Parameter Optimization of Power Control Strategy for Series Hybrid Electric Vehicle

Author

Huang, Bufu ; Shi, Xi ; Xu, Yangsheng

Author_Institution

Chinese Univ. of Hong Kong, Shatin

fYear

0

fDate

0-0 0

Firstpage

1989

Lastpage

1994

Abstract

Aimed at the more and more serious problems of energy and pollution, Hybrid Electric Vehicle (HEV) is one of the best practical applications for transportation with high fuel economy and low emission. Since the power control strategy has a critical effect on the performance of HEV, genetic algorithm is introduced to optimize the strategy parameters for fuel economy and emissions in this paper. Compared with two main strategies, Thermostatic and DIRECT, the computation procedures of genetic algorithm are discussed, and simulation study based on the model of series hybrid electric vehicle is given to illustrate the optimization validity of the genetic algorithm.

Keywords

air pollution; genetic algorithms; hybrid electric vehicles; power control; fuel economy; genetic algorithm; parameter optimization; power control strategy; series hybrid electric vehicle; transportation; Automatic control; Batteries; Engines; Fuel economy; Genetic algorithms; Hybrid electric vehicles; Optimization methods; Pollution; Power control; Transportation;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2006. CEC 2006. IEEE Congress on

Conference_Location

Vancouver, BC

Print_ISBN

0-7803-9487-9

Type

conf

DOI

10.1109/CEC.2006.1688551

Filename

1688551