Research on Efficiency Optimization Based Energy Management Strategy for a Hybrid Electric Vehicle with Reinforcement Learning

被引：0
|
作者：
Yang N. [1 ]
Han L. [1 ,2 ]
Liu H. [1 ,2 ]
Zhang X. [3 ]
机构：
[1] School of Mechanical Engineering, Beijing Institute of Technology, Beijing
[2] Institute of Advanced Technology, Beijing Institute of Technology, Jinan
[3] China North Vehicle Research Institute, Beijing
来源：
Qiche Gongcheng/Automotive Engineering | 2021年 / 43卷 / 07期
关键词：
Efficiency optimization; Energy management strategy; Hybrid electric vehicle; Reinforcement learning;
D O I：
10.19562/j.chinasae.qcgc.2021.07.012
中图分类号：
学科分类号：
摘要：
Taking the power split hybrid electric vehicle as the object,this paper establishes the model for calculating the system comprehensive efficiency and proposes an efficiency optimization based energy management strategy with reinforcement learning. Firstly, the efficiency model of key components and the efficiency model of coupling mechanism are established. Based on the general structure of stepless speed regulation of composite transmission, the influence law of power splitting coefficient on the efficiency is analyzed, and the system comprehensive efficiency model is further constructed. Then with efficiency optimization as the goal, an energy management strategy based on reinforcement learning is proposed. Simulation comparisons are implemented, and the results show that the proposed strategy can achieve excellent fuel economy while maintaining battery SOC within a smaller fluctuation range. Finally, a test bench is built and the test results prove the correctness of the established efficiency model and the effectiveness of the proposed energy management strategy. © 2021, Society of Automotive Engineers of China. All right reserved.
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页码：1046 / 1056
页数：10
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