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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS)
Kourab, Zakaria
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Hybrid fuel cell-supercapacitor system: modeling and energy management using Proteus Haidoury, Mohamed; Rachidi, Mohammed; El Hadraoui, Hicham; Laayatii, Oussama; Kourab, Zakaria; Tayane, Souad; Ennaji, Mohamed
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp110-128

Abstract

The increasing adoption of electric vehicles (EVs) presents a promising solution for achieving sustainable transportation and reducing carbon emissions. To keep pace with technological advancements in the vehicular industry, this paper proposes the development of a hybrid energy storage system (HESS) and an energy management strategy (EMS) for EVs, implemented using Proteus Spice Ver 8. The HESS consists of a proton exchange membrane fuel cell (PEMFC) as the primary source and a supercapacitor (SC) as the secondary source. The EMS, integrated into an electronic board based on the STM32, utilizes a low-pass filter algorithm to distribute energy between the sources. The accuracy of the proposed PEMFC and SC models is validated by comparing Proteus simulation results with experimental tests conducted on the Bahia didactic bench and Maxwell SC bench, respectively. To optimize energy efficiency, simulations of the HESS system involve adjusting the hybridization rate through changes in the cutoff frequency. The analysis compares the state-of-charge (SOC) of the SC and the voltage efficiency of the fuel cell (FC), across different frequencies to optimize overall system performance. The results highlight that the chosen strategy satisfies the energy demand while preserving the FC’s dynamic performance and optimizing its utilization to the maximum.
Development of a PEM fuel cell equivalent circuit model with PINN-based parameter identification Taleb, Ismail Ait; Kourab, Zakaria; Tayane, Souad; Ennaji, Mohamed; Gaber, Jaafar
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i4.pp2804-2818

Abstract

This paper presents a novel equivalent electrical circuit model for proton exchange membrane fuel cells (PEMFCs) and introduces a physics-informed neural network (PINN) algorithm for parameter identification. The proposed model provides a more accurate representation of the fuel cell’s dynamic behavior while maintaining computational efficiency. Unlike conventional methods, the PINN framework integrates physical constraints with data-driven learning, ensuring physically consistent parameter estimation. To validate its effectiveness, the proposed model is compared with the widely used RC equivalent circuit and a generic PEMFC model. Experimental data from a 1.2 kW PEMFC test bench serve as a benchmark for evaluating the transient and steady-state performance of each modeling approach. Results demonstrate that the proposed circuit, combined with PINN-based identification, yields enhanced accuracy in predicting voltage response under various operating conditions. Additionally, the model exhibits improved adaptability to transient phenomena compared to conventional equivalent circuits. These findings highlight the potential of physics-informed machine learning for advancing fuel cell modeling and control strategies.
Co-Authors El Hadraoui, Hicham Ennaji, Mohamed Gaber, Jaafar Haidoury, Mohamed Laayatii, Oussama Rachidi, Mohammed Taleb, Ismail Ait Tayane, Souad