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Precise modeling of PEM fuel cell using a novel Enhanced Transient Search Optimization algorithm

dc.contributor.authorHasanien, Hany M.
dc.contributor.authorShaheen, Mohamed A.M.
dc.contributor.authorTurky, Rania A.
dc.contributor.authorQais, Mohammed H.
dc.contributor.authorAlghuwainem, Saad
dc.contributor.authorKamel, Salah
dc.contributor.authorTostado-Véliz, Marcos
dc.contributor.authorJurado, Francisco
dc.date.accessioned2024-12-02T08:32:43Z
dc.date.available2024-12-02T08:32:43Z
dc.date.issued2022-05-15
dc.description.abstractThis paper introduces a novel enhancement to the Transient Search Optimization (TSO) algorithm to estimate an accurate electrical model of the proton exchange membrane fuel cell (PEMFC). The PEMEFC model is a non-linear model that includes seven unknown variables which cannot be calculated analytically. The TSO is enhanced by inserting two new factors, the Levy function and the Weibull distribution function. The proposed enhanced Transient Search Optimization (ETSO) and TSO algorithms are applied to estimate the seven variables by minimizing the sum of the squared errors (SSEs) between the measured and calculated voltages. The error is defined as the difference between the measured and the calculated output voltage of the PEMFC. Three different commercial types of PEMFCs are modeled: i) Ballard, Mark V 5 kW, ii) Horizon H-12, and iii) 6 kW Nedstack PS6 stacks PEMFC. The estimated seven variables and the minimum SSE of electrical PEMFCs using ETSO and TSO algorithms are compared with the results obtained by using other optimization algorithms like whale optimization algorithm, genetic algorithm, neural network algorithm and others. The results obtained by the ETSO are better than that obtained by TSO by more than 10% and this percentage increases with other algorithms. The accuracy of the proposed PEMFC model is verified by comparing the estimated V–I and P–I characteristics with the measured data. The effectiveness of the proposed ETSO based model is verified by an investigation of sensitivity analysis for design variables and the robustness of the ETSO algorithm via the statistical analysis and the parametric t-test.es_ES
dc.identifier.citationHany M. Hasanien, Mohamed A.M. Shaheen, Rania A. Turky, Mohammed H. Qais, Saad Alghuwainem, Salah Kamel, Marcos Tostado-Véliz, Francisco Jurado, Precise modeling of PEM fuel cell using a novel Enhanced Transient Search Optimization algorithm, Energy, Volume 247, 2022, 123530, ISSN 0360-5442, https://doi.org/10.1016/j.energy.2022.123530.es_ES
dc.identifier.issn0360-5442es_ES
dc.identifier.other10.1016/j.energy.2022.123530es_ES
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S0360544222004339es_ES
dc.identifier.urihttps://hdl.handle.net/10953/3445
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relation.ispartofEnergy [2022]; [247]: [123530]es_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectEnergy system modelinges_ES
dc.subjectFuel cellses_ES
dc.subjectHydrogen energyes_ES
dc.subjectOptimization methodses_ES
dc.subjectParameter extractiones_ES
dc.titlePrecise modeling of PEM fuel cell using a novel Enhanced Transient Search Optimization algorithmes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.type.versioninfo:eu-repo/semantics/acceptedVersiones_ES

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