Title :
Optimal Sizing of a Series Hybrid Electric Vehicle Using a Hybrid Genetic Algorithm
Author :
Liu, Xudong ; Wu, Yanping ; Duan, Jianmin
Author_Institution :
Beijing Univ. of Technol., Beijing
Abstract :
Hybrid electric vehicle is considered as the most promising solution to energy crisis and urban air pollution. However, as it has at least two sets of propulsion systems, its configuration is complex. To get better fuel economy and vehicle performance, the design and sizing of its powertrain components are important. In this paper, an HEXA optimal sizing method combining optimization algorithm and HEV simulation tool is introduced, and then a real-coded, adaptive based hybrid genetic algorithm is developed and applied to the optimal sizing of a series hybrid electric vehicle. ADVISOR2002 is used as the vehicle simulator. The results have proved the validity of the optimal sizing methodology and the efficiency of the hybrid genetic algorithm. Based on the results, some improvements are proposed on the vehicle studied.
Keywords :
genetic algorithms; hybrid electric vehicles; propulsion; hybrid genetic algorithm; optimal sizing; propulsion systems; real-coded genetic algorithm; series hybrid electric vehicle; Air pollution; Algorithm design and analysis; Couplings; Design optimization; Fuel economy; Genetic algorithms; Hybrid electric vehicles; Mechanical power transmission; Optimization methods; Propulsion; genetic algorithm; hybrid electric vehicle; optimal sizing; optimization;
Conference_Titel :
Automation and Logistics, 2007 IEEE International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-1531-1
DOI :
10.1109/ICAL.2007.4338737