Research of Parameter Self-learning Fuzzy Control Strategy in motor control system for Electric Vehicles

被引:0
作者
Zhang Jian [1 ]
Wen Xuhui [1 ]
Zeng Li [1 ]
机构
[1] Chinese Acad Sci, Inst Elect Engn, Beijing, Peoples R China
来源
2009 INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS, VOLS 1-3 | 2009年
关键词
Electric vehicle (EV); Permanent magnet synchronous motor (PMSM); Fuzzy control; Parameter self-learning; Single neuron; Phase plane; DESIGN;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Based on the vector control method for PMSM, a parameter self-learning hybrid fuzzy controller was implemented to provide the speed control for the EV propulsion system with the purpose to obtain the maximum acceleration during starting and accelerating. A three-term fuzzy controller is implemented by simply using a two-term fuzzy control rule-base without any increase of rules. The method of fuzzy deduction based on phase plane had less computational burden, while the fuzzy inputs could be continuous. The control parameters are self-tuned by introducing a single neuron together with a back-propagation learning algorithm. This method has simpler structure and control algorithms and can be realized online easily. The simulation results and experiment results of 18kW PMSM for electric vehicle propulsion are given, the experiment results show that the electric vehicle with parameter self-learning hybrid fuzzy vector control system has excellent performances of starting, accelerating and cruising on road.
引用
收藏
页码:844 / +
页数:2
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