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Energy management strategies, control systems, and artificial intelligence-based algorithms development for hydrogen fuel cell-powered vehicles: A review

Hydrogen fuel cell electric vehicles (HFCEVs) are gaining revived attention due to the HFCEVs promising potential as important syndicates to net zero carbon emission attainment. However, HFCEVs' performance and cost-effectiveness do not yet match up with battery electric vehicles (BEVs) and tra...

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Main Authors:	Oladosu T.L., Pasupuleti J., Kiong T.S., Koh S.P.J., Yusaf T.
Other Authors:	57202498005
Format:	Review
Published:	Elsevier Ltd 2025
Subjects:	Control systems Cost effectiveness Energy management Energy management systems Fossil fuels Hydrogen fuels Reinforcement learning Algorithms development Carbon emissions Fuel cell electric vehicle Fuel-cell powered vehicles Hybridisation Hydrogen fuel cells Management strategies Multi objective System strategies Zero carbons Fuel cells
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id	my.uniten.dspace-36578
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spelling	my.uniten.dspace-365782025-03-03T15:43:11Z Energy management strategies, control systems, and artificial intelligence-based algorithms development for hydrogen fuel cell-powered vehicles: A review Oladosu T.L. Pasupuleti J. Kiong T.S. Koh S.P.J. Yusaf T. 57202498005 11340187300 57216824752 22951210700 23112065900 Control systems Cost effectiveness Energy management Energy management systems Fossil fuels Hydrogen fuels Reinforcement learning Algorithms development Carbon emissions Fuel cell electric vehicle Fuel-cell powered vehicles Hybridisation Hydrogen fuel cells Management strategies Multi objective System strategies Zero carbons Fuel cells Hydrogen fuel cell electric vehicles (HFCEVs) are gaining revived attention due to the HFCEVs promising potential as important syndicates to net zero carbon emission attainment. However, HFCEVs' performance and cost-effectiveness do not yet match up with battery electric vehicles (BEVs) and traditional fossil fuel vehicles despite many different Energy Management System (EMS) strategies previously adopted. Rule-based controls are still limited specifically in handling multi-objective systems as HFCEVs and some optimization-based algorithms also pose computational and retrofitting difficulties. Therefore, this study presents the prospect of artificial intelligence-based algorithms, control systems, and energy management strategies advances on HFCEVs performance optimization. EMS strategies; AI-based algorithms categories, functions and hybridization; the state-of-art and future direction of AI-based algorithms and HFCEVs? cost components amongst others are explained in the study. The multi-objective-based algorithm, reinforcement learning algorithm, and different hybridizations are enhancing HFCEVs cost-competing edge. ? 2024 Hydrogen Energy Publications LLC Final 2025-03-03T07:43:11Z 2025-03-03T07:43:11Z 2024 Review 10.1016/j.ijhydene.2024.02.284 2-s2.0-85187227450 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187227450&doi=10.1016%2fj.ijhydene.2024.02.284&partnerID=40&md5=ceec9c46ac0c287e84a68ef976f20875 https://irepository.uniten.edu.my/handle/123456789/36578 61 1380 1404 Elsevier Ltd Scopus
institution	Universiti Tenaga Nasional
building	UNITEN Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tenaga Nasional
content_source	UNITEN Institutional Repository
url_provider	http://dspace.uniten.edu.my/
topic	Control systems Cost effectiveness Energy management Energy management systems Fossil fuels Hydrogen fuels Reinforcement learning Algorithms development Carbon emissions Fuel cell electric vehicle Fuel-cell powered vehicles Hybridisation Hydrogen fuel cells Management strategies Multi objective System strategies Zero carbons Fuel cells
spellingShingle	Control systems Cost effectiveness Energy management Energy management systems Fossil fuels Hydrogen fuels Reinforcement learning Algorithms development Carbon emissions Fuel cell electric vehicle Fuel-cell powered vehicles Hybridisation Hydrogen fuel cells Management strategies Multi objective System strategies Zero carbons Fuel cells Oladosu T.L. Pasupuleti J. Kiong T.S. Koh S.P.J. Yusaf T. Energy management strategies, control systems, and artificial intelligence-based algorithms development for hydrogen fuel cell-powered vehicles: A review
description	Hydrogen fuel cell electric vehicles (HFCEVs) are gaining revived attention due to the HFCEVs promising potential as important syndicates to net zero carbon emission attainment. However, HFCEVs' performance and cost-effectiveness do not yet match up with battery electric vehicles (BEVs) and traditional fossil fuel vehicles despite many different Energy Management System (EMS) strategies previously adopted. Rule-based controls are still limited specifically in handling multi-objective systems as HFCEVs and some optimization-based algorithms also pose computational and retrofitting difficulties. Therefore, this study presents the prospect of artificial intelligence-based algorithms, control systems, and energy management strategies advances on HFCEVs performance optimization. EMS strategies; AI-based algorithms categories, functions and hybridization; the state-of-art and future direction of AI-based algorithms and HFCEVs? cost components amongst others are explained in the study. The multi-objective-based algorithm, reinforcement learning algorithm, and different hybridizations are enhancing HFCEVs cost-competing edge. ? 2024 Hydrogen Energy Publications LLC
author2	57202498005
author_facet	57202498005 Oladosu T.L. Pasupuleti J. Kiong T.S. Koh S.P.J. Yusaf T.
format	Review
author	Oladosu T.L. Pasupuleti J. Kiong T.S. Koh S.P.J. Yusaf T.
author_sort	Oladosu T.L.
title	Energy management strategies, control systems, and artificial intelligence-based algorithms development for hydrogen fuel cell-powered vehicles: A review
title_short	Energy management strategies, control systems, and artificial intelligence-based algorithms development for hydrogen fuel cell-powered vehicles: A review
title_full	Energy management strategies, control systems, and artificial intelligence-based algorithms development for hydrogen fuel cell-powered vehicles: A review
title_fullStr	Energy management strategies, control systems, and artificial intelligence-based algorithms development for hydrogen fuel cell-powered vehicles: A review
title_full_unstemmed	Energy management strategies, control systems, and artificial intelligence-based algorithms development for hydrogen fuel cell-powered vehicles: A review
title_sort	energy management strategies, control systems, and artificial intelligence-based algorithms development for hydrogen fuel cell-powered vehicles: a review
publisher	Elsevier Ltd
publishDate	2025
_version_	1825816066409889792
score	13.244109

Energy management strategies, control systems, and artificial intelligence-based algorithms development for hydrogen fuel cell-powered vehicles: A review

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