000117417 001__ 117417
000117417 005__ 20240319080956.0
000117417 0247_ $$2doi$$a10.1016/j.ijhydene.2021.11.084
000117417 0248_ $$2sideral$$a127306
000117417 037__ $$aART-2022-127306
000117417 041__ $$aeng
000117417 100__ $$aLosantos R.
000117417 245__ $$aParameter characterization of HTPEMFC using numerical simulation and genetic algorithms
000117417 260__ $$c2022
000117417 5060_ $$aAccess copy available to the general public$$fUnrestricted
000117417 5203_ $$aThis paper develops a novel approach to the parameterisation of high temperature exchange membrane fuel cells (HTPEMFC) with limited and non-invasive measurements. The proposed method allows an effective identification of electrochemical parameters for three-dimensional fuel cell models by combining computational simulation tools and genetic algorithms. To avoid each evaluation undertaken by the optimisation method involving a complete computational simulation of the 3D model, a strategy has been designed that, thanks to an iterative process, makes it possible to decouple the fluid dynamic resolution from the electrochemistry one. Two electrochemical models have been incorporated into these tools to describe the behaviour of the catalyst layer, Butler-Volmer and spherical aggregate. For each one, a case study has been carried out to validate the results by comparing them with empirical data in the first model and with data generated by numerical simulation in the second. Results show that, from a set of measured operating conditions, it is possible to identify a unique set of electrochemical parameters that fits the 3D model to the target polarisation curve. The extension of this framework can be used to systematically estimate any model parameter in order to reduce the uncertainty in 3D simulation predictions. © 2021 The Author(s)
000117417 536__ $$9info:eu-repo/grantAgreement/ES/DGA/LMP246-18$$9info:eu-repo/grantAgreement/ES/DGA/T01-20R$$9info:eu-repo/grantAgreement/ES/MICINN/RTI2018-096001-B-C31
000117417 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000117417 590__ $$a7.2$$b2022
000117417 592__ $$a1.318$$b2022
000117417 591__ $$aELECTROCHEMISTRY$$b7 / 30 = 0.233$$c2022$$dQ1$$eT1
000117417 591__ $$aENERGY & FUELS$$b33 / 119 = 0.277$$c2022$$dQ2$$eT1
000117417 591__ $$aCHEMISTRY, PHYSICAL$$b41 / 161 = 0.255$$c2022$$dQ2$$eT1
000117417 593__ $$aCondensed Matter Physics$$c2022$$dQ1
000117417 593__ $$aRenewable Energy, Sustainability and the Environment$$c2022$$dQ1
000117417 593__ $$aFuel Technology$$c2022$$dQ1
000117417 593__ $$aEnergy Engineering and Power Technology$$c2022$$dQ1
000117417 594__ $$a12.1$$b2022
000117417 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000117417 700__ $$aMontiel M.
000117417 700__ $$0(orcid)0000-0001-7472-7542$$aMustata R.
000117417 700__ $$aZorrilla F.
000117417 700__ $$0(orcid)0000-0002-2384-5896$$aValiño L.
000117417 773__ $$g47 (2022), 4814-4826$$pInt. j. hydrogen energy$$tInternational Journal of Hydrogen Energy$$x0360-3199
000117417 8564_ $$s1706408$$uhttps://zaguan.unizar.es/record/117417/files/texto_completo.pdf$$yVersión publicada
000117417 8564_ $$s1983491$$uhttps://zaguan.unizar.es/record/117417/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000117417 909CO $$ooai:zaguan.unizar.es:117417$$particulos$$pdriver
000117417 951__ $$a2024-03-18-13:35:51
000117417 980__ $$aARTICLE