An Energy Management Strategy for Hybrid Energy Storage System Based on Reinforcement Learning

被引:3
|
作者
Wang, Yujie [1 ,2 ]
Li, Wenhuan [1 ]
Liu, Zeyan [1 ]
Li, Ling [1 ]
机构
[1] Univ Sci & Technol China, Sch Informat Sci & Technol, Hefei 230027, Peoples R China
[2] Hefei Comprehens Natl Sci Ctr, Inst Artificial Intelligence, Hefei 230027, Peoples R China
来源
WORLD ELECTRIC VEHICLE JOURNAL | 2023年 / 14卷 / 03期
关键词
hybrid energy storage system; energy management strategy; system modeling; speed prediction; reinforcement learning; ELECTRIC VEHICLE; BATTERY; OPTIMIZATION;
D O I
10.3390/wevj14030057
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Due to the continuous high traction power impact on the energy storage medium, it is easy to cause many safety risks during the driving process, such as triggering the aging mechanism, causing rapid deterioration of the battery performance during the driving process and even triggering thermal runaway. Hybrid energy storage is an effective way to solve this problem. The ultracapacitor is an energy storage device that has high power density, which can withstand high instantaneous currents and can be charged and discharged quickly. By combining batteries and ultracapacitors in a hybrid energy storage system, energy sources with different characteristics can be combined to take advantage of their respective strengths and increase the efficiency and lifetime of the system. The energy management strategy plays an important role in the performance of hybrid energy storage systems. Traditional optimization algorithms have difficulty improving the flexibility and practicality of applications. In this paper, an energy management strategy based on reinforcement learning is proposed. The results indicate that the proposed reinforcement method can effectively distribute the charging and discharging conditions of the power supply and maintain the SOC of the battery and, at the same time, meet the power demand of working conditions at the cost of less energy loss and effectively realize the goal of optimizing the overall efficiency and effective energy management strategy.
引用
收藏
页数:15
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