Battery and ultracapacitor in-the-loop approach to validate a real-time power management method for an all-climate electric vehicle
Battery and ultracapacitor in-the-loop approach to validate a real-time power management method for an all-climate electric vehicle
复制标题
DOI：
10.1016/j.apenergy.2018.02.128
复制
发表时间：
2018-05
期刊：
影响因子：
11.2
通讯作者：
R. Xiong;Yanzhou Duan;Jiayi Cao;Quanqing Yu
中科院分区：
文献类型：
--
作者：
R. Xiong;Yanzhou Duan;Jiayi Cao;Quanqing Yu
为了同时满足高比能量和高比功率的要求，延长储能系统在温度恶劣条件下的使用寿命，高比能量锂离子电池和高比功率超级电容器的多电源配置是全气候电动汽车（ACEV）的最佳选择。针对混合储能系统（HESS）的实时功率管理问题，系统地比较了基于规则、动态规划算法和实时强化学习算法的功率管理策略。为了验证控制策略的性能，搭建了基于xPC Target的半实物仿真试验平台。仿真结果表明，基于强化学习算法的实时电源管理策略具有上级的优越性。该策略可以降低电池组的充放电比，延长电池组的使用寿命，提高系统的效率。
In order to meet the requirements of high specific energy and high specific power together and extend the service life of the energy storage system in temperature abusive conditions, a multi-power configuration with high specific energy lithium-ion battery and high specific power ultracapacitor is the best choice for the all-climate electric vehicle (ACEV). Aiming at real-time power management of a hybrid energy storage system (HESS), three power management strategies, which are respectively based on rules, dynamic programming algorithm, and real-time reinforcement learning algorithm, have been systematically compared in this study. To verify the performance of the control strategies, the hardware-in-loop (HIL) simulation test platform based on xPC Target has been built. The results show that the real-time power management strategy based on reinforcement learning algorithm is superior to the others. This strategy can reduce the charge and discharge ratio of the battery pack, which extends the life of battery pack and improves the efficiency of the system.