Applying genetic search techniques to drivetrain modeling

Author

Maclay, D. ; Dorey, R.

Author_Institution

Cambridge Control Ltd., UK

Volume

13

Issue

3

fYear

1993

fDate

6/1/1993 12:00:00 AM

Firstpage

50

Lastpage

55

Abstract

Work carried out to identify a nonlinear model of a vehicle engine and drivetrain is discussed. A hybrid approach that combines both physical modeling and parameter optimization using genetic algorithm (GA) search techniques is used. The resulting models, which cover a range of operating conditions, have allowed the sensitivity to variation of key parameters to be assessed and have been used to help optimize the overall response of the vehicle drivetrain. A comparison of the GA search and a gradient based method, which highlights the intelligent nature of the former approach, is presented.<>

Keywords

automobiles; genetic algorithms; intelligent control; internal combustion engines; parameter estimation; search problems; drivetrain modeling; genetic algorithm; gradient based method; intelligent control; parameter identification; parameter optimization; road vehicle; search problems; sensitivity; vehicle engine; Damping; Engines; Genetics; Mechanical power transmission; State-space methods; Testing; Transfer functions; Vehicle driving; Vehicle dynamics; Vehicles;

fLanguage

English

Journal_Title

Control Systems, IEEE

Publisher

ieee

ISSN

1066-033X

Type

jour

DOI

10.1109/37.214944

Filename

214944