Genetic algorithm based optimization and simulation of electric bus power system parameters

Author

Zhang, Hailong ; Huang, Dagui ; Dai, Deng ; Guo, Ping ; Lin, Fengjun

Author_Institution

Sch. of Mechatron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China

fYear

2012

fDate

5-8 Aug. 2012

Firstpage

2451

Lastpage

2455

Abstract

This paper based on the pure electric bus for research object, according to the requirements of electric vehicle performance, the parameters of electric motors and battery could be selected and designed. Combined with the electric vehicle simulation software ADVISOR to simulate the dynamic performance and driving range. Simulation software can not optimize the parameters, so the total capacity of the battery pack and the number is set to use the Genetic Algorithm, to select the variables and determine the objective function to find the optimal solution to improve vehicle performance.

Keywords

battery powered vehicles; electric motors; genetic algorithms; ADVISOR electric vehicle simulation software; battery pack; electric bus power system parameter simulation; electric motors; electric vehicle performance; genetic algorithm; objective function; Batteries; Electric vehicles; Genetic algorithms; Linear programming; Software; System-on-a-chip; ADVISOR; Drive range; Electric bus; Genetic Algorithm; Simulation;

fLanguage

English

Publisher

ieee

Conference_Titel

Mechatronics and Automation (ICMA), 2012 International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4673-1275-2

Type

conf

DOI

10.1109/ICMA.2012.6285730

Filename

6285730