Optimizing Hybrid Electric Vehicle Performance: A Detailed Overview of Energy Management Strategies
Rising greenhouse gas emissions stemming from road transport have intensified the need for efficient and environmentally friendly propulsion technologies. Hybrid and fuel cell electric vehicles have emerged as a viable solution, integrating internal combustion engines and fuel cells with electric mo...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/1/10 |
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| _version_ | 1841549261983973376 |
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| author | Álvaro Gómez-Barroso Iban Vicente Makazaga Ekaitz Zulueta |
| author_facet | Álvaro Gómez-Barroso Iban Vicente Makazaga Ekaitz Zulueta |
| author_sort | Álvaro Gómez-Barroso |
| collection | DOAJ |
| description | Rising greenhouse gas emissions stemming from road transport have intensified the need for efficient and environmentally friendly propulsion technologies. Hybrid and fuel cell electric vehicles have emerged as a viable solution, integrating internal combustion engines and fuel cells with electric motors to optimize fuel efficiency and reduce emissions. This article reviews and analyzes energy management strategies for the principal powertrain topologies of hybrid electric vehicles, focusing on achieving solution optimality in real-time applications. A thorough and comprehensive overview of rule-based, optimization-based, and learning-based energy management strategies is presented, highlighting their main attributes and providing a comparative analysis in terms of fuel economy improvements, real-time implementation feasibility, and computational complexity, while simultaneously identifying and uncovering areas requiring further research in the field. We found that while rule-based methods offer simplicity and real-time capability, their adaptability remains limited. Optimization-based and learning-based approaches, although often achieving near-optimal solutions, face challenges due to their high computational demands and integration complexities. Our analysis also revealed the importance of leveraging vehicle connectivity and intelligent transportation systems for future energy management developments, which will contribute to broader sustainability goals in the automotive sector. |
| format | Article |
| id | doaj-art-4330344529934987b90ad3479619cc2a |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-4330344529934987b90ad3479619cc2a2025-01-10T13:16:49ZengMDPI AGEnergies1996-10732024-12-011811010.3390/en18010010Optimizing Hybrid Electric Vehicle Performance: A Detailed Overview of Energy Management StrategiesÁlvaro Gómez-Barroso0Iban Vicente Makazaga1Ekaitz Zulueta2Tecnalia Research & Innovation, 48160 Derio, SpainTecnalia Research & Innovation, 48160 Derio, SpainSystem Engineering and Automation Control Department, Faculty of Engineering of Vitoria-Gasteiz, University of the Basque Country (UPV/EHU), 01006 Vitoria-Gasteiz, SpainRising greenhouse gas emissions stemming from road transport have intensified the need for efficient and environmentally friendly propulsion technologies. Hybrid and fuel cell electric vehicles have emerged as a viable solution, integrating internal combustion engines and fuel cells with electric motors to optimize fuel efficiency and reduce emissions. This article reviews and analyzes energy management strategies for the principal powertrain topologies of hybrid electric vehicles, focusing on achieving solution optimality in real-time applications. A thorough and comprehensive overview of rule-based, optimization-based, and learning-based energy management strategies is presented, highlighting their main attributes and providing a comparative analysis in terms of fuel economy improvements, real-time implementation feasibility, and computational complexity, while simultaneously identifying and uncovering areas requiring further research in the field. We found that while rule-based methods offer simplicity and real-time capability, their adaptability remains limited. Optimization-based and learning-based approaches, although often achieving near-optimal solutions, face challenges due to their high computational demands and integration complexities. Our analysis also revealed the importance of leveraging vehicle connectivity and intelligent transportation systems for future energy management developments, which will contribute to broader sustainability goals in the automotive sector.https://www.mdpi.com/1996-1073/18/1/10energy management strategieshybrid electric vehiclesfuel cell hybrid electric vehiclesoptimizationreal-time controlfuel economy |
| spellingShingle | Álvaro Gómez-Barroso Iban Vicente Makazaga Ekaitz Zulueta Optimizing Hybrid Electric Vehicle Performance: A Detailed Overview of Energy Management Strategies Energies energy management strategies hybrid electric vehicles fuel cell hybrid electric vehicles optimization real-time control fuel economy |
| title | Optimizing Hybrid Electric Vehicle Performance: A Detailed Overview of Energy Management Strategies |
| title_full | Optimizing Hybrid Electric Vehicle Performance: A Detailed Overview of Energy Management Strategies |
| title_fullStr | Optimizing Hybrid Electric Vehicle Performance: A Detailed Overview of Energy Management Strategies |
| title_full_unstemmed | Optimizing Hybrid Electric Vehicle Performance: A Detailed Overview of Energy Management Strategies |
| title_short | Optimizing Hybrid Electric Vehicle Performance: A Detailed Overview of Energy Management Strategies |
| title_sort | optimizing hybrid electric vehicle performance a detailed overview of energy management strategies |
| topic | energy management strategies hybrid electric vehicles fuel cell hybrid electric vehicles optimization real-time control fuel economy |
| url | https://www.mdpi.com/1996-1073/18/1/10 |
| work_keys_str_mv | AT alvarogomezbarroso optimizinghybridelectricvehicleperformanceadetailedoverviewofenergymanagementstrategies AT ibanvicentemakazaga optimizinghybridelectricvehicleperformanceadetailedoverviewofenergymanagementstrategies AT ekaitzzulueta optimizinghybridelectricvehicleperformanceadetailedoverviewofenergymanagementstrategies |