A hybrid control-oriented PEMFC model based on echo state networks and gaussian radial basis functions

The goal of increasing efficiency and durability of fuel cells can be achieved through optimal control of their operating conditions. In order to implement such controllers, accurate and computationally efficient fuel cell models must be developed. This work presents a hybrid (physics-based and data...

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Autores: Aguilar Plazaola, José Agustín|||0000-0002-5432-4567, Chanal, Damien, Chamagne, Didier, Yousfi-Steiner, Nadia, Péra, Marie-Cécile, Husar, Attila Peter|||0000-0001-8503-3837, Andrade-Cetto, Juan|||0000-0002-6354-8941
Tipo de documento: artigo
Data de publicação:2024
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositório:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglês
OAI Identifier:oai:upcommons.upc.edu:2117/401910
Acesso em linha:https://hdl.handle.net/2117/401910
https://dx.doi.org/10.3390/en17020508
Access Level:Acceso aberto
Palavra-chave:Proton exchange membrane fuel cells
PEMFC
Hybrid model
ESN
Radial basis functions
Piles de combustible de membrana d'intercanvi de protons
Àrees temàtiques de la UPC::Energies
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oai_identifier_str oai:upcommons.upc.edu:2117/401910
network_acronym_str ES
network_name_str España
repository_id_str
spelling A hybrid control-oriented PEMFC model based on echo state networks and gaussian radial basis functionsAguilar Plazaola, José Agustín|||0000-0002-5432-4567Chanal, DamienChamagne, DidierYousfi-Steiner, NadiaPéra, Marie-CécileHusar, Attila Peter|||0000-0001-8503-3837Andrade-Cetto, Juan|||0000-0002-6354-8941Proton exchange membrane fuel cellsPEMFCHybrid modelESNRadial basis functionsPiles de combustible de membrana d'intercanvi de protonsÀrees temàtiques de la UPC::EnergiesThe goal of increasing efficiency and durability of fuel cells can be achieved through optimal control of their operating conditions. In order to implement such controllers, accurate and computationally efficient fuel cell models must be developed. This work presents a hybrid (physics-based and data-driven), control-oriented model for approximating the output voltage of proton exchange membrane fuel cells (PEMFCs) while operating under dynamical conditions. First, a physics-based model, built from simplified electrochemical, membrane dynamics and mass conservation equations, is developed and validated through experimental data. Second, a data-driven, neural network (echo state network) is trained, fitted and tested with the same dataset. Then, the hybrid model is formed as a parallel structure, where the simplified physics-based model and the trained data-driven model are merged through an algorithm based on Gaussian radial basis functions. The merging algorithm compares the output of both single models and assigns weights for computing the prediction of the hybrid result. The proposed hybrid model structure is successfully trained, validated and tested with an experimental dataset originating from fuel cells within an automotive PEMFC stack. The hybrid model is assessed through the mean square error index, with the result of a low tracking error.Peer Reviewed20242024-01-0120242024-02-14journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/401910https://dx.doi.org/10.3390/en17020508reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/4019102026-05-27T15:37:01Z
dc.title.none.fl_str_mv A hybrid control-oriented PEMFC model based on echo state networks and gaussian radial basis functions
title A hybrid control-oriented PEMFC model based on echo state networks and gaussian radial basis functions
spellingShingle A hybrid control-oriented PEMFC model based on echo state networks and gaussian radial basis functions
Aguilar Plazaola, José Agustín|||0000-0002-5432-4567
Proton exchange membrane fuel cells
PEMFC
Hybrid model
ESN
Radial basis functions
Piles de combustible de membrana d'intercanvi de protons
Àrees temàtiques de la UPC::Energies
title_short A hybrid control-oriented PEMFC model based on echo state networks and gaussian radial basis functions
title_full A hybrid control-oriented PEMFC model based on echo state networks and gaussian radial basis functions
title_fullStr A hybrid control-oriented PEMFC model based on echo state networks and gaussian radial basis functions
title_full_unstemmed A hybrid control-oriented PEMFC model based on echo state networks and gaussian radial basis functions
title_sort A hybrid control-oriented PEMFC model based on echo state networks and gaussian radial basis functions
dc.creator.none.fl_str_mv Aguilar Plazaola, José Agustín|||0000-0002-5432-4567
Chanal, Damien
Chamagne, Didier
Yousfi-Steiner, Nadia
Péra, Marie-Cécile
Husar, Attila Peter|||0000-0001-8503-3837
Andrade-Cetto, Juan|||0000-0002-6354-8941
author Aguilar Plazaola, José Agustín|||0000-0002-5432-4567
author_facet Aguilar Plazaola, José Agustín|||0000-0002-5432-4567
Chanal, Damien
Chamagne, Didier
Yousfi-Steiner, Nadia
Péra, Marie-Cécile
Husar, Attila Peter|||0000-0001-8503-3837
Andrade-Cetto, Juan|||0000-0002-6354-8941
author_role author
author2 Chanal, Damien
Chamagne, Didier
Yousfi-Steiner, Nadia
Péra, Marie-Cécile
Husar, Attila Peter|||0000-0001-8503-3837
Andrade-Cetto, Juan|||0000-0002-6354-8941
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Proton exchange membrane fuel cells
PEMFC
Hybrid model
ESN
Radial basis functions
Piles de combustible de membrana d'intercanvi de protons
Àrees temàtiques de la UPC::Energies
topic Proton exchange membrane fuel cells
PEMFC
Hybrid model
ESN
Radial basis functions
Piles de combustible de membrana d'intercanvi de protons
Àrees temàtiques de la UPC::Energies
description The goal of increasing efficiency and durability of fuel cells can be achieved through optimal control of their operating conditions. In order to implement such controllers, accurate and computationally efficient fuel cell models must be developed. This work presents a hybrid (physics-based and data-driven), control-oriented model for approximating the output voltage of proton exchange membrane fuel cells (PEMFCs) while operating under dynamical conditions. First, a physics-based model, built from simplified electrochemical, membrane dynamics and mass conservation equations, is developed and validated through experimental data. Second, a data-driven, neural network (echo state network) is trained, fitted and tested with the same dataset. Then, the hybrid model is formed as a parallel structure, where the simplified physics-based model and the trained data-driven model are merged through an algorithm based on Gaussian radial basis functions. The merging algorithm compares the output of both single models and assigns weights for computing the prediction of the hybrid result. The proposed hybrid model structure is successfully trained, validated and tested with an experimental dataset originating from fuel cells within an automotive PEMFC stack. The hybrid model is assessed through the mean square error index, with the result of a low tracking error.
publishDate 2024
dc.date.none.fl_str_mv 2024
2024-01-01
2024
2024-02-14
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/401910
https://dx.doi.org/10.3390/en17020508
url https://hdl.handle.net/2117/401910
https://dx.doi.org/10.3390/en17020508
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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