Design of Energy Management Strategy in Hybrid Electric Vehicles by Evolutionary Fuzzy System Part II: Tuning Fuzzy Controller by Genetic Algorithms

Author

Wang, Aihua ; Yang, Weizi

Author_Institution

Dept. of Electr. & Comput. Eng., Purdue Univ., Indianapolis, IN

Volume

2

fYear

0

fDate

0-0 0

Firstpage

8329

Lastpage

8333

Abstract

This paper presents the second part of a two-part paper on development of an evolutionary fuzzy energy management strategy for parallel hybrid vehicles. In this part, we utilized genetic algorithms (GA) to optimize the parameters of the fuzzy controller. In addition, we employed a novel method to cope with the difficulties often encountered in designing a fitness function of GA. The simulation study reveals that the proposed "evolutionary fuzzy system" based energy management strategy provide a platform of new energy management system and gives improved performance of a parallel hybrid vehicle

Keywords

energy management systems; fuzzy control; fuzzy set theory; genetic algorithms; hybrid electric vehicles; evolutionary fuzzy energy management system; fitness function; fuzzy controller parameter optimization; fuzzy controller tuning; genetic algorithm; parallel hybrid electric vehicle; Algorithm design and analysis; Control systems; Energy management; Fuzzy control; Fuzzy logic; Fuzzy systems; Genetic algorithms; Hybrid electric vehicles; Medical services; Physics; Fuzzy rule base; energymanagement strategy; genetic algorithms; hybrid electric vehicle;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1713600

Filename

1713600