Maximum power point tracking in fuel cells an AI controller based on metaheuristic optimisation DOI Creative Commons

P.M. Preethiraj,

J. Belwin Edward

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Dec. 30, 2024

Language: Английский

Fast and accurate estimation of PEMFCs model parameters using a dimension learning-based modified grey wolf metaheuristic algorithm DOI
Salem Saidi, Rabeh Abbassi, M. Premkumar

et al.

Measurement, Journal Year: 2025, Volume and Issue: unknown, P. 116917 - 116917

Published: Feb. 1, 2025

Language: Английский

Citations

2
Robust parameter estimation of proton exchange membrane fuel cell using Huber loss statistical function DOI

Bahaa Saad,

Ragab A. El‐Sehiemy, Hany M. Hasanien

et al.

Energy Conversion and Management, Journal Year: 2024, Volume and Issue: 323, P. 119231 - 119231

Published: Nov. 11, 2024

Language: Английский

Citations

7
Optimization of material-energy Co-management in a proton exchange membrane fuel cell DOI
Shengping Li, Huali Zhao, Yuhan Huang

et al.

International Journal of Hydrogen Energy, Journal Year: 2025, Volume and Issue: 101, P. 391 - 402

Published: Jan. 1, 2025

Language: Английский

Citations

1
Optimizing parameter extraction in proton exchange membrane fuel cell models via differential evolution with dynamic crossover strategy DOI
Driss Saadaoui, Mustapha Elyaqouti, Imade Choulli

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 135397 - 135397

Published: March 1, 2025

Language: Английский

Citations

1
An efficient framework for proton exchange membrane fuel cell parameter estimation using numerous MH algorithms DOI
Asmita Ajay Rathod, Pankaj Sharma, Arun Choudhary

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2025, Volume and Issue: 216, P. 115603 - 115603

Published: April 8, 2025

Language: Английский

Citations

1
Parameters optimization of PEMFC model based on gazelle optimization algorithm DOI
Sofiane Haddad, M. Benghanem,

Belqees Hassan

et al.

International Journal of Hydrogen Energy, Journal Year: 2024, Volume and Issue: 87, P. 214 - 226

Published: Sept. 7, 2024

Language: Английский

Citations

5
A novel leaf bionic flow field with structured multi-level channel based on Murray's law in proton exchange membrane fuel cell for enhanced mass transfer DOI

Zongming Huang,

Yuan Chen, Weidong Wu

et al.

Physics of Fluids, Journal Year: 2024, Volume and Issue: 36(11)

Published: Nov. 1, 2024

The design of flow field has a significant impact on the performance proton exchange membrane fuel cells (PEMFCs). In this study, novel leaf bionic is designed and optimized based Murray's law. power consumption ratio first used in PEMFC. Additionally, an evaluation criterion, mass transfer efficiency criterion (MTEEC), proposed to characterize efficiency, synergy theory analyze differences among various fields. results demonstrate that adding multi-level channel obstacles significantly enhances cell output reduces voltage losses regions. Applying law distribute improves uniformity oxygen concentration distribution alleviates under-rib water accumulation. Compared secondary stream (SSFF), structure mesh (SMLBFF) demonstrates nearly 19% increase current density at 0.45 V. SMLBFF exhibits 81.51% convective rate compared SSFF 0.4 Moreover, MTEEC shows improvements 179.68% 0.5 A/cm2 135.43% 1.0 A/cm2, SSFF.

Language: Английский

Citations

4
SOFCs integrated with SMES under dynamic power control using Chernobyl disaster optimizer DOI Creative Commons
Sameh I. Selem, Attia A. El‐Fergany, Eid Gouda

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 24, 2025

Language: Английский

Citations

0
A novel Parrot Optimizer for robust and scalable PEMFC parameter optimization DOI Creative Commons
Mohammad Aljaidi, Pradeep Jangir,

Arpita Arpita

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 4, 2025

The use of proton exchange membrane fuel cells (PEMFCs) in sustainable energy applications depends on their high efficiency levels along with ability to produce low emissions and operation without noise. optimization PEMFC design variables faces difficulties because the complex nonlinear relationships which exist between activation overpotential concentration internal resistance. methods PSO, DE WOA face three major setbacks include delayed convergence rates as well sensitiveness initial parameter settings tendency lock onto sub-optimal solutions. study presents Parrot Optimizer (PO) a new metaheuristic algorithm derives its inspiration from adaptive behaviors Pyrrhura Molinae parrots overcome current challenges. PO serves optimize six stack for BCS 500 W, Nedstack 600 W PS6, SR-12 Horizon H-12, Ballard Mark V, STD 250 W. research performs an extensive comparison nine advanced algorithms analyze performance against DE, WOA, Rabbit Optimization Algorithm (ROA), Flamingo Herd (FHO), Arithmetic (AOA), Sine Cosine (SCA), Multi-Verse (MVO) Bat (BA). objective function Sum Squared Error (SSE) voltage is minimized using different comparative analysis. Simulation results I-V V-P characteristics aligned closely experimental data under varying temperature pressure conditions. achieved lowest Mean SSE values across all cases, 0.025519, 0.275211, 0.242413, 0.102915, 0.148632, 0.283774 stacks, respectively. Additionally, demonstrated fastest runtime (RT) 0.116855 s H-12 stack. indicate that delivers better than existing it reaches outputs every test scenario. characteristic simulations match proves theoretical value practical usage solving problems. demonstrates dependable method improves processes while enhancing operational reliability through future includes real-time control combination system scalability.

Language: Английский

Citations

0
Identifying the unknown parameters of PEM fuel cells based on a human-inspired optimization algorithm DOI
Badis Lekouaghet, Mohammed Haddad, M. Benghanem

et al.

International Journal of Hydrogen Energy, Journal Year: 2025, Volume and Issue: 129, P. 222 - 235

Published: April 25, 2025

Language: Английский

Citations

0