基于遗传算法的并联式混合动力汽车能量管理策略优化  

Optimization of Energy Management Strategy for Parallel Hybrid Electric Vehicle Based on Genetic Algorithm

作　　者：张丹 刘国 Zhang Dan;Liu Guo(Hunan Automotive Engineering Vocational College,Zhuzhou 412000)

机构地区：[1]湖南汽车工程职业学院,株洲412000

出　　处：《内燃机与配件》2022年第21期95-97,共3页Internal Combustion Engine & Parts

基　　金：湖南省教育厅科学研究项目(20C0999)。

摘　　要：针对并联式混合动力汽车发动机和电机功率的实时分配问题,设计了一种基于遗传优化的模糊控制策略。引入模糊逻辑控制以增强整车控制系统的鲁棒性、实时性;采用遗传算法对隶属度函数进行优化,并在CYC_UDDS循环工况下进行仿真实验。Advisor仿真结果表明,相较于未优化的模糊控制策略,优化后的模糊控制器提升了整车的燃油经济性,同时避免了电池在SOC过低时继续放电,延长电池组的使用寿命。A fuzzy control strategy based on genetic optimization was designed to solve the real-time power allocation problem of engine and motor in parallel hybrid electric vehicle. Fuzzy logic control was introduced to enhance the robustness and real-time performance of the vehicle control system. The membership function were optimized by genetic algorithm, and the simulation experiment was carried out under CYC_UDDS cycle condition. Advisor simulation results showed that compared with the non-optimized fuzzy control strategy, the optimized fuzzy controller improves the fuel economy of the vehicle.The SOC of battery was controlled within a reasonable range, and the service life of battery pack was extended.

关 键 词：遗传算法 模糊控制 混合动力汽车 

分 类 号：U464[机械工程—车辆工程]