机械科学与技术2024，Vol.43Issue(8)：1437-1446,10.DOI:10.13433/j.cnki.1003-8728.20230067
运用改进蜉蝣算法的增程式电动汽车能量管理策略研究
Research on Energy Management Strategy of Extended-range Electric Vehicle Using Improved Mayfly Algorithm
摘要
Abstract
Aiming at the rule-based energy control strategy optimization for the extended-range electric vehicles,a multi-point energy management control strategy based on the improved mayfly optimization algorithm is proposed.Taking the extended-range light truck as the object,the model for multi-objective optimization of the whole vehicle is established,and the improved mayfly optimization algorithm is used for offline optimization.A fuzzy controller is designed by taking the vehicle demand power and the variation of the battery SOC value as real-time input parameters to control the minimum hold time of the APU's current operating point.Finally,under the WLTP test condition,the optimized energy management control strategy is analyzed and verified by using MATLAB/Simulink and Cruise co-simulation.The results show that the improved optimization algorithm IMA inherits the advantages of MA,and improves the global search ability and the overall convergence speed of the algorithm in the early stage of optimization.Comparing with the thermostat and power-following energy management control strategies,the present multi-point energy management control strategy improves the comprehensive performance by 16.2%and 7.8%respectively,which effectively improves the overall performance of the vehicle.关键词
增程器/能量管理/多目标优化/蜉蝣算法Key words
range-extender/energy management/multi-objective optimization/mayfly algorithm分类
交通工程引用本文复制引用
孙云祥,王贵勇,王伟超,何述超..运用改进蜉蝣算法的增程式电动汽车能量管理策略研究[J].机械科学与技术,2024,43(8):1437-1446,10.基金项目
云南省科技厅揭榜制项目(202104BN050007)与云南省科技计划项目(202102AC080004) （202104BN050007）
