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Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

GT CONFERENCE 2014 – Oct. 20th - Frankfurt

Dipl. Ing. Thorsten Krenek Ass. Prof. Dr. Thomas Lauer

GT Conference 2014 Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

20.10.2014 | Frankfurt | T. Krenek | Folie 2

Overview

Introduction

Comprehensive vehicle modelling

− Development of the simulation model

Powertrain optimization

− Problemdefinition and constraints

− Applied optimization software

− Experimental results

Conclusions and outlook

GT Conference 2014 Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

20.10.2014 | Frankfurt | T. Krenek | Folie 3

Introduction Motivation

Electric hybrid powertrains are a promising approach in terms of CO2

emissions

Higher electrificication higher complexity higher degree of freedom

− Operation strategy

− Component dimensioning

− Thermal management

Development and application of numerical simulation models and

optimization software

GT Conference 2014 Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

20.10.2014 | Frankfurt | T. Krenek | Folie 4

Overview

Introduction

Comprehensive vehicle modelling

− Development of the simulation model

Powertrain optimization

− Problemdefinition and constraints

− Applied optimization software

− Experimental results

Conclusions and outlook

GT Conference 2014 Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

20.10.2014 | Frankfurt | T. Krenek | Folie 5

Numerical Vehicle Simulation Model Overview

The longitudinal vehicle model and all sub-models were built in GT-SUITE

Thermal- management

ICE

Operation Strategy

Battery

Aux. Driving Cycle

Brake Control E-Maschine

Generator E-Maschine Motor

Clutch- control

PGS

Vehicle

Ambient

GT Conference 2014 Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

20.10.2014 | Frankfurt | T. Krenek | Folie 6

Numerical Vehicle Simulation Model Internal Combustion Engine

Vibe Combustion

Inlet ports Exhaust ports Inlet ports Exhaust ports

Vibe parameters are calculated using neural networks Mean cylinder

Calculation of the influencing variables by neural networks

Detailed ICE and mean value ICE

GT Conference 2014 Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

20.10.2014 | Frankfurt | T. Krenek | Folie 7

Numerical Vehicle Simulation Model Internal Combustion Engine

Why using a detailed instead of map-based ICE model ?

− Geometry, Cylindernumber and ICE parameters can be varied

− But much higher computational effort

Mean Value Models

− Realtime capability

− ICE parameters still variable

− Variations must be included in

neural network training

− Lower accuracy

Simplification necessary for optimization purposes

Fast Running Models (FRM)

− Simplified geometries

− Still Good accuracy

− Lower computational effort

− But to slow for optimization

GT Conference 2014 Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

20.10.2014 | Frankfurt | T. Krenek | Folie 8

Coolant Cyle with and without using ICE Waste Heat

Numerical Vehicle Simulation Model Thermal management - coolant circle

ICE waste-heat

Coolant Cabin-air Heat-exchange

Electric heater

Using Waste-Heat

Without waste-heat usage

GT Conference 2014 Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

20.10.2014 | Frankfurt | T. Krenek | Folie 9

Coolant Cyle with and without using ICE Waste Heat

Numerical Vehicle Simulation Model Thermal management - coolant circle

ICE waste-heat

Coolant Cabin-air Heat-exchange

Electric heater

Using Waste-Heat

GT Conference 2014 Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

20.10.2014 | Frankfurt | T. Krenek | Folie 10

Overview

Introduction

Comprehensive vehicle modelling

− Development of the simulation model

Powertrain optimization

− Problemdefinition and constraints

− Applied optimization software

− Experimental results

Conclusions and outlook

GT Conference 2014 Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

20.10.2014 | Frankfurt | T. Krenek | Folie 11

Optimization Goal

− Minimized fuel consumption for specified driving cycles

Constraints

− Battery state-of-charge (SOC) at the end of the driving cycle must be equal to the

reference solutions, otherwise penalty consumption will be added

− Maximum deviation of the driving-cycle of +/- 1 km/hr or +/- 1 second

− At cold ambient conditions (-10°C) a specific cabin temperature must be achieved

after five minutes

Powertrain Optimization Problemdefinition and constraints

GT Conference 2014 Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

20.10.2014 | Frankfurt | T. Krenek | Folie 12

Why using numerical optimization?

− higher degrees of freedom at electro-hybrid powertrains

− High computational effort for the objective

function calculation

Development of numerical optimization

software for continuous parameter variations

− Cooperation with the workgroup for algorithms

and data structures at the Vienna University of

Technology

− Combination of metaheuristics (Particle Swarm,

Genetic Algorithms, Evolutionary Algorithms)

− Model approximation by neural networks

Powertrain Optimization Optimization Software

GT Conference 2014 Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

20.10.2014 | Frankfurt | T. Krenek | Folie 13

For the investigations two different driving cycles were considered

− Ambient Temperatures -10°C, 20°C, 40°C

− Min and max SOC at cycle start

Powertrain Optimization Experimental Results

Vehi

cle

Spe

ed [k

m/h

]

Time [s]

NEFZ US06

33 km/h Average speed Low dynamic

77 km/h Average speed High dynamic

GT Conference 2014 Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

20.10.2014 | Frankfurt | T. Krenek | Folie 14

Optimization and parameter analyse using Self-organizing-maps (SOMs)

Powertrain Optimization Experimental results – example: US06 at cold ambient conditions

Amount of calculated solutions Fuel consumption

low

high high

low

low

high

Maximum used generator power

Valu

es

Valu

es

Max. e-heat power

GT Conference 2014 Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

20.10.2014 | Frankfurt | T. Krenek | Folie 15

ICE operation points distribution

− High powerdemand ICE at high load / speed lambda < 1 necessary

− Limitation of the max.

generator power

most of the operation time is

at lower speed with higher

efficiency

Powertrain Optimization Experimental results – example: US06 at cold ambient conditions

Low efficiency High efficiency

GT Conference 2014 Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

20.10.2014 | Frankfurt | T. Krenek | Folie 16

Electrical heat demand

− Electrical heating deactivated

at optimized solutions

− higher usage of the coolant

thermal energy

− Disadvantage: lower coolant

temperature higher friction

− Nearly the same thermal

comfort during heat up

Powertrain Optimization Experimental results – example: US06 at cold ambient conditions

GT Conference 2014 Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

20.10.2014 | Frankfurt | T. Krenek | Folie 17

Overview

Introduction

Comprehensive vehicle modelling

− Development of the simulation model

Powertrain optimization

− Problemdefinition and constraints

− Applied optimization software

− Experimental results

Conclusions and outlook

GT Conference 2014 Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

20.10.2014 | Frankfurt | T. Krenek | Folie 18

Conclusions

For investigations of an electro-hybrid powertrain a comprehensive

longitudinal model was developed with GT-SUITE and calibrated with

measurements on the engine test bench and dynamometer

Using numerical optimization software the operating strategy and

powertrain components were optimized under different ambient

conditions and driving cycles

For the specific driving cycles optimized operating strategies could be

developed with respect to fuel consumption using numerical optimization

methods

GT Conference 2014 Optimization of a Hybrid Powertrain using a Comprehensive Vehicle Model

20.10.2014 | Frankfurt | T. Krenek | Folie 19

Outlook

In-Car GPS Coupling – derivation of

the power demand

Results of optimized strategies with

similar power demand could be used

Optimization of real and longer

driving-cycles

Segmentation of the driving

cycles

Simplification and

approximation of the models

Use of the simulation model and the optimized strategies for real driving

Thank you for your attention!

Dipl. Ing. Thorsten Krenek [email protected]