增程式电动汽车能量管理策略多目标优化  

Multi-objective optimization of energy management strategy for extended range electric vehicle

作　　者：徐严 王良模[1] 刘经兴 王陶[1] 陈刚[1] 邹小俊[2] Xu Yan;Wang Liangmo;Liu Jingxing;Wang Tao;Chen Gang;Zou Xiaojun(School of Mechanical Engineering,Nanjing University of Science and Technology,Nanjing 210094,China;Nanjing Iveco Automobile Co.,Ltd.,Nanjing 211800,China)

机构地区：[1]南京理工大学机械工程学院,江苏南京210094 [2]南京依维柯汽车有限公司,江苏南京211800

出　　处：《南京理工大学学报》2023年第5期596-603,共8页Journal of Nanjing University of Science and Technology

基　　金：国家自然科学基金面上项目(51675281)。

摘　　要：针对增程式电动汽车馈电状态下增程器燃油消耗较高,动力电池寿命衰减较大等问题,提出一种基于遗传算法的能量管理策略多目标优化方法。在选择增程器四点控制策略的基础上,以减少等效燃油消耗及提高电池循环使用寿命作为优化目标,采用遗传算法进行多目标优化。分别采用Simulink、Cruise搭建控制策略模型和整车模型,进行NEDC工况和复合工况下的联合仿真。仿真结果表明,该文提出的控制策略鲁棒性较强,在电量保持模式下,优化后百公里等效油耗分别减少13.2%和8.8%、流经电池能量减少8.9%和5%,有助于提高电池循环使用寿命。In order to solve the problems of high fuel consumption of range extender and large power battery life attenuation under the feeding condition of extended range electric vehicle,a multi-objective optimization method of energy management strategy based on genetic algorithm is proposed.On the basis of selecting the four-point control strategy of the range extender,the optimization goal is to reduce equivalent fuel consumption and improve battery cycle life,the genetic algorithm is used for multi-objective optimization.Simulink and Cruise are used to build the control strategy model and vehicle model respectively,and the co-simulation under NEDC condition and compound condition is carried out.The simulation results show that the proposed control strategy has strong robustness.Under the Charge Sustain mode,the equivalent fuel consumption per 100 km is reduced by 13.2%and and 8.8%respectively,and the energy flowing through the battery is reduced by 8.9%and 5%,which is helpful to improve the cycle service life of the battery.

关 键 词：增程式电动汽车 控制策略 多目标遗传算法 等效燃油消耗 

分 类 号：U461.8[机械工程—车辆工程]