基于TD3的电动汽车复合电源能量管理策略研究

TD3-based energy management strategy for hybrid energy storage system of electric vehicle

将蓄电池与超级电容组成复合电源系统并结合有效的能量管理策略,能显著提高能量利用率,延长储能系统的使用寿命。为了实现复合电源系统能耗损失的最小化,设计了一种基于双延迟深度确定性策略梯度(TD3)算法的能量管理策略。与深度确定性策略梯度(DDPG)算法相比,该算法解决了Q值过高估计问题,能耗损失更小。利用电动汽车行驶方程式和复合电源系统等效电路模型,搭建了基于TD3算法的MATLAB/Simulink仿真模型,并进行测试。仿真结果显示,所提出的能量管理策略能降低大电流对蓄电池的冲击,与DDPG算法相比,能量利用率提高了1.36%,蓄电池峰值电流输出降低了14.68%,蓄电池温升降低了3.52%,系统总能耗降低了2.17%。

Combining batteries and super capacitors into a composite power system(CPS)with an effective energy management strategy can significantly improve the energy utilization,and increase the service life of the energy storage system.To minimize the energy loss of the system,an energy management strategy based on the twin delayed deep deterministic policy gradient(TD3)algorithm was designed.Compared with the deep deterministic policy gradient(DDPG)algorithm,TD3 algorithm solved the problem of overestimation of Q value and less energy loss.A MATLAB/Simulink simulation model based on the TD3 algorithm was built,and tested with the electric vehicle driving equation and the equivalent circuit model of CPS.The outcomes indicate that the proposed energy management strategy can effectively reduce the impact of high current on the battery,and compared with DDPG algorithm,the energy utilization efficiency is improved by 1.36%,the peak of output current of the battery is reduced by 14.68%,the temperature rise of the battery is reduced by 3.52%,the total energy consumption of the system is reduced by 2.17%.