of the beneficial working area for EcoRoll being moved, see the vertical linesin Figure 7.1. Therefore, other hills with different inclinations and lengths will beutilized. For a specific road, these hills can be more or less existing.

Another explanation is that the model according to (3.5) is dependent on incli-nation rather than speed, which gives different resistance behavior. Therefore, thedecisions from the controller varies.

52

8.1. SENSITIVITY ANALYSES OF THE CONVENTIONAL ECOROLL

8.1.3 Air ResistanceThe air resistance is modeled by (3.3). In previous simulations, the air speed vairwas neglected. However, there is usually tailwind or headwind. Figure 8.1 presentsthe results for different air velocities.

−25 −20 −15 −10 −5 0 5 10 15 20 25−7

−6

−5

−4

−3

−2

−1

0

vair

[m/s]

Savin

g [%

]

The Impact of Air Speed on Södertälje−Norrköping

Cost

Time

Fuel

(a) The impact of air velocity when traveling from Södertälje to Norrköping.

−25 −20 −15 −10 −5 0 5 10 15 20 25−4

−3.5

−3

−2.5

−2

−1.5

−1

−0.5

0

vair

[m/s]

Savin

g [%

]

The Impact of Air Speed on Linköping−Jönköping

Cost

Time

Fuel

(b) The impact of air velocity when traveling from Linköping to Jönköping.

Figure 8.1: The impact of different air velocities on the results of the conventionalEcoRoll.

From Figure 8.1, it can be concluded that the results varies to different airresistances. Still, it is stable even to a headwind of 25 m/s, which unfortunately isclassified as storm [12]. However, as could be expected, a tailwind is favorable forEcoRoll.

8.1.4 Mass EstimationThe simulations show stability of the conventional EcoRoll strategy even regardingvehicle mass estimation error, Mε, by ±50%. The simulation is done by keepingvehicle mass to 40 tonnes, and change the signal into the control strategy. Theresults are shown in Table 8.3.

The controller is robust regarding Mε, since it affects only the term of gravita-tional force when estimating the acceleration for an open powertrain. The gravi-

53


Table 8.3: Sensitivity analysis of mass estimation error, using conventional EcoRoll.

Road Mε Cost Time Fuel


-50% -3.9665% -0.3506% -3.1207%-25% -4.1380% -0.3261% -3.2852%0% -4.2648% -0.2943% -3.4164%25% -4.2716% -0.2166% -3.4758%50% -4.2325% -0.2204% -3.4395%


-50% -0.8069% -0.1713% -0.5599%-25% -0.8683% -0.1784% -0.6066%0% -0.8622% -0.1572% -0.6157%25% -0.8275% -0.0353% -0.6683%50% -0.8296% -0.0007% -0.6933%

tational force (3.2) is proportional to sinus the inclination, and hence the resultingerror in estimated acceleration is small for the small inclination deviations of theroads.

An observation that is more visible in the results for Södertälje-Norrköping,is that the time savings decrease while the fuel savings increase with increasedoverestimation of the mass. This is due to the controller that accepts even smallerslopes to activate EcoRoll. Thereby, more fuel efficiency will be achieved but witha lower acceleration, resulting in longer travel time. However, this is the case up toa limit, letting the total cost be most profitable around correct mass estimation.

8.1.5 CC and DHSC Set Speeds

EcoRoll opens the powertrain when a positive acceleration is estimated. Hence, itutilizes the difference between the CC and DHSC set speeds. A large difference givesmore operating points. Until now, the difference has been 10 km/h. This is reducedto 5 km/h here to study the impact of it. It is done by reducing the DHSC setspeed, as a change in CC set speed would affect the resistances, and therefore givesirrelevant results.

Table 8.4: Sensitivity analysis of the results to different DHSC set speeds, usingconventional EcoRoll.

Södertälje-Norrköping Linköping-JönköpingvCCset vDHSCset Cost Time Fuel Cost Time Fuel80 km/h 85 km/h -3.2757% -0.0450% -2.7372% -0.5960% -0.0422% -0.4696%80 km/h 90 km/h -4.2648% -0.2943% -3.4164% -0.8622% -0.1572% -0.6157%

54

8.2. SENSITIVITY ANALYSES OF LOOK-AHEAD ECOROLL

Table 8.4 shows expected results. When the difference between the CC and DHSCset speeds decreases, the working area of EcoRoll decreases. Thereby, the obtainedresults are worse.

8.1.6 Best Case vs. Worst Case

The aim of comparing the best case with worst case scenario is to get knowledge ofthe amount in result variation. The cases are chosen based on the previous sensi-tivity analyses. The road Linköping-Jönköping gave worse results than Södertälje-Norrköping in general. Therefore, the worst case scenario is based on the preferencesof worst cost results corresponding to Linköping-Jönköping, and in the same wayfor the best case. The combination is presented in Table 8.5. Simulating these twocombinations gives the results presented in Table 8.6. The results do not excludethat other results can be reached outside these boundaries due to other disturbancesand combinations. However, the results indicates a large variation. The results arethough extreme; not often a HDV runs with a headwind classified as storm.

Table 8.5: The combinations of preferences for the best and worst case respectively.

Best case Worst caseSödertälje-Norrköping Linköping-Jönköping

13 liters ICE 13 liters ICEMichelin’s model The model (3.5) with Cr = 0.01vair = 25m/s vair = −25m/sMε = 25% Mε = −50%

vDHSCset = 90km/h vDHSCset = 85km/h

Table 8.6: The result of the comparison of best and worst case scenario, usingconventional EcoRoll.

Case scenario Cost Time FuelBest -6.8324% -0.5996% -5.4432%Worst 0.1155% 0.3896% -0.1642%

8.2 Sensitivity Analyses of Look-Ahead EcoRoll

The sensitivity analyses of the conventional EcoRoll were more or less stable, andthe aim here is to do the same study for the Look-Ahead EcoRoll.

55


8.2.1 Different Piston DisplacementsSeveral HDVs with different piston displacements were studied in Section 8.1.1. Sim-ilar study is done here, using the same ICEs but for the Look-Ahead EcoRoll. Fromthe results presented in Table 8.7, the same conclusions can be made. The to-pography Södertälje-Norrköping does not show large differences. The study onLinköping-Jönköping, on the other hand, showed larger differences that cannot beexplained explicitly. However, as mentioned in Section 8.1.1, the reasons couldbe that the engines have different characteristics of the fuel map and the differentcapacities changes the circumstances for EcoRoll.

Table 8.7: Sensitivity analysis of the results to different piston displacements, usingLook-Ahead EcoRoll.

Södertälje-Norrköping Linköping-JönköpingPist. displ. Cost Time Fuel Cost Time Fuel

9 liters -4.0424% -0.2449% -3.2587% -1.5127% 0.0035% -1.2710%13 liters -4.5648% -0.1972% -3.7427% -1.0264% -0.0468% -0.8276%16 liters -4.7520% -0.1089% -3.9661% -1.1479% -0.0980% -0.8953%

8.2.2 Rolling ResistanceThe same conclusion can be obtained from the results in Table 8.8 as for corre-sponding results for the Conventional EcoRoll in Table 8.2. Michelin’s model givesless resistance and enables the HDV to roll easier, letting EcoRoll be utilized moreoften. Thus, the results are better when using Michelin’s model, regardless of thereal rolling resistance. Yet, all models that are used indicate the benefit of EcoRoll.

Table 8.8: Sensitivity analysis of the results to different rolling resistance models,using Look-Ahead EcoRoll.

Södertälje-Norrköping Linköping-JönköpingModel Cr Cost Time Fuel Cost Time FuelMichelin - -4.5648% -0.1972% -3.7427% -1.0264% -0.0468% -0.8276%Other 0.006 -4.0168% -0.1280% -3.3171% -0.9069% -0.1279% -0.6728%Other 0.01 -1.7569% -0.0158% -1.4643% -0.6529% 0.2143% -0.6895%

8.2.3 Air ResistanceThe behavior of the results when varying the air velocity while using Look-AheadEcoRoll, is similar to the behavior of the conventional EcoRoll, see Figure 8.2.

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The more tailwind, the greater the fuel savings. However, the travel time is longerhere even for tailwind, which is more visible for the road Linköping-Jönköping, seeFigure 8.2b. The travel time is increased more since Look-Ahead EcoRoll does notopen the powertrain in a hill where it is predicted that the DHSC set speed will bereached. This increases the travel time, but saves more fuel.

−25 −20 −15 −10 −5 0 5 10 15 20 25−7

−6

−5

−4

−3

−2

−1

0

vair

[m/s]

Savin

g [%

]

The Impact of Air Speed on Södertälje−Norrköping

Cost

Time

Fuel

(a) The impact of air velocity when traveling from Södertälje to Norrköping.

−25 −20 −15 −10 −5 0 5 10 15 20 25−7

−6

−5

−4

−3

−2

−1

0

1

vair

[m/s]

Savin

g [%

]

The Impact of Air Speed on Linköping−Jönköping

Cost

Time

Fuel

(b) The impact of air velocity when traveling from Linköping to Jönköping.

Figure 8.2: The impact of different air velocities on the results of Look-AheadEcoRoll.

8.2.4 Mass EstimationIt was concluded from the mass estimation analysis of conventional EcoRoll, thatan overestimation of mass gave more fuel savings up to a limit where the behaviourturns, see Table 8.3. This, since the controller would open the powertrain even forless steep slopes. The case is the same here, as can be seen in Table 8.9.

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Table 8.9: Sensitivity analysis of mass estimation error, using Look-Ahead EcoRoll.

Road Mε Cost Time Fuel


-50% -2.0778% 2.0940% -3.1931%-25% -3.9204% 0.0925% -3.3860%0% -4.5648% -0.1972% -3.7427%25% -4.6944% -0.0576% -3.9517%50% -4.6579% -0.0595% -3.9187%


-50% -0.6156% 0.1440% -0.6109%-25% -0.9322% -0.0150% -0.7698%0% -1.0264% -0.0468% -0.8276%25% -1.1023% 0.0609% -0.9638%50% -1.8430% -0.2067% -1.4081%

8.2.5 CC and DHSC Set Speeds

Table 8.10 compares the results of when the DHSC set speed is 85 km/h and 90km/h. The results corresponding to the road Södertälje-Norrköping is as expected;a DHSC set speed of 90 km/h gives better results. Furthermore, the case is the samefor Linköping-Jönköping, regarding the cost. However, the relative fuel savings areless for the higher DHSC set speed. The explanation is that there are two hills onthis road, where the maximum speed that can be reached is between 85 km/h and90 km/h when brakes are not used, see Figure 8.3. This lets Look-Ahead EcoRollopen the powertrain for the higher DHSC set speed but not for the lower. However,this does not mean that it is more fuel efficient not to increase the DHSC set speed,since the presented results are relative to a reference vehicle and thus not absolutevalues. The reference vehicle has the same preferences even regarding the DHSC setspeed, but equipped with a conventional CC without EcoRoll.

Table 8.10: Sensitivity analysis of the results to different DHSC set speeds, usingLook-Ahead EcoRoll.

Södertälje-Norrköping Linköping-JönköpingvCCset vDHSCset Cost Time Fuel Cost Time Fuel80 km/h 85 km/h -3.4670% 0.3095% -3.1453% -0.9665% 0.1593% -0.9159%80 km/h 90 km/h -4.5648% -0.1972% -3.7427% -1.0264% -0.0468% -0.8276%

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1.12 1.14 1.16 1.18 1.2 1.22 1.24 1.26

x 105

75

80

85

90

distance [m]

speed [km

/h]

vCC

set

vDHSC

set

HDV with EcoRoll

HDV with CC

1.12 1.14 1.16 1.18 1.2 1.22 1.24 1.26

x 105

80

100

120

140

distance [m]

altitude [m

]

1.12 1.14 1.16 1.18 1.2 1.22 1.24 1.26

x 105

0

0.5

1

distance [m]

contr

ol sig

nal

(a)

1.12 1.14 1.16 1.18 1.2 1.22 1.24 1.26

x 105

70

80

90

distance [m]

speed [km

/h]

vCC

set

vDHSC

set

HDV with EcoRoll

HDV with CC

1.12 1.14 1.16 1.18 1.2 1.22 1.24 1.26

x 105

80

100

120

140

distance [m]

altitude [m

]

1.12 1.14 1.16 1.18 1.2 1.22 1.24 1.26

x 105

0

0.5

1

distance [m]

contr

ol sig

nal

(b)

Figure 8.3: Hills with a length and inclination that gives an increased speed above85 km/h but below 90 km/h.

8.2.6 Best Case vs. Worst Case

The combinations of the preferences for the best and worst case scenario are de-termined in the same way as in Section 8.1.6. The combinations corresponding toLook-Ahead EcoRoll is presented in Table 8.11 and the results of the simulations

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in Table 8.12. The results give the same conclusion; large variation can be obtainedfor different disturbances. However, the risk of having all these worse preferences islow.

The worst case gave here even an increase of fuel consumption and travel time.This is of course possible, since the disturbances are large. The headwind is strong,and the mass estimation is wrong letting the controller take wrong decisions.

Table 8.11: The combinations of preferences for the best and worst case respectively.

Best case Worst caseSödertälje-Norrköping Linköping-Jönköping

16 liters ICE 13 liters ICEMichelin’s model The model (3.5) with Cr = 0.01vair = 20m/s vair = −25m/sMε = 25% Mε = −50%

vDHSCset = 90km/h vDHSCset = 85km/h

Table 8.12: The result of the comparison of best and worst case scenario, usingLook-Ahead EcoRoll.

Case scenario Cost Time FuelBest -7.3838% -0.5581% -5.9597%Worst 0.2511% 0.0305% 0.1887%

8.3 Validation in a HDVA truck was driven from Södertälje to Tystberga with same preferences as used inthe simulations, see Table A.1, except the mass was 14 tonnes instead of 40 tonnes.The route was driven twice; first by using the conventional CC, and then by request-ing disengaged gear when it seemed beneficial. Tystberga is approximately 42.8 kmfrom Södertälje, and placed in the same direction as to Norrköping. Therefore, asimulation is done for the same route with a 14 tonnes HDV to compare it withlogged data, see Table 8.13.

The logged data and results from the simulations, both indicate that EcoRoll isfuel efficient. The logged data gave even better results than simulations, regardingfuel savings and total cost. The increased travel time is because it is difficult to esti-mate the acceleration obtained for open powertrain by eyes. However, results fromthe logged data should only be seen as an indication. This, since many disturbancefactors may affect the results, e.g., the air resistance. In order to get same behav-ior between the reference and EcoRoll drive cycle, two identical vehicles should be

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8.3. VALIDATION IN A HDV

Table 8.13: Comparing results between simulations and logged data when drivingfrom Södertälje to Tystberga.

Model Cost Time FuelLogged data -1.6971% 1.4130% -2.3915%

Conventional EcoRoll -0.9700% -0.0290% -0.7921%Look-Ahead EcoRoll -1.1433% -0.0023% -0.9558%

driven in parallel, beside each other to get same air resistance. Furthermore, bothdrivers should act in the same way, which is almost impossible. A solution is todrive same route several times, in order to get more data to analyze. However,this is sufficient for the purpose of this study, indicating that the results from thesimulation are reliable.

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Chapter 9

Discussion

EcoRoll is a fuel efficient way of traveling down a hill. By using Look-Ahead data,the speed of the HDV can be predicted and the controller improved. This was donesince it was proven that it is more beneficial to have the powertrain closed in a steepand long slope, where the length is unknown unless Look-Ahead data is available.Look-Ahead EcoRoll was developed in Chapter 6, where it is mentioned that thecontroller will still be based on rules in order to be able to compare the controllers.However, from the sensitivity analysis in Chapter 8, it can be seen that in somespecific cases the conventional EcoRoll gave more profitable cost than the strategyof Look-Ahead EcoRoll (e.g., for negative mass estimation error, see Table 8.3 and8.9). This indicates that the strategy of Look-Ahead EcoRoll can be improved evenfurther, even though it has had better results in general.

A suggestion of improvement of Look-Ahead EcoRoll is to base the decisions ona cost function rather than rules. Based on the speed prediction and known enginecharacteristics, the cost function can be determined. However, this requires a moreaccurate speed prediction, since the used strategy filters small speed deviations bywaiting for an overspeed, see Section 6.1.1. This filter lets small hills not beingutilized have a negative impact on the results.

The speed prediction can also be improved by adding an adaptation of thedriving resistance. This lets the controller become less sensitive to disturbances.

As mentioned before in the background, Chapter 2, it could be more benefi-cial to turn off the engine when opening the powertrain. This enables the higheracceleration of an open powertrain without the need to feed fuel to the engine. How-ever, this requires that several systems that are powered by the engine to becomeelectronically powered. Regarding that the fuel savings were 73% on an ideal sloperesulted in approximately 3.4% saving on Södertälje-Norrköping, the additional fuelsavings (27% on an ideal slope) due to a turned off engine are small. This shouldbe compared to the additional costs of changed systems, such as the power steering.Also, considering that more fuel is fed each time the engine is turned on again, giveseven smaller improvements.

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CHAPTER 9. DISCUSSION

9.1 ConclusionAmazing results are obtained from EcoRoll, regardless of Look-Ahead data beingutilized or not. Even though the differences were not significant, Look-Ahead Eco-Roll is to prefer. This, since it enables larger possibility to be improved, not onlyregarding fuel reduction, but also driving performance.

9.2 Future WorkDespite the amazing results, there are much that can be improved and studiedfurther in this field. Among these studies is to implement the developed strategiesinto a vehicle to get a feeling of their driving performance, and also to validate theobtained results of the fuel savings.

A deeper study of Look-Ahead EcoRoll using a cost function to decide whetherto open the powertrain or not should also be done, since it could enable further fuelreduction and even better driving performance. Also, the speed prediction could beimproved by, e.g., adding an adaptation of the driving resistance. This is especiallyimportant for the implementation of the controllers.

Last but not least, the impact of turning the engine off while the powertrainis open could be studied. Also, comparing different ways of turning the engine onagain; by the conventional starter motor, a larger starter motor that reduces fuelconsumption or start the engine only by closing the powertrain and let the motionof the HDV power with force to turn the engine on.

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Bibliography

[1] Drivers at Scania Transportlab AB about experience of EcoRoll. PersonalCommunication, 2011.

[2] Rudberg Arvid. Optimization Based Control Strategy for Energy EfficientDecelerations in an Automobile Cruise Controller. Master’s thesis, Departmentof Automatic Control, Lund University, Sweden, August 2010.

[3] Peter Asplund. Personal Communication, 2011.

[4] Martin Evaldsson. Optimal styrning av ett tungt fordon med hänsyn till vägto-pografi, motorkaraktäristik och körupplevelse. Master’s thesis, Royal Instituteof Technology, August 2010.

[5] Anders Fröberg. Efficient Simulation and Optimal Control for Vehicle Propul-sion. PhD thesis, Linköping University, May 2008.

[6] Magnus Gamberg. Mätning av däcktemperaturer för verifiering av ny rullmot-ståndsmodell. Master’s thesis, Royal Institute of Technology, May 2003.

[7] R P G HEATH. Seamless AMT offers efficient alternative to CVT, 2007.

[8] Anders Jensen. Scania LowRev vs. Volvo EcoRoll, March 2010.

[9] MathWorks. Simulink - Simulation and Model-Based Design. Available from:http://www.mathworks.com/products/simulink/ [cited May, 2011].

[10] Lars Nielsen and Lars Eriksson. Vehicular Systems. Linköping Institute ofTechnology, 2004.

[11] Fredrik Roos. Design and theoretical evaluation of electric power steering inheavy vehicles, 2005.

[12] SMHI. Skalor för vindhastighet, November 2008. Available from: http://www.smhi.se/kunskapsbanken/meteorologi/skalor-for-vindhastighet-1.252 [cited May, 2011].

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Appendix A

Parameter Values

Table A.1: The parameters of the studied HDV.

Symbol ValueAv 10 m2

CaF 5.64 ∗ 10−8 s2/m2

Cb 0.58 ∗ 10−5 s/m

Cd 0.6CrrisoF 5.36 ∗ 10−3

g 8.92 m/s2

Mv 40 tonnes

nr 2ncyl 6rw 0.501 m

vISO 80 km/h

ρair 1.29 kg/s2

Table A.2: The parameters for the strategy of EcoRoll.

Symbol ValuevDHSCset 90 km/h

vDHSCmargin 2 km/h

vCCset 80 km/h

vCCmargin 2 km/h

decmax -0.07 m/s2

tchangemin5 s

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