Title :
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
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;
Conference_Titel :
Mechatronics and Automation (ICMA), 2012 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4673-1275-2
DOI :
10.1109/ICMA.2012.6285730
