Jul 2026· Journal of Control Automation and Electrical Systems· 0 citations· 20 references
Abstract
In this paper, a real-time optimized sigmoid-based energy management system (EMS) is proposed for a fuel cell hybrid vehicle (FCHV). The power demand is dynamically shared among the fuel cell, a lithium-ion battery (LIB), and an ultracapacitor. The sigmoid function is employed to regulate the full cell operation, ensuring higher efficiency. A real-time particle swarm optimization (RT-PSO) algorithm defines both the power distribution and the ultracapacitor frequency response in a multi-objective framework that accounts for source degradation, fuel consumption, and power losses, without relying on prior knowledge of the driving cycle. To reduce computational complexity, the optimization is executed at fixed time steps. Numerical results demonstrate the enhanced performance and real-time feasibility of the proposed strategy, increasing LIB lifetime by factors of 1.41 and 1.74 compared to global and non-optimized strategies, respectively, while reducing operational costs by 16.5% and 27.4%. These results confirm that the proposed EMS is a suitable real-time solution with optimal performance and low computational burden.
The energy management strategy (EMS) of fuel cell hybrid electric vehicles (FCHEVs) plays an important role in determining both hydrogen economy and the state-of-charge (SOC) regulation and prevention of over-charge/discharge. Existing fuzzy logic-based EMS typically employs a single fuzzy logic controller with fixed S...
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L. Grisales-Noreña, V. M. Garrido Arevalo, O. Montoya· 2026 IEEE Colombian Conferen...· 0 citations
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