基于动态规划的增程式电动汽车优化控制  

Optimal control strategy of the extended-range electric vehicle based on dynamic programming

作　　者：张晓玲[1] 贝绍轶[1] 汪伟[1] 朱凯[1] 杭卫星[1] 

机构地区：[1]江苏理工学院汽车与交通工程学院,常州213001

出　　处：《现代制造工程》2016年第10期30-35,共6页Modern Manufacturing Engineering

基　　金：江苏省自然科学基金面上项目(BK2012586);江苏省"六大人才高峰"资助项目(ZBZZ-023);江苏省研究生科研创新计划项目(20820111435)

摘　　要：针对给定工况下增程式电动汽车燃料最优控制问题,提出了基于动态规划算法的全局优化控制策略。通过分析整车动力系统的能量流以及能源管理控制原理,建立了以蓄电池的荷电状态(State of Charge,SOC)为状态变量和发动机-发电机组成的增程器(Auxiliary Power Unit,APU)输出功率为控制变量的最优控制数学模型,并以油耗最低为目标函数,采用离散动态规划方法,建立动态规划递归方程,求解其最优控制策略。基于ADVISOR平台对整车进行仿真,仿真结果表明,与功率跟随式控制策略相比,基于动态规划的控制策略能够在蓄电池和APU之间合理地分配功率,可以有效提高增程式电动汽车的燃油经济性。An optimal control strategy based on the dynamic programming algorithm was proposed according the Extended-Range Electric Vehicle（E-REV） fuel consumption minimization problem over a fixed driving cycle. According to the analysis of energy flow of the power system and energy management control theory, optimal control mathematical model was built for the E-REV system. State Of Charge （SOC） of the battery are selected as the state variables and Auxiliary Power Unit （APU） as the control variables of the model respectively. Then,the lowest fuel consumption in the whole cycle was taken as the objective function of the mathematical model. By building its recursive equation, the discrete dynamic programming algorithm is utilized to compute the optimal control strategy. Then, a certain E-REV is simula, ed on the ADVISOR platform. Simulation showed that compared with based on the power-tracking control strategies, the energy management strategy based on the dynamic programming algorithm can reasonably distribute the energy between the APU and the battery, and can significantly increase the fuel economy of the E-REV.

关 键 词：增程式电动汽车 能源管理策略 动态规划算法 优化 

分 类 号：U461.2[机械工程—车辆工程]