Consistent development of hybrid vehicles at the engine-in ... · Consistent simulation-based development methodologies help to manage high complexity and number of variants in the

19 September 2012 | Ettlingen | Institute for Internal Combustion Engines | Matthias Kluin | 1

Consistent development of hybrid vehicles at the engine-in-the-loop testbed

Maximilian Bier, Matthias Kluin, Prof. Dr. Christian Beidl Institute for Internal Combustion Engines and Powertrain Systems Technische Universität Darmstadt

apply & innovate 2012 IPG Technology Conference 18 and 19 September 2012 | Ettlingen


Content

Motivation

Development process and tools for hybrid powertrains

Consistent hybrid operating strategy

Testing methodologies for hybrid powertrains

Application examples at the engine-in-the-loop testbed

Summary


Strong Increase of Parameters in Hybrid Powertrains

Operating strategy

Vehicle size

Cost of sales

Component dimensions Cost of ownership

Drivability/ fun-to-drive

Powertrain architecture

Usage scenario

Veh

icle

par

amet

ers

Cu

stomer req

uirem

ents

Hybrid Powertrains


Efficient and Coordinated Development of Hybrid Vehicles

Efficiency in Development

Efficient Operating

• Trade-Off: • Lowest consumption

possible • Emission limits • Driveability • Durability

• Sophisticated tuning in harmonizing strategy and concept (usage rate of installed components)

Efficient Development

• Few iteration steps

• Few prototypes

• Few test vehicles

• Determination and validation of optimal configurations

Consistent Tools, Models and Control Functions


Content

Motivation





Summary


Development Tools in the Development Process

System integration System tests

System application

Architecture

Detailed function and component design

Requirements

Component test Component dimensioning Basic energy management


Architecture Definition and Component Dimensioning via Reverse Simulation

Virtual Vehicle

Vehicle kinetics

Driving resis- tance

Operating strategy (HCU)

+

Powertrain

ICE

EM

EG

dv(t)/dt

v(t)

FWheel(t)

nICE(t) TICE(t)

nEM(t) TEM(t)

nEG(t) TEG(t)

PBat(t) Battery

Fuel tank

mFuel(t)

Driving profiles

αIncl.(t)

TGas(t) mGas(t) XGas(t)

Exhaust system

Reverse Simulation: Targets as inputs (velocity, torque, etc.) Highly comparative results by open loop control Simple models for fast simulation

Need for basic operating strategy

Environment




System application

Architecture

Component dimensioning


Requirements

Component test Basic energy management


Detailed Forward Simulation

Driver

Input

Driver Model

Environment

vact

Vehicle Model Operating Strategy

~ =

ICE Clutch

Battery

+ -




System application

Architecture



Requirements



Detailed Forward Simulation and Engine-in-the-Loop (EiL)

TB Automation System

MG

2 Dyno

Converter T mea

s.

Vehicle Model

Driver

Input

Driver Model

Environment

Operating Strategy

vact

ICE

RT Simulation Platform

nset CAN

Kle

mm

e 15

, alp

ha

n act

Speed Control

~ =

ICE Clutch

Battery

+ -



Architecture



Requirements



System application


X-in-the-Loop (XiL)


MG

2 Dyno

Converter T mea

s.

Vehicle Model

Driver

Input

Driver Model

Environment

Operating Strategy

vact

ICE

RT Simulation Platform

nset CAN

Kle

mm

e 15

, alp

ha

n act

Speed Control

Battery

+ -

~ =

Battery Simulator.


in-the-Loop-Simulation

nist


MG

2

Dyno

ConverterT mea

s.

Vehicle Model

Driver

Input

Driver Model

Environment

Operating Strategy

vact RT Simulation Platform

nsetCAN

Kle

mm

e 15

, alp

ha

n act

Speed Control

~=

ICE Clutch

Battery

+ -

Operating Strategy: Vehicle-realistic composition Depending on signals provided by real

components Depending on powertrain and vehicle

concept

Vehicle models at VKM: Powersplit hybrid P1 parallel hybrid P2 parallel hybrid Boosted Range Extender

Focus of VKM Testbed set-up Application Methods for

Operating Strategies


Content

Motivation





Summary


Proposed Strategy Structure

Energy Management (OP-Determination, Thermo Management)

Driving State

ECU

Driver input Driver type Road state Track

information Trip

information

Power Electr.

Operating State

SOC Power in

low voltage system

ICE OP TCat …

Driver Feedback

TCU

Low Voltage System Control

Operating Strategy

BCU

+ -

Auxilia-ries

Control of Dynamics


Proposed Strategy Structure: State Analysis


Driving State


information Trip

information

Operating State

SOC Power in

low voltage system

ICE OP TCat …

Driver Feedback


Operating Strategy

Control of Dynamics

Driver input interpretation Communication with

driver assistance systems Adaptation and prediction

functions

Interpretation of sensor signals

Communication with Control Units

Virtual sensors

High potential for reuse of functions in different strategies


Proposed Strategy Structure: Operating Point Assignation


Driving State


information Trip

information

Operating State

SOC Power in

low voltage system

ICE OP TCat …

Driver Feedback


Operating Strategy

Control of Dynamics

Quasi-stationary Basic operating point

Determination Conditioning functions

Coordination in dynamic manouvers: Engine start Mode switch Gear shifting

Coordinate power peaks

Coordinate heat provision with heat usage

Facilitation of continuous evolution and parallel development

Separation of test procedures


Proposed Strategy Structure: Driver Feedback


Driving State


information Trip

information

Operating State

SOC Power in

low voltage system

ICE OP TCat …

Driver Feedback


Operating Strategy

Control of Dynamics

Advise for efficient driving

Range and Risk information

High potential for reuse of functions in different strategies


Content

Motivation





Summary


Test Scenarios in the Development of Hybrid Vehicles

Real World Cons. Durability Drivability

Driver and Road Adaptation

Cycle Consumpt. Emissions

Road Profile

Traffic

Driver

Trade-Off

Real World NEDC Maneuvers

Durability Drivability Emissions

Functionality


Strategy Development and Application in Corresponding Test Scenarios


Driving State


information Trip

information

Operating State

SOC Power in

low voltage system

ICE OP TCat …

Driver Feedback


Operating Strategy

Control of Dynamics

Maneuvers Real World

Functionality Driver and Road

Adaptation

Maneuvers

XiL

Functionality

NEDC Real World

Simulation, EiL

Cyc. Consumpt. Emissions

RW Cons. Durability Drivability

Maneuvers

EiL, XiL


Functionality

Maneuvers

Simulation, XiL


Functionality

Simulation


Example for Energy Management Application

Driving Cycles

Vehicle Parameters

Simulation+Test

Environment Virtual Vehicle

v

MICE

Pedals

v

Driver

Road+ Traffic/ Vel. Profile

VMα, Inj…

SoC

M F

nWheels

MEM

Gear No. / i

MSet

nEM

Battery

EM

U I

nICE

ICE TB

VehicleKinetics

HCU

Environment Information (Friction, Inclination, …)

Mech.System Wheels

Consumption/CO2-Em.

Emissions

Durability

Driveability

DoE Model

Parameters Targets (out of

modelling)

Optimization

Validation


Content

Motivation




Application examples

Summary


Example for Energy Management Application

Testrun: Forward simulation Powersplit hybrid TUD urban cycle (Real World) Variation of 6 Parameters 2D-map for battery charging power

(3 Parameters) ICE state parameters (3 Parameters)

Targets Efficiency – fuel consumption with

SOC equivalent Durability – battery stress index

(depending on SOC and current) 50

100

150

200

250

300

4 5 6 7 8 9

Batt

ery

Stre

ss [1

/km

]

Fuel Consumption [l/100km]

Simulated Points (generated by DoE)

Pareto Set

Optima of Pareto Set used for Verification

Verification


Example for Advanced Energy Management Application

Road Gradient

Initial SpeedEgo-Vehicle

TrafficSpeed

ParametersEnergy Management

Scenario and its parameters

Road Gradient [m/m] Traffic Speed [m/s]

Cum

. Bat

tery

Stre

ss[W

h]

Road Gradient [m/m] Traffic Speed[m/s]

Ener

gyCon

sum

ptio

n[W

h]

Simulation results

Control functions and parameters •ACC parameters

• Time gap • Control constants

•HCU parameters • SOC swing • Max. el. Power


Driveability issues for clutch actuated ICE start in P2 hybrid

Example for Control of Dynamics Application

17.7 18.0 18.3 18.6 18.9 19.2 19.5 19.8Time [s]

Spe

ed [r

pm]

-500

0

500

1000

1500

2000

2500

3000

Com

bine

d To

rque

[Nm

]

-240

-160

-80

0

80

160

ICE Speed

EM Speed


Driving State


information Trip

information

Operating State

SOC Power in

low voltage system

ICE OP TCat …

Driver Feedback


Operating Strategy

Control of Dynamics

~ =


Content

Motivation





Summary


Consistent simulation-based development methodologies help to manage high complexity and number of variants in the development of hybrid powertrains

In-the-loop simulation is key development methodology for a reliable determination of relevant targets like fuel consumption or exhaust emissions in early development phases

Necessary consistent use of hybrid operating strategy demands a consequential structure of the hirarchy of the functions

Testing methodologies like emission cycles, maeuvers or real-world cycles have to be adopted to development targets

Systematic optimization methodologies enable an efficient and reliable determination of optimal parameter configurations for energy management functions

Summary


Thank you for your attention.

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Consistent development of hybrid vehicles at the engine-in ... · Consistent simulation-based development methodologies help to manage high complexity and number of variants in the