Research and Comparative Analysis of Energy Management Strategies for Hybrid Electric Vehicles: A Review
Hybrid electric vehicles have received more and more attention owing to energy saving and environmental protection. Optimized energy-management strategies are critical to improve vehicle energy efficiency and reduce the emissions of hybrid electric vehicles. This study summarized the research status...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/11/2873 |
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| author | Fan Wang Yina Hong Xiaohuan Zhao |
| author_facet | Fan Wang Yina Hong Xiaohuan Zhao |
| author_sort | Fan Wang |
| collection | DOAJ |
| description | Hybrid electric vehicles have received more and more attention owing to energy saving and environmental protection. Optimized energy-management strategies are critical to improve vehicle energy efficiency and reduce the emissions of hybrid electric vehicles. This study summarized the research status of energy-management strategies for hybrid electric vehicles and analyzed the energy allocation and modeling methods of hybrid power systems. The principles, advantages, and limitations of rule-based and optimized and learning-based energy-management strategies were compared. It is found that the optimized energy-management strategies can improve fuel economy by approximately 6% compared with the rule-based energy-management strategies. The learning-based energy-management strategies can reduce fuel consumption by about 5.2~17%. This study can provide a theoretical basis and practical guidance for the efficient design and optimization of hybrid electric vehicle energy-management systems, which can promote the development and application of related technologies. |
| format | Article |
| id | doaj-art-7681cccddb7b44e68e92c1e0032a14a9 |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-7681cccddb7b44e68e92c1e0032a14a92025-08-20T03:46:46ZengMDPI AGEnergies1996-10732025-05-011811287310.3390/en18112873Research and Comparative Analysis of Energy Management Strategies for Hybrid Electric Vehicles: A ReviewFan Wang0Yina Hong1Xiaohuan Zhao2Energy and Electricity Research Center, International Energy College, Zhuhai Campus, Jinan University, Zhuhai 519070, ChinaEnergy and Electricity Research Center, International Energy College, Zhuhai Campus, Jinan University, Zhuhai 519070, ChinaEnergy and Electricity Research Center, International Energy College, Zhuhai Campus, Jinan University, Zhuhai 519070, ChinaHybrid electric vehicles have received more and more attention owing to energy saving and environmental protection. Optimized energy-management strategies are critical to improve vehicle energy efficiency and reduce the emissions of hybrid electric vehicles. This study summarized the research status of energy-management strategies for hybrid electric vehicles and analyzed the energy allocation and modeling methods of hybrid power systems. The principles, advantages, and limitations of rule-based and optimized and learning-based energy-management strategies were compared. It is found that the optimized energy-management strategies can improve fuel economy by approximately 6% compared with the rule-based energy-management strategies. The learning-based energy-management strategies can reduce fuel consumption by about 5.2~17%. This study can provide a theoretical basis and practical guidance for the efficient design and optimization of hybrid electric vehicle energy-management systems, which can promote the development and application of related technologies.https://www.mdpi.com/1996-1073/18/11/2873hybrid electric vehiclesenergy management strategyhybrid power systemrule-based strategyoptimized strategylearning strategy |
| spellingShingle | Fan Wang Yina Hong Xiaohuan Zhao Research and Comparative Analysis of Energy Management Strategies for Hybrid Electric Vehicles: A Review Energies hybrid electric vehicles energy management strategy hybrid power system rule-based strategy optimized strategy learning strategy |
| title | Research and Comparative Analysis of Energy Management Strategies for Hybrid Electric Vehicles: A Review |
| title_full | Research and Comparative Analysis of Energy Management Strategies for Hybrid Electric Vehicles: A Review |
| title_fullStr | Research and Comparative Analysis of Energy Management Strategies for Hybrid Electric Vehicles: A Review |
| title_full_unstemmed | Research and Comparative Analysis of Energy Management Strategies for Hybrid Electric Vehicles: A Review |
| title_short | Research and Comparative Analysis of Energy Management Strategies for Hybrid Electric Vehicles: A Review |
| title_sort | research and comparative analysis of energy management strategies for hybrid electric vehicles a review |
| topic | hybrid electric vehicles energy management strategy hybrid power system rule-based strategy optimized strategy learning strategy |
| url | https://www.mdpi.com/1996-1073/18/11/2873 |
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