基于TD3的电动汽车复合电源能量管理策略研究

刘家成; 张向文

doi:10.11959/j.issn.2096-6652.202230

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基于TD3的电动汽车复合电源能量管理策略研究

学术论文 | 更新时间：2024-06-05

- 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
- 智能科学与技术学报 2022年4卷第2期页码：277-287
- 作者机构：
  
  1. 桂林电子科技大学电子工程与自动化学院，广西桂林 541004
  2. 广西自动检测技术与仪器重点实验室，广西桂林 541004
- 作者简介：
  
  [ "刘家成（1995− ），男，桂林电子科技大学电子工程与自动化学院硕士生，主要研究方向为汽车电子、电动汽车能量管理" ]
  [ "张向文（1976− ），男，博士，桂林电子科技大学电子工程与自动化学院研究员，主要研究方向为电动汽车能量管理、动力电池管理系统、电动汽车再生制动控制" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(51465100);广西自然科学基金资助项目;The Natural Science Foundation of Guangxi(2018GXNSFAA281282);广西自动检测技术与仪器重点实验室基金资助项目;The Key Laboratory of Automatic Detection Technology and Instrumentation Foundation of Guangxi(YQ17110);桂林电子科技大学研究生教育创新计划资助项目;Graduate Education Innovation Program of Guilin University of Electronic Technology(2021YCXS120)
- DOI：10.11959/j.issn.2096-6652.202230
  中图分类号： U469.72
- 网络出版日期：2022-06，
  
  纸质出版日期：2022-06-15
- 稿件说明：
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刘家成, 张向文. 基于TD3的电动汽车复合电源能量管理策略研究[J]. 智能科学与技术学报, 2022,4(2):277-287.

Jiacheng LIU, Xiangwen ZHANG. TD3-based energy management strategy for hybrid energy storage system of electric vehicle[J]. Chinese journal of intelligent science and technology, 2022, 4(2): 277-287.
刘家成, 张向文. 基于TD3的电动汽车复合电源能量管理策略研究[J]. 智能科学与技术学报, 2022,4(2):277-287. DOI： 10.11959/j.issn.2096-6652.202230.

Jiacheng LIU, Xiangwen ZHANG. TD3-based energy management strategy for hybrid energy storage system of electric vehicle[J]. Chinese journal of intelligent science and technology, 2022, 4(2): 277-287. DOI： 10.11959/j.issn.2096-6652.202230.

摘要

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%。

Abstract

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%.

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references

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