Deployment of Model Based Design for Engine Control at Renault

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CIMdata Renault 9 April 2014

CIMdataDeployment of Model Based Design for Engine Control at Renault

Dr Vincent TALON

[email protected]

CIMdata Renault 9 April 2014Deployment of Model Based Design, for Engine Control at Renault 2

0102 The best answer : System Engineering

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Our process, our customers à our added values

Technical point of view : model typology

Examples of success stories

Target, constraints and added value à customers

06 Conclusion

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END

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2


Car manufacturers are initially faced to :

Constraints / Objectives


What are the constraints ? Constraints / Objectives

3


Major value chain shifts until 2030 Constraints / Objectives


Increasing regulation pressure Constraints / Objectives

4


Renault Strategy : CO2 road map Constraints / Objectives


Car manufacturers playgrounds are

Markets

And the Renault strategy is to win the battle…

5


2020 World vision : diversity required by our markets

Markets

Energy and transmission type share


Renault Powertrain Strategy Strategy

6


But to answer to those constraints, objectives and markets we must face a lot of

Variety


Variety

7


Variety

Friction reduction


Variety

8


Powertrain electrification Variety


Finally we must optimize our powertrains for :Ø multiple objectives / playgrounds Ø under multiple constraints

9


Targets

Economical

Environmental

Customer satisfaction

Constraints

Optimization

Added value àcustomer

Variety 1 Variety 2 Variety 3

Variety 4 Variety 5

Variety X


From an engineering point of view, the best way to answer to this high challenge, is the Engineering System linked to 0D System Model

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06 Conclusion

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System Engineering @ Renault

Pow

ertr

ain

entit

y

Con

trol

de

part

men

t

Customers needs

Company needs for their customers

Functional Requirements (performances subjective

description)

Quantified customer requirements

Technical system requirements

Organic system technical definition

Technical system validation

Customer requirements

validation

Global customer requirements

validation (company)

Customers satisfaction feedback

Level 1

Level 2

Level 3&4

Level 5

Level 6&7

Level 8

SystemEngineering

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CIMdata Renault 9 April 2014Deployment of Model Based Design, for Engine Control at Renault

System YSystem X

Customerrequirement

Customer requirement deployed to system

Product target

Technical definition for each variety

Variety 1 Variety N

Level 3

Level 5

Concept choiceHyp macro Technical Definition

Regulation objective: < 68 mg/km NOx WLTC

Tuning objective: < xx mg/km NOx Engine Out

Requirements range : from customer requirements to system

Local customer requirement for each variety

Global engineering for the customer requirement objective

Level 6

Level 7Final tuning objective: < yy mg/km NOx Engine Out

Simplest model (level 0)

0D system model (level 1)

1D system model (level 2)

SystemEngineering

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06 Conclusion

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How we are organized for Model Based Design in Renault Nissan Alliance ?


24

DEA-MAAdvance & strategy

engineering

DEA-MM

Mechanical

DEA-ME

Electric & hybrid

DEA-MCControl / System /

tuning

DEA-MD

Diesel

DEA-MG

Gasoline

DEA-MX

Driveline

Renault / Nissan Engineering World

Engineering Alliance

Platform and Vehicle

Engineering

Mechanical Engineering

Nissan

Projects

Renault

Projects

Engineering Test &

Services

Engineering Research &

Advance Engineering

System Engineering

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Model area

Gasoline & Diesel Combustion

Cooling

After treatment

Battery

Electric motor

Air path

Transmission

Vehicle

Pollutants


Who are our customers ?

Where do we use 0D System Model in the V development cycle ?

14


Identification tools & processes

HIL validation

TUNING

Functional MIL validation• Simulation module or complete

controls

Soft calibrated / validatedRequirements for

customers

Requirements for control• functional / dysfunctional

Architecture choice• Technical definition• Mechanical & soft design requirements

1u

u

yx_e

observateur_de_kalman

K*u

gain LQ 2

K*u

gain LQ 1

K*u

Feedforward

T

z-1

T

z-1Demux

3[N;Qcarb]

2y_mes

1y_ref

Control synthesis• Control & virtual sensors

Our customers

Time to Market

Time to MarketQuality

Quality

Quality

Time to Market

QualityCost

CostTime to Market

Cost


How can the 0D system model contribute to this design challenge ?

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ENGINE : Air path

Usage cases:• Functional / Dysfunctional analysis• Control design and validation (MIL)• HIL verification• Tuning• Drivability requirements

0 10 20 30 40 50 60 70 80 90 1000

200

400

600

800

1000

1200

1400

1600

1800

2000

RCOpap [%]

Sef

f [m

m2 ]

00.2

0.40.6

0.8

0

2000

4000

6000

0.3

0.32

0.34

0.36

0.38

0.4

0.42

Mair [g]

Rendement combustion

N [tr/min]


ENGINE: gasoline and diesel combustion

Mean value High frequency

Two model typologies

Torque / CO2PollutantsIntake air efficiency

Torque / CO2PollutantsIntake air efficiencyCylinder pressure

0 50 100 150 200 250-50

0

50

100

150

200

250

N° point

Cou

ple

Mesure brtMesure indAMESim

0 50 100 150 200 2500

10

20

30

40

50

60

70

80

90

100

N° point

Qai

r [g/

s]

MesureAMESim

0 100 200 300 400 500 6000

5

10

15

Temps [s]

Emiss

ions N

Ox [m

g/s]

NOX instantanné

0 100 200 300 400 500 6000

200

400

600

800

1000

Temps [s]

Cumu

l NOx

[mg]

NOX cumulé

Usage cases:• Functional / Dysfunctional analysis• Control design and validation (MIL)• HIL verification• Tuning• Drivability requirements• Raw pollutants & After treatment requirements

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AFTER TREATEMENT : diesel & gasoline

Air fuel ratioEfficiencyPollutants

Impact of volume, PGM, ratio L/D …

Usage case:• Functional / Dysfunctional analysis• Control design and validation (MIL)• HIL verification• Tuning• Pollutants & After treatment hardware design



TRANSMISSION & HYBRID

Usage case:• Functional / Dysfunctional analysis• Control design and validation (MIL)• HIL verification• Tuning• Drivability requirements• Mechanical design

With ideal actuators for computer simulation time


With real actuator

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Calculation time / implementation complexity

Empirical Model

0D Model

1D Model

Number of tests for identification

Extrapolation ability / functional analysis

Accuracy/ robustness / driving pleasure

Model types

Nota for 1D model:GTpower : 10 % Renault modelsAMESim: 90 % Renault models

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Empirical model

Link between model types

1D model

0D model

Learning process possible

Few tests

Target tests

Lots of tests

Test number for model identification

Mechanical design

Control / Diag / MIL

Tuning / Layout


Engine control specifications

Plant model

Stimuliis

Analysis tools

Our tools

LMS Imagine.Lab Amesim

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How do we develop models and simulators ?


Process for simulation development

New model brick

New simulator

New tool or customer

Deployment of model

based

French University(academic partener)

Sub contractor(LMS / IFPen)

Renault+ sub

contractorRenault

Highlight key points to “Industrial Chair”:

• Duration : 5 years• Global budget : 4.500 k€• Renault : diesel K9K and gasoline H5Ft• Human resources : equivalent of 13 FTE• Test facilities: 1 BHD, 1 BMS , 1 turbo gas

stand, 1 vehicle test (4x4)

Strong partnershipSuppliersRFI and RFQ

*notaBMS : engine test benchBHD : high-dynamic engine test benchFTE : full time equivalent

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5 examples of Model Based success stories performed by Renault engineering.

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1. CUSTOMER REQUIREMENTS : NOx-trap

Output products• volume• ratio length / diameter• % of precious metal (Pt,

Pd, Rh…)

High level requirementà Define the lean NOx-trap system for a specific engine (one variety)

Objective to meet• Euro 6 level (pollutants)• Cost• Engine compartment

volume

Use cases• NEDC / WLTC• Real Drive

Emission (RDE)

Time to Market

Cost


2. CONTROL DESIGN: for air path

Model linearization on multiple points

Control law or observer synthesis

( )

( ) ( ) ( )( )

( ) ( )( )

120

1

col

dmotcolvmot

colavtHEGRcolavccompcolcol

colcol

colmotcolavtHEGRcolapccompcolcol

colcol

colmotavtHEGRapccompcol

col

RTVNpQ

FFQFFQVp

RTF

TQTTQTTQVp

RTT

TQTQTQVRp

η

γγγ

γ

=

−+−=

−−−+−=

−+=

•

•

•

or non linear model reduction for LPV / sliding mode observer

Requirementsà To control intake air pressure with waste-gate and throttle

Check all functional requirements and quality commitments

Output products• Quality software

design report• Ready to

prototyping• Validation plan to

SIL & HILTime to Market

Quality

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3. MIL FUNCTIONNAL : for air pathRequirementsà Two-stage turbocharging air path control validation

Output products• Efficiency debugging

process• Validation report• Fast soft bug corrective loop

0 5 1 0 1 5 2 0 2 5 3 00 .5

1

1 .5

2

2 .5

te m p s [s ]

Psu

ral [

bar]

0 5 1 0 1 5 2 0 2 5 3 0-0 . 0 2

0

0 .0 2

0 .0 4

0 .0 6

0 .0 8

0 .1

0 .1 2

te m p s [s ]

Qai

r [kg

/s]

Time to Market

QualityCost

Optimal control under multi objectives / constraints


4. HIL : gasoline engine

44

RTABRESIL Curitiba

é

RTKCOREESeoul

RNTBCIINDEChennai

WEFRANCEESPAGNEValladolid

RTRROUMANIETitu

Objectives• Coding quality

verification• Verification on

virtual test bench

Output products• Quality report

Quality

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5. TUNING : virtual test bench

Driver and vehicle

Vehicle speed

Drivelineand gearbox

Powertrain control

Plant model

• Pollutants / CO2 • Air path : pressure,

temperature, mass-flow

• Torque…

Emission driving

Calibrations

Air path MVEM combustion &

pollutants

User interface

Objective• Replace real test bench by virtual test bench

Outputs products• Calibrations for the whole line-up• € save…

CostTime to Market



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06 Conclusion

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END

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Conclusion: Renault is ready to deploy next generation model-driven engineering capabilities and competences

Functional requirementsUse cases

Variety hypothesis

QualityCost

Time to Market

Plant Model


Thank you

[email protected]

Besten Dank für Ihre Aufmerksamkeit

Documents

Deployment of Model Based Design for Engine Control at Renault