Model-Based Design and Future Calibration...

1Workshop on Open Problems and Challenges in Automotive Control – April 2006

Model-Based Design and

Future Calibration Processesat Toyota

Akira OhataMasato EharaSatoru Watanabe Ken ButtsToyota Motor Corporation Toyota Technical Center


Contents1. Introduction

2. Current Situation

3. Concurrent Development

4. Directions for Calibration Productivity Improvement

5. Current Work

6. Cooperation within the engineering community

7. Conclusions


1.Introduction

Increasing Engine Control Variables

Calibration process improvement is an urgent issue => establish a competitive engine control system development environment !

Power Train Requirements are becoming increasingly strict.Fuel EconomyCleaner Exhaust Gas EmissionsPerformance

Pressures for Calibration Process Improvement


1. Introduction

Various Marketsand

Vehicles

Calibration Process and Methodology Improvementsshould consider the Whole Engine Development Process

Development ProcessAdvanced Production

Mass Development

Leadoff Development

Leadoff Development and Mass Development

Small Modifications


2. Current SituationTarget Quality is achieved through Iterative work.

MakingPrototype

Calibration,Validation,Evaluation

DesignModification

SoftwareHardware

Quality

END

TargetQuality

Development Process

Current Process

Improved Process

=> Concurrent Development would reduce Iterative Work


3. Concurrent Development3.1 Concept of Concurrent Development

3.2 Model Based Development

3.3 Rapid Modeling

3.4 Relationship between Modeling and Calibration


3.1 Concept of Concurrent Development system design

System Validation&Calibration

Requirements and constraints analysis

Engine hardware and control software development should proceed synchronously In Concurrent Development

Softwaremodules

Control SoftwareV-process

Validation

Verification

Requirements andconstraints analysiscontroller

Control design

embedded code development

Software Specification

Combination

Software module

Hardwareparts

Combination

Partitioning parts

Hardware design

Hardware V-process

Validation

VerificationParts drawing

System hardwareRequirements andconstraints analysis

Parts

combination

Engine System


3.2 Model Based Development

controllersoftware hardware

validation

engine hardwareengine actuators sensors

engine model

validation

combine

combine

controller model

Specification of functionalhardware requirements

Specification of functionalsoftware requirements

Rapid Proto ECU

SILS

HILS

Actual Testing

Virtual World

Real World

The fundamental idea of MBD is to use engine and control software models as executable specifications in co-simulation of hardware and software.

=>The key to MBD is Rapid Modeling.


Completion of Prototype Engine

Parts

3.3 Rapid ModelingM

odel

Acc

urac

yIncremental Modeling

Model Accuracy improves rapidly during development.

Development Process

Advanced Production

Required Accuracy Achieved Accuracy

Knowledgefrom Measured Data

Knowledge from Physical Modeland Existing Engines


3.4 The Relationship between Modeling and Calibration

Controllers are derived from models.The model parameters are put into the tracking controller with models in the control design.

Pseudo inverse modelreference

Plant

Model with time delay

Controlled variableC1

+ -

+

-

-

+C2Model

without time delay

Pseudo inverse modelreference

Plant

Model with time delay

Controlled variableC1

+ -

+

-

-

+C2Model

without time delay

Example of Tracking Controller


Improvement of calibration productivity meansimprovement of model identification productivity.

3.4 The Relationship between Model and Calibration

Model parameters in the tracking controllers are determined through model identification with data obtainedby time consuming calibration experiments.


Summary of Concurrent Development 1. We expect „Concurrent Development“ to reduce iterative work.

2. We are promoting „Model Based Development (MBD)“ in order to achieve high productivity and quality in Concurrent Development.

3.A key to Model Based Development is „Rapid Modeling“.In relation to „Rapid Modeling“,we have the concept of „Incremental Modeling“ wherein the model accuracy increases as development progresses.

4. Calibration productivity improvement corresponds to model identification produtivity improvement.

=> In the following, we change the focus toCalibration Productivity Improvement.


4. Directions for Calibration Productivity Improvement

4.1 Structured Calibration Process

4.2 Automation

4.3 Methodology


4.1 Structured Calibration Process

Development ProcessAdvanced Production

Mass DevelopmentLeadoff Development Prio

rity

in

Cal

ibra

tion

Speed Quality

Completion of Prototype Engine

Knowledge from Physical Modeland Existing Engines

Knowledgefrom Measured Data

Parts

Cal

ibra

tion

Qua

lity

Target Quality Level

„ Incremental Calibration “Calibration quality is accumulated throughout the engine development process


4.1 Structured Calibration ProcessA well-defined calibration process helps to assure quality when

distributed engineers develop a great variety of products for world-wide markets.

end

Inputs• Predetermined data• Experimental data

Outputs• Calibration Result• Intermediate data

Transformation

Evaluation criteriaTest condition Procedure

start

ProcedurePre det. Calib.Exp. Inter.


ProcedureCalib.

Exp. Inter.




ProcedurePre det. Calib.Exp.


ReplacementModular


4.2 Automation

Auto-Cal PC

Data Acquisition

Dynamometer Engine

Gas-Analyzer etc.Combustion Analyzer

Rapid-proto ECU

Database

1. Automated-calibration needs well defined procedures.2. The system should be flexible and user-friendly to prepare timely

auto-calibration applications for various engines at various stages of development.

3. Auto-adjustments for Knock, Engine Roughness,and Temperature Limits are also important.


4.3 Methodology

4.3.1 Model Based Calibration (Statistical & Physical Models)

4.3.2 Rapid Measurement


4.3.1 Model Based Calibration (MBC)

-Basic Concepts of MBC

-Examples of Approximation Methods

-Use of Physical Models in MBC

-Interface between Physical Models and Statistical Models

-Example of Model Compensation by Error Function


4.3.1 Model Based Calibration

Actuator2

Actuator1

BS

FC

OptimizationDoEAutomated Data

Measurement Modeling&Evaluation

Engine Speed

Load

VVT Map

Target A/F Map

Spark Timing Map

Basic Concept of MBC:To represent the experimental data by simulations provided by anapproximated function.

Model Based Calibration can be expanded beyond steady state calibration to transient and driveability calibration.

Expansion of MBC Application:

Basic Concept of MBC

Integration of MBC and long term accumulated knowledge is important.


4.3.1 Model Based CalibrationExamples of Approximation Methods

(a)Taylor Series

(b)Basis Functions (ex.Radial Basis Function)( ) ( ) ( ) ( )XfwXfwXfwXf nn+++≅ �2211

( ) ( )( ) ( ) ( ) �+−∂∂+≅

=00

0

,, XXXf

XfpkukxfXX

( ) ( )[ ]ttt kukxX ,=

nww ,,1 � ( )Xff n,,1 �:coefficients :basis functions

( ) ( ) ( )( )pkukxfkx ,,1 =+

: the states of the system

( ) ( )kxCky =

xk

: the observed variable x

)( nRx∈ u )( mRu ∈p )( lRp∈ f uC )( npRC ×∈ y )( pRy∈

: Sampling Number: the input of the system

: the parameters of the model : a function of: a constant matrix

and

Engine models can be expressed by the following discretized equation.


4.3.1 Model Based CalibrationApplication of Physical Models in MBC

ApproximatedModels

Models Consistent with Experimental Data

Target Models

PhysicalModels

StatisticalModels

Physical Models: Models which satisfy Conservation Laws.=>Too Strict Constraint for Practical Use

Practical Approach: Integration of Physical and Statistical Models

Target Models : Simpler, Approximated Models around Pure Physical Models.


4.3.1 Model Based CalibrationInterface between Physical Models and Statistical Models

( ) ( ) ( ) ( )XfwXfwXfwXp nn+++= �2211

(a) Physical model would become more accurate if parameters P changeas a function of X.

(b) Introduction of Error Functions between Measured Data and Simulation Models

( )XfXfXerr simmeas −= )()(

( )XfXf

Xerrsim

meas )()( =

( ) ( )[ ]ttt kukxX ,=p :Parameters of a Physical Model

nww ,,1 � ( )Xff n,,1 �:coefficients :basis functions: the states of the systemx )( nRx∈ u )( mRu ∈: the input of the system

k : Sampling Number

( ) ( ) ( )( )pkukxfkx ,,1 =+ ( ) ( )kxCky =,


4.3.1 Model Based Calibration

Physical Model

ReducedExperimental Data Compensated

Model

INPUT x

OU

TPU

T

y

If the error function is simple, the Compensated Model forthe engine can be obtained by a small number of test data.

Example of Model Compensation by Error Function

Error Function

( )XfXfXerr simmeas −= )()(



-Concept of „ Rapid Measurement “

-Required New Technology for Rapid Measurement


Measurement Time for Each Data Point 1/20 (5min=>15sec)

„To Reduce Measurement Time for Each Data Point“

=

MBC

Total Measurement Time1/200x

Rapid Measurement

New Methodology is Required.Challenging Theme

"This is a worthwhile challenge !"

Number of Data Points

1/10

Might be effectively combined with Incremental Calibration.

4.3.2 Rapid MeasurementConcept of „ Rapid Measurement “



(1)Stable Values Estimation for Slow Response Variables from the Short Period Measurement Data.

y(k) OUTPUT

u(k) INPUT

y(�)

(2)Improvement of Measurement Stability

Required New Technology for Rapid Measurement

Stable

Estimation

Time

Instrumentation Response Fluid Temperature Control etc.


5.Current Work at Toyota

-Calibration Process

-Examples of Model-Based & Automated Calibration


5.Current Work at ToyotaCalibration Process

Toyota’s current calibration process is highly dependent on personal skills.

1. Creating structured, modular, and documented calibration process.2. Trying new software infrastructure to manage the procedures,

process, test data, and calibration results .

start


Procedure Pre det. Calib.Exp. Inter.

ProcedureCalib.

Exp. Inter.




ProcedurePre det. Calib.Exp.

End

Structured Calibration Process.


5.Current Work at ToyotaExamples of Model-Based & Automated Calibration

1. Base (Steady-state control) mapping

2. Cylinder air-charge estimation

3. Fuel wall-wetting

4. Emission cold-start and drive-away (with refinement on the vehicle chassis-roll)

[Note]Test-bench fluid conditioning has a significant influence on test-bench measurement speed and accuracy or repeatability.=>Performance of testing facilities is also important for MBC.


6.Cooperation of Engineering Community

Sharing fundamental knowledge of process and methodology will be more and more encouraged.

The globalization and the commonization of calibration process and methodology form a strong industry direction.

The development of an automated calibration process requiresthe cooperation of various technical fields


7.ConclusionsFuture Directions to Improve Calibration Process Productivity

1. Improvement of calibration processes is an urgent issue to managethe increasing calibration complexity presented by modern engine actuation control systems.

2. The concept of„Calibration Process Linked with Engine Development Process“is introduced.

„Incremental Modeling“and „Incremental Calibration“ to Achieve„Model Based Development “and „Concurrent Development“

3. Integration of physical model, statistical model and long term accumulated knowledge will be key to productivity improvement.

4. The cooperation of the engineering community is desirable.

Model-Based Design and Future Calibration...

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