Challenges in Energy Management for Fuel Cell Electric Vehicles
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "E: Electric Vehicles".
Deadline for manuscript submissions: 10 August 2026 | Viewed by 249
Special Issue Editors
2. Department of Electrical and Computer Engineering, e-TESC Lab, Université de Sherbrooke, Sherbrooke, QC, Canada
Interests: energy management strategy; fuel cell hybrid electric vehicle; online Identification; reinforcement learning; multi-agent systems
2. Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, VA, USA
Interests: modeling and control of nonlinear dynamic systems; adaptive and intelligent control theory; soft-computing and machine intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: fuel cell; energy storage; neural network; fuel cell hybrid electric vehicles
Special Issue Information
Dear Colleagues,
The transition toward sustainable mobility has placed Fuel Cell Electric Vehicles at the forefront of research, particularly for heavy-duty and long-range applications where battery-only solutions face limitations. Fuel Cell Electric Vehicles offer the compelling advantages of zero tailpipe emissions, high energy density, and short refueling times. However, the commercial viability and operational efficiency of these vehicles rely heavily on the sophistication of their powertrains, which typically hybridize a fuel cell stack with an energy storage system (such as a battery or supercapacitor).
The critical challenge in this domain lies in Energy Management Strategy. Effectively splitting power demand between the fuel cell and the auxiliary storage is essential to maximize hydrogen economy, ensure rapid dynamic response, and significantly prolong the lifespan of the fuel cell stack. As driving conditions vary and component degradation occurs over time, the demand for adaptive, intelligent, and robust control strategies becomes increasingly urgent.
This Special Issue aims to consolidate the latest academic and industrial findings regarding the optimization, control, and architecture of energy management in Fuel Cell Electric Vehicles. We invite submissions that address the theoretical and practical hurdles of making Fuel Cell Electric Vehicles more efficient, durable, and cost-effective.
Topics of interest for publication include, but are not limited to:
- Advanced Control Strategies: Model Predictive Control, Equivalent Consumption Minimization Strategy, and Rule-based optimization.
- AI and Machine Learning in Energy Management Strategy: Deep Reinforcement Learning and neural networks for adaptive real-time power splitting.
- Prognostics and Health Management: Integrating degradation models and state-of-health estimation into energy management to extend component life.
- Multi-objective Optimization: Balancing fuel economy, thermal constraints, and drivetrain durability.
- Hybrid Energy Storage Topologies: Architectures combining Fuel Cells with Batteries, Supercapacitors.
- Thermal Management Systems: Coupling thermal dynamics with electrical energy management.
- Hardware-in-the-Loop Validation: Real-time simulation and experimental validation of novel Energy Management Strategy strategies.
Dr. Razieh Ghaderi
Prof. Dr. Hicham Chaoui
Prof. Dr. Samir Jemeï
Guest Editors
Manuscript Submission Information
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Keywords
- fuel cell electric vehicle
- energy management strategy
- degradation
- fuel cell
- modeling
- fault diagnosis
- machine learning
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