摘要
为了降低混合动力汽车的能耗,提高其能量回收率及减少其尾气排放量,对并联式混合动力汽车(PHEV)的能量管理系统采用基于粒子群优化的模糊控制进行分析与设计。首先在Matlab中的Simulink软件上建立了模糊控制器模型,根据经验设计模糊控制规则;然后将模糊控制器嵌入到Advisor仿真软件的并联式混合动力汽车模型中,并用粒子群优化算法对该模糊控制器进行优化;最后选择几种典型的运行路况进行仿真分析研究。仿真结果表明,在满足汽车行驶性能的前提下,优化后的模糊控制器不仅能有效降低尾气的排放,并且能明显提高能量回收率。
In order to reduce the energy consumption, improve energy recovery and reduce emissions, the energy management system for Parallel Hybrid Electric Vehicle was analyzed and designed using fuzzy control based on particle swarm optimization. First, the fuzzy control of EMS for PHEV was built in Matlab/Simulink, and fuzzy control rules were designed according to experience. Then, the fuzzy control was embedded in the parallel vehicle of the ADVISOR software, and the fuzzy controller was optimized by particle swarm optimization algorithm. Then the simulation results are obtained from several kinds of typical operation traffic. The results of the simulation show that, on the premise of meeting the car performance, the fuzzy controller which has been optimized can not only reduce ex- haust emissions effectively, but also improve the energy recovery obviously.
出处
《控制工程》
CSCD
北大核心
2014年第3期357-360,共4页
Control Engineering of China
基金
国家自然科学基金项目(61074067
21106036)
湖南省自然科学基金项目(13JJ1038)
湖南省教育厅科学研究基金项目(11B038)
关键词
PHEV
模糊控制
能量管理策略
粒子群算法
parallel hybrid electric vehicle
fuzzy controller
energy management strategy
PSO
