Comprehensive optimization of fuzzy logic-based energy management system for fuel-cell hybrid electric vehicle using genetic algorithm

International Journal of Hydrogen Energy, Год журнала: 2024, Номер 81, С. 889 - 905

Опубликована: Июль 26, 2024

Язык: Английский

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Combining proportional integral and fuzzy logic control strategies to improve performance of energy management of fuel cell electric vehicles

International Journal of Thermofluids, Год журнала: 2025, Номер unknown, С. 101076 - 101076

Опубликована: Янв. 1, 2025

Язык: Английский

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Energy transition towards electric vehicle technology: Recent advancements

Energy Reports, Год журнала: 2025, Номер 13, С. 2958 - 2996

Опубликована: Фев. 28, 2025

Язык: Английский

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Fuel efficiency through co-optimization of speed planning and energy management in intelligent fuel cell electric vehicles

International Journal of Hydrogen Energy, Год журнала: 2025, Номер 126, С. 9 - 21

Опубликована: Апрель 8, 2025

Язык: Английский

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Multi-objective adaptive energy management strategy for fuel cell hybrid electric vehicles considering fuel cell health state

Applied Thermal Engineering, Год журнала: 2024, Номер 257, С. 124270 - 124270

Опубликована: Авг. 30, 2024

Язык: Английский

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Energy-Oriented Hybrid Cooperative Adaptive Cruise Control for Fuel Cell Electric Vehicle Platoons

Sensors, Год журнала: 2024, Номер 24(15), С. 5065 - 5065

Опубликована: Авг. 5, 2024

Given the complex powertrain of fuel cell electric vehicles (FCEVs) and diversified vehicle platooning synergy constraints, a control strategy that simultaneously considers inter-vehicle energy economy is one key technologies to improve transportation efficiency release energy-saving potential vehicles. In this paper, an energy-oriented hybrid cooperative adaptive cruise (eHCACC) proposed for FCEV platoon, aiming enhance while ensuring stable car-following performance. The eHCACC employs architecture, consisting top-level centralized controller (TCC) bottom-level distributed controllers (BDCs). TCC integrates eco-driving CACC (eCACC) based on minimum principle random forest, which generates optimal reference velocity datasets by aligning comprehensive objectives platoon addressing performance economic platoon. Concurrently, further unleash potential, BDCs utilize equivalent consumption minimization (ECMS) determine inputs combining with detailed optimization information system states components. A series simulation evaluations highlight improved stability

Язык: Английский

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Empowering Fuel Cell Electric Vehicles Towards Sustainable Transportation: An Analytical Assessment, Emerging Energy Management, Key Issues, and Future Research Opportunities

World Electric Vehicle Journal, Год журнала: 2024, Номер 15(11), С. 484 - 484

Опубликована: Окт. 26, 2024

Fuel cell electric vehicles (FCEVs) have received significant attention in recent times due to various advantageous features, such as high energy efficiency, zero emissions, and extended driving range. However, FCEVs some drawbacks, including production costs; limited hydrogen refueling infrastructure; the complexity of converters, controllers, method execution. To address these challenges, smart management involving appropriate intelligent algorithms, optimizations is essential for enhancing effectiveness towards sustainable transportation. Therefore, this paper presents emerging strategies improve system reliability, overall performance. In context, a comprehensive analytical assessment conducted examine several factors, research trends, types publications, citation analysis, keyword occurrences, collaborations, influential authors, countries conducting area. Moreover, schemes are investigated, with focus on optimization techniques, control strategies, highlighting contributions, key findings, issues, gaps. Furthermore, state-of-the-art domains thoroughly discussed order explore domains, relevant outcomes, existing challenges. Additionally, addresses open issues challenges offers valuable future opportunities advancing FCEVs, emphasizing importance suitable techniques enhance their The outcomes findings review will be helpful researchers automotive engineers developing advanced methods, schemes, greener

Язык: Английский

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An Adaptive Energy Management Strategy for Off-Road Hybrid Tracked Vehicles

Energies, Год журнала: 2025, Номер 18(6), С. 1371 - 1371

Опубликована: Март 11, 2025

Conventional energy management strategies based on reinforcement learning often fail to achieve their intended performance when applied driving conditions that significantly deviate from training conditions. Therefore, the conventional reinforcement-learning-based strategy is not suitable for complex off-road This research suggests an hybrid tracked vehicles operating in adaptive learning. Power demand described using a Markov chain model updated online recursive way. The technique updates MC and recalculates algorithm intrinsic matrix norm (IMN) as criteria. According simulation results, suggested method can increase adaptability of conditions, evidenced by 7.66% reduction equivalent fuel consumption compared with Q-learning strategy.

Язык: Английский

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Assessment of hydrogen vehicle fuel economy using MRAC based on deep learning

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Апрель 16, 2025

Язык: Английский

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Adaptive Energy Optimization Based on Fuel Cell Degradation Prediction for Fuel Cell Hybrid Electric Vehicles

Опубликована: Янв. 1, 2025

Язык: Английский

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