Research on Genetic-fuzzy Control Strategy for Parallel Hybrid Electric Vehicle

被引：0
|
作者：
Yang, Shichun [1 ]
Li, Ming [1 ]
Weng, Haoyu [2 ]
Liu, Bao [2 ]
Li, Qiang [2 ]
Zhu, Yongli [2 ]
Liu, Xiu [2 ]
机构：
[1] Beihang Univ, Sch Transportat Sci & Engn, 37 Xueyuan Rd, Beijing 100191, Peoples R China
[2] Great Wall Automobile Co Ltd, New Energy Lab, Baoding 071000, Hebei Province, Peoples R China
来源：
25TH WORLD BATTERY, HYBRID AND FUEL CELL ELECTRIC VEHICLE SYMPOSIUM AND EXHIBITION PROCEEDINGS, VOLS 1 & 2 | 2010年
关键词：
Parallel hybrid electric vehicle; genetic algorithm (GA); fuzzy control; optimization;
D O I：
暂无
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
Fuzzy control strategy is developed for the dual-clutch single-axis torque coupling parallel hybrid electric vehicle. Torque distribution fuzzy controller which has been designed for the hybrid vehicle is optimized by genetic algorithms. The simulation model of the hybrid vehicle was built upon matlab / simulink and ADVISOR software. Under typical condition NEDC, the fuzzy control strategy is optimized both by genetic algorithms with the constraint condition of economy performance and by integrated constraint conditions of economy performance and emission performance. Optimization results show that when the controller is optimized by genetic algorithms and the fuzzy controller, the fuel consumption decreased by 4.3%.
引用
收藏
页码：402 / 407
页数：6
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