强化学习
计算机科学
控制(管理)
工程类
控制工程
人工智能
作者
Jianghua Gan,Li Li,Xianke Lin,Xiaolin Tang
出处
期刊:IEEE Transactions on Vehicular Technology
[Institute of Electrical and Electronics Engineers]
日期:2024-01-01
卷期号:: 1-13
被引量:1
标识
DOI:10.1109/tvt.2024.3373906
摘要
The progress of artificial intelligence (AI) technology promotes the development of energy management research for hybrid electric vehicles (HEV). To explore the application of multi-agent deep reinforcement learning (DRL) algorithm in multi-objective cooperative control of HEVs, this article proposes a multi-objective cooperative control strategy based on the multi-agent deep deterministic policy gradient (MADDPG) algorithm for a four-wheel drive (4WD) HEV equipped with a hybrid energy storage system (HESS). Firstly, the parameters of the HESS of the 4WD HEV are matched. Secondly, the DRL-based regenerative braking control strategy and HESS power distribution strategy are designed. Thirdly, an HEV control method based on MADDPG is proposed, in which different agents are used for training different control strategies for cooperative control. The results show that the MADDPG-based multi-objective cooperative control strategy can achieve a better cooperative optimization effect than the single-agent DDPG-based multi-objective cooperative control strategy.
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