Khalatbarisoltani, A., Zhou, H., Tang, X., Kandidayeni, M., Boulon, L. et Hu, X. (2023). Energy management strategies for fuel cell vehicles: A comprehensive review of the latest progress in modeling, strategies, and future prospects. IEEE Transactions on Intelligent Transportation Systems . ISSN 1524-9050 1558-0016 DOI 10.1109/TITS.2023.3309052
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Résumé
Fuel cell vehicles (FCVs) are considered a promising solution for reducing emissions caused by the transportation sector. An energy management strategy (EMS) is undeniably essential in increasing hydrogen economy, component lifetime, and driving range. While the existing EMSs provide a range of performance levels, they suffer from significant shortcomings in robustness, durability, and adaptability, which prohibit the FCV from reaching its full potential in the vehicle industry. After introducing the fundamental EMS problem, this review article provides a detailed description of the FCV powertrain system modeling, including typical modeling, degradation modeling, and thermal modeling, for designing an EMS. Subsequently, an in-depth analysis of various EMS evolutions, including rule-based and optimization-based, is carried out, along with a thorough review of the recent advances. Unlike similar studies, this paper mainly highlights the significance of the latest contributions, such as advanced control theories, optimization algorithms, artificial intelligence (AI), and multi-stack fuel cell systems (MFCSs). Afterward, the verification methods of EMSs are classified and summarized. Ultimately, this work illuminates future research directions and prospects from multi-disciplinary standpoints for the first time. The overarching goal of this work is to stimulate more innovative thoughts and solutions for improving the operational performance, efficiency, and safety of FCV powertrains.
Type de document: | Article |
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Date de dépôt: | 25 sept. 2023 14:50 |
Dernière modification: | 25 sept. 2023 14:50 |
Version du document déposé: | Post-print (version corrigée et acceptée) |
URI: | https://depot-e.uqtr.ca/id/eprint/10866 |
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