Research on Energy Management Strategy of Electric Vehicle Hybrid System Based on Reinforcement Learning
From the perspective of energy management, the demand power of a hybrid electric vehicle driving under random conditions can be considered as a random process, and the Markov chain can be used for modeling. In this article, an energy management strategy based on reinforcement learning with real-time...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/11/13/1933 |
| _version_ | 1797480458606346240 |
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| author | Yu Cheng Ge Xu Qihong Chen |
| author_facet | Yu Cheng Ge Xu Qihong Chen |
| author_sort | Yu Cheng |
| collection | DOAJ |
| description | From the perspective of energy management, the demand power of a hybrid electric vehicle driving under random conditions can be considered as a random process, and the Markov chain can be used for modeling. In this article, an energy management strategy based on reinforcement learning with real-time updates is proposed to reasonably allocate the energy flow of the hybrid power system under unknown working conditions. The hybrid system is powered by a supercapacitor and a lithium battery, which uses the characteristics of each component to reduce the energy loss of the system, reduce the rate of change of the lithium battery current, and prolong the service life of the components. The strategy takes the change of the transition probability matrix under real-time working conditions as the basis. The system judges whether it is necessary to use the new transition probability to calculate and update the energy management strategy of the system by calculating the Pearson similarity between the transition probability matrix at the current time and previous time. The simulation results validate the proposed method. |
| first_indexed | 2024-03-09T22:00:20Z |
| format | Article |
| id | doaj.art-2bc26f6e6400439abad5161d66985e1d |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-09T22:00:20Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-2bc26f6e6400439abad5161d66985e1d2023-11-23T19:50:10ZengMDPI AGElectronics2079-92922022-06-011113193310.3390/electronics11131933Research on Energy Management Strategy of Electric Vehicle Hybrid System Based on Reinforcement LearningYu Cheng0Ge Xu1Qihong Chen2School of Automation, Wuhan University of Technology, Wuhan 430070, ChinaSchool of Automation, Wuhan University of Technology, Wuhan 430070, ChinaSchool of Automation, Wuhan University of Technology, Wuhan 430070, ChinaFrom the perspective of energy management, the demand power of a hybrid electric vehicle driving under random conditions can be considered as a random process, and the Markov chain can be used for modeling. In this article, an energy management strategy based on reinforcement learning with real-time updates is proposed to reasonably allocate the energy flow of the hybrid power system under unknown working conditions. The hybrid system is powered by a supercapacitor and a lithium battery, which uses the characteristics of each component to reduce the energy loss of the system, reduce the rate of change of the lithium battery current, and prolong the service life of the components. The strategy takes the change of the transition probability matrix under real-time working conditions as the basis. The system judges whether it is necessary to use the new transition probability to calculate and update the energy management strategy of the system by calculating the Pearson similarity between the transition probability matrix at the current time and previous time. The simulation results validate the proposed method.https://www.mdpi.com/2079-9292/11/13/1933hybrid electric systemenergy managementreinforcement learningQ-learning |
| spellingShingle | Yu Cheng Ge Xu Qihong Chen Research on Energy Management Strategy of Electric Vehicle Hybrid System Based on Reinforcement Learning Electronics hybrid electric system energy management reinforcement learning Q-learning |
| title | Research on Energy Management Strategy of Electric Vehicle Hybrid System Based on Reinforcement Learning |
| title_full | Research on Energy Management Strategy of Electric Vehicle Hybrid System Based on Reinforcement Learning |
| title_fullStr | Research on Energy Management Strategy of Electric Vehicle Hybrid System Based on Reinforcement Learning |
| title_full_unstemmed | Research on Energy Management Strategy of Electric Vehicle Hybrid System Based on Reinforcement Learning |
| title_short | Research on Energy Management Strategy of Electric Vehicle Hybrid System Based on Reinforcement Learning |
| title_sort | research on energy management strategy of electric vehicle hybrid system based on reinforcement learning |
| topic | hybrid electric system energy management reinforcement learning Q-learning |
| url | https://www.mdpi.com/2079-9292/11/13/1933 |
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