Co-Simulation for hybrid vehicle control software development

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Co-Simulation For HEV Control SW-Development

Co-Simulation for hybrid vehicle control software

development

Marcus Boumans, Sebastian Wansleben

Robert Bosch GmbH

GT User Conference

21. October 2013

Frankfurt

DGS-EC/EAM | 06/09/2013 | © Robert Bosch GmbH 2013. All rights reserved, also regarding any disposal, exploitation, reproduction, editing, distribution, as well as in the event of applications for industrial property rights.

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Co-Simulation For HEV Control SW-Development

Contents



Scope & Motivation



Use cases & Requirements



Simulation Environments



Parameterization & Validation

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Scope of (Co)Simulation

Scope & Motivation

Scope of (Co)Simulation

Support the development of innovative

energy management control strategies for passenger cars

Domains under investigation:

Combined control strategy

HEV Powertrain control strategy

Thermal system control strategy

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Motivation for (Co)Simulation

Scope & Motivation

Motivation for (Co)Simulation



Good reproducibility and fast repeatability of experiments



Required especially for traffic simulation & warm-up experiments



Investigation of real world systems with limited availability



Not all HEV / thermal topologies are available as real systems



Time & costs savings by “Virtual Controller Prototyping”



Run control strategy model on a rapid prototyping system in a

vehicle

Using (Co)Simulation makes us faster and saves money!

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Development: Thermal System Control Strategy

Usecases &

Requirements

Development: Thermal System Control Strategy

Function:



Optimized thermal management with

i iti ti

f

f t d f l

prioritization of comfort and fuel

consumption

Considered information:



Engine load and speed



Cooling/Exhaust system

temperatures/flowrates



Influence on powertrain control

Requirements for the Simulation:



Engine model with thermal behavior



Detailed cooling/ exhaust system model



Powertrain model including friction

EM

E-Machine

TC

Turbo Charger

HTC

High Temperature Cooler



Model of control strategy software

OC

Oil Cooler

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Development: Map-based

eco

ACC (HEV)

Usecases &

Requirements

Development: Map based

eco

ACC (HEV)

Function:



Vehicle increases, decreases and

h ld d t

l

holds speed autonomously

Considered information:

f

Navigation

ACC

HMI



Desired vehicle behavior from HMI



Track information from navigation



Traffic information from radar

Map-based

ecoACC

Requirements for the Simulation:



Radar system model, traffic model

Powertrain

Control

Brake

Control



Navigation system model



Powertrain model



Model of control strategy software

•

CO

2

-reduction



Cross domain function



Department | 06/09/2013 | © Robert Bosch GmbH 2013. All rights reserved, also regarding any disposal, exploitation, reproduction, editing, distribution, as well as in the event of applications for industrial property rights.

Diesel Gasoline Systems

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gy

•

Cross domain function



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Contents

Simulation

Environments

Contents



Scope & Motivation



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Optimization Thermal System Control Strategy (HEV)

Simulation

Environments

Optimization Thermal System Control Strategy (HEV)

load, speed

Plant Model

Control Software Model

Thermal system

Lubrication

Exhaust System

actuator

sensor

temperatures, fuel consumption

make

Tasks:



Optimization of the thermal system (HW & SW)



Testing of optimized SW version in a concept car

Rapid-Prototyping-HW

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Testing of optimized SW version in a concept car

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Co-Simulation For HEV Control SW-Development

Combined HEV & Thermal Strategy Optimization

Simulation

Environments

Combined HEV & Thermal Strategy Optimization

Plant Model

Driving cycle

(operation strategy thermal)

actuator

sensor

Thermal system

Lubrication

Exhaust System

Vehicle

(operation strategy hev)

DLL

Import

T k

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ti t CO2 b

fit f

bi d th

l

d HEV t t

ti i ti

temperatures, fuel consumption, SOC

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Simulation Environment for Map-based

eco

ACC

Simulation

Environments

Simulation Environment for Map based

eco

ACC

Maneuver Road Traffic

Maneuver, Road,Traffic

ADAS RP

eHorizon

actuator, sensor

Surrounding sensor info

Plant Model

Powertrain

GPS

Position

torque

,

speed

Tasks:

Optimize & develop predictive powertrain control strategy

fuel consumption, SOC

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Tasks:

Optimize & develop predictive powertrain control strategy

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Contents

Parameterization &

Validation

Contents



Scope & Motivation



Used Simulation Environments



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Co-Simulation For HEV Control SW-Development

Parameterization

Parameterization &

Validation

Parameterization

Perform special vehicle

measurements

Use data from

calibration departments

Use catalogue data

geometric data

Vehicle.dat

EngineDyno

XLS

p

MotorDyno

XLS

g

100

Script

0 50 100 150 200 250 300 0 10 20 30 40 50 60 70 80 90 100 Vehicle Speed [km/h] Acce l. Pe d a l Po s. [%] shift12 shift23 shift34 shift45 shift56 shift67 shift78

Shift

strategy

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Validation: Fuel Consumption

Parameterization &

Validation

Validation: Fuel Consumption

16 18 Fuelconsumption NEDC Measurement Simulation

Rel. Error

MEAN

2.61 %

6 8 10 12 14 el c ons um pt ion [m l/ s ]

SDEV

10.94 %

0 100 200 300 400 500 600 700 800 900 1000 0 2 4 Fu 1000 1200 1400 1600 1800 o ns u m pt io n [ m l]

Rel. Error

MEAN

1.71 %

SDEV

1.69 %

0 200 400 600 800 1000 A c c u mu la te d fu e l c o 0 100 200 300 400 500 600 700 800 900 1000 0 time [s]

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Validation: Exhaust Temperature

Parameterization &

Validation

Validation: Exhaust Temperature

900 1000

Temperature downstream Catalyst

Measurement Simulation

Rel. Error

MEAN

- 1.89 %

S

10 31 %

700 800 900

SDEV

10.31 %

400 500 600 Tem per at ur e [ °C ] 200 300 400 0 200 400 600 800 1000 1200 1400 0 100 time [s]

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Contents



Scope & Motivation



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Summary

Summary &

Conclusion

Summary



There are use case specific simulation environments for

Thermal Strategy

Combined Strategy

Predictive Strategy

Thermal Strategy

Combined Strategy

Predictive Strategy



GTSuite is applied for plant models



CarMaker is applied for radar sensor models & maneuver, traffic

pp

,

simulation



ASCET & Simulink are applied for control software models

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ASCET & Simulink are applied for control software models

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Conclusion



GT Suite fulfills our requirements for a scalable simulation/modeling

environment for plant models



To cover all use cases several tools have to be integrated to one

useful simulation application

Requirement:

Standardized interfaces for tool interoperability



Reuse of subsystem models coming from different tools is essential

Requirement:

q

Standardized ex-/import features for model exchange

/ p

g

Continue development in tool interoperability & model exchange features

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Co-Simulation For HEV Control SW-Development

Th k

f

tt ti !

Thank you for your attention!

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