Parameter extraction of proton exchange membrane fuel cell based on artificial rabbits' optimization algorithm and conducting laboratory tests.

Faisal B Baz, Ragab A El Sehiemy, Ahmed S A Bayoumi, Amlak Abaza

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Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed

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1 citing paper in PubMed.

Modeling of solid oxide fuel cells and optimal parameter extraction at various operating data using an optimization method.PloS one · 2026
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Authors and funding

4 authors.

Faisal B BazMechanical Engineering Department, Faculty of Engineering, Kafrelsheikh University, Kafr El Sheikh, 33516, Egypt.

Ragab A El SehiemyElectrical Engineering Department, Faculty of Engineering, Kafrelsheikh University, Kafr El Sheikh, 33516, Egypt. elsehiemy@eng.kfs.edu.eg.

Ahmed S A BayoumiMathematical and Physics Engineering Department, Faculty of Engineering, Kafrelsheikh University, Kafr El Sheikh, 33516, Egypt.

Amlak AbazaElectrical Engineering Department, Faculty of Engineering, Kafrelsheikh University, Kafr El Sheikh, 33516, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Proton exchange membrane fuel cell (PEMFC) parameter extraction is an important issue in modeling and control of renewable energies. The PEMFC problem's main objective is to estimate the optimal value of unknown parameters of the electrochemical model. The main objective function of the optimization problem is the sum of the square errors between the measured voltages and output voltages of the proposed electrochemical optimized model at various loading conditions. Natural rabbit survival strategies such as detour foraging and random hiding are influenced by Artificial rabbit optimization (ARO). Meanwhile, rabbit energy shrink is mimicked to control the smooth switching from detour foraging to random hiding. In this work, the ARO algorithm is proposed to find the parameters of PEMFC. The ARO performance is verified using experimental results obtained from conducting laboratory tests on the fuel cell test system (SCRIBNER 850e, LLC). The simulation results are assessed with four competitive algorithms: Grey Wolf Optimization Algorithm, Particle Swarm Optimizer, Salp Swarm Algorithm, and Sine Cosine Algorithm. The comparison aims to prove the superior performance of the proposed ARO compared with the other well-known competitive algorithms.

Indexed as

Artificial rabbits optimisationExperimental testsOptimization modelParameter estimationProton exchange membrane fuel cell

Identifiers

PMID39256400

DOI10.1038/s41598-024-70886-6

PMCPMC11387624

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