摘要
针对电动汽车复合电源模糊能量管理,传统模糊控制依赖专家经验存在精度不高、自适应性弱等不足,设计了一种基于改进布谷鸟搜索算法(ICS)优化的模糊控制方法;在Matlab/Simulink平台上建立车载复合电源模糊控制器,采用ICS算法对模糊控制器中的隶属度函数参数进行优化,然后将其嵌入到Advisor软件中复合电源电动汽车模型进行仿真与分析;结果表明,与传统模糊控制相比较,该方法能更好发挥超级电容性能优势,减缓了电池输入、输出功率且整车能耗经济性得到提升。
Aiming at the fuzzy energy management of hybrid energy storage system(HESS)in electric vehicle,the traditional fuzzy control,which relies on expert experience,has the disadvantages of low accuracy and poor adaptability.A improved cuckoo search(ICS)algorithm optimization fuzzy control method is designed.Establishing fuzzy controller for vehicle-mounted HESS based on Matlab/Simulink platform,and the ICS algorithm is used to optimize the parameters of membership function in fuzzy controller.Then,the optimized fuzzy controller is embedded into the HESS with electric vehicle of Advisor software for simulation and analysis.The result shows that compared with the traditional fuzzy control,the designed method can more effectively exert ultracapacitor performance advantage,slow down the input and output power of the battery,and energy consumption economy of the vehicle is raised.
作者
陈德海
徐王娟
华铭
Chen Dehai;Xu Wangjuan;Hua Ming(School of Electrical Engineering and Automation,Jiangxi University of Science and Technology,Ganzhou 341000,China)
出处
《计算机测量与控制》
2019年第1期92-96,101,共6页
Computer Measurement &Control
基金
江西省自然科学基金(20151BAB206034)
关键词
电动汽车
复合电源
改进布谷鸟搜索算法
控制策略
electric vehicle
hybrid energy storage system
improved cuckoo search algorithm
control strategy