并联式混合动力汽车模糊控制策略优化  

Fuzzy Control Strategy Optimization of Parallel Hybrid Electric Vehicle

作　　者：黄禀通 朱建军 周忠伟 陈登攀 HUANG Bing-tong;ZHU Jian-jun;ZHOU Zhong-wei;CHEN Deng-pan(College of Mechanical and Vehicle Engineering,Taiyuan University of Technology,Shanxi Taiyuan 030024,China)

机构地区：[1]太原理工大学机械与运载工程学院,山西太原030024

出　　处：《机械设计与制造》2020年第12期293-297,共5页Machinery Design & Manufacture

基　　金：山西省应用基础研究项目(201701D121125)。

摘　　要：整车节能减排效果受模糊能量管理策略中各种参数的影响,因此有必要针对模糊控制中的关键参数进行优化。在MATLAB/Simulink环境下搭建面向并联式混合动力电动汽车的驱动模糊控制能量管理策略,将油耗及排放综合最小化作为目标,在C-WTVC循环工况下采用遗传算法求解模糊逻辑控制器最优的模糊规则表和整车动力性参数。利用硬件在环仿真测试系统验证优化后控制策略的有效性,结果表明,采用遗传算法优化后的驱动模糊控制策略可以进一步降低整车的百公里燃油消耗,改善各种污染物的排放,并减小动力电池组SOC值的波动。The effect of energy saving and emission reduction is affected by various parameters in the fuzzy energy management strategy,so it is necessary to optimize the key parameters in the fuzzy control.The driving fuzzy control energy management strategy for parallel hybrid electric vehicle is established in the MATLAB/Simulink and with the goal of minimizing fuel consumption and emissions,genetic algorithm is used to optimize the fuzzy rules of fuzzy logic controller and vehicle dynamic parameters under C-WTVC cycle condition.The effectiveness of the optimized control strategy is verified by HIL,and the results show that the driving fuzzy control strategy based on optimization of genetic algorithm can further reduce fuel consumption measuring on one-hundred-kilometer,improve the emissions of various pollutants and reduce the fluctuation of SOC for battery pack.

关 键 词：并联式混合动力汽车 模糊控制 遗传算法 硬件在环仿真 

分 类 号：TH16[机械工程—机械制造及自动化]