Model uncertainty estimation of a solid oxide fuel cell using a Volterra-type model

Autores
Biagiola, Silvina Ines; Schmidt, Christian Andrés; Figueroa, Jose Luis
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The dynamic nature of solid oxide fuel cells (SOFC) shows that they can be conceived as multi-input multi-output nonlinear processes. Aiming at dynamic simulation and control, this work presents a modeling study of a SOFC stack following a gray-box modeling approach. For such purpose, a Modified Generalized Memory Polynomial (MGMP) model is identified based only on input–output data of the system. Additionally, dedicated estimation is dealt with in order to cope with the presence of possible model uncertainty. Simulation results are given to illustrate the quality of the obtained model which is compared with other modeling approaches.
Fil: Biagiola, Silvina Ines. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación En Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur; Argentina
Fil: Schmidt, Christian Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación En Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur; Argentina
Fil: Figueroa, Jose Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación En Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur; Argentina
Materia
Identification
Uncertainty Estimation
Solid Oxide Fuel Cell
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/11784
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/11784
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Model uncertainty estimation of a solid oxide fuel cell using a Volterra-type modelBiagiola, Silvina InesSchmidt, Christian AndrésFigueroa, Jose LuisIdentificationUncertainty EstimationSolid Oxide Fuel Cellhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2The dynamic nature of solid oxide fuel cells (SOFC) shows that they can be conceived as multi-input multi-output nonlinear processes. Aiming at dynamic simulation and control, this work presents a modeling study of a SOFC stack following a gray-box modeling approach. For such purpose, a Modified Generalized Memory Polynomial (MGMP) model is identified based only on input–output data of the system. Additionally, dedicated estimation is dealt with in order to cope with the presence of possible model uncertainty. Simulation results are given to illustrate the quality of the obtained model which is compared with other modeling approaches.Fil: Biagiola, Silvina Ines. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación En Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur; ArgentinaFil: Schmidt, Christian Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación En Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur; ArgentinaFil: Figueroa, Jose Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación En Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur; ArgentinaElsevier Science2014-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/11784Biagiola, Silvina Ines; Schmidt, Christian Andrés; Figueroa, Jose Luis; Model uncertainty estimation of a solid oxide fuel cell using a Volterra-type model; Elsevier Science; Journal Of The Franklin Institute; 351; 8; 8-2014; 4183-41970016-0032enginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0016003214001392info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jfranklin.2014.04.025info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:55:26Zoai:ri.conicet.gov.ar:11336/11784instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:55:27.075CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Model uncertainty estimation of a solid oxide fuel cell using a Volterra-type model
title Model uncertainty estimation of a solid oxide fuel cell using a Volterra-type model
spellingShingle Model uncertainty estimation of a solid oxide fuel cell using a Volterra-type model
Biagiola, Silvina Ines
Identification
Uncertainty Estimation
Solid Oxide Fuel Cell
title_short Model uncertainty estimation of a solid oxide fuel cell using a Volterra-type model
title_full Model uncertainty estimation of a solid oxide fuel cell using a Volterra-type model
title_fullStr Model uncertainty estimation of a solid oxide fuel cell using a Volterra-type model
title_full_unstemmed Model uncertainty estimation of a solid oxide fuel cell using a Volterra-type model
title_sort Model uncertainty estimation of a solid oxide fuel cell using a Volterra-type model
dc.creator.none.fl_str_mv Biagiola, Silvina Ines
Schmidt, Christian Andrés
Figueroa, Jose Luis
author Biagiola, Silvina Ines
author_facet Biagiola, Silvina Ines
Schmidt, Christian Andrés
Figueroa, Jose Luis
author_role author
author2 Schmidt, Christian Andrés
Figueroa, Jose Luis
author2_role author
author
dc.subject.none.fl_str_mv Identification
Uncertainty Estimation
Solid Oxide Fuel Cell
topic Identification
Uncertainty Estimation
Solid Oxide Fuel Cell
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv The dynamic nature of solid oxide fuel cells (SOFC) shows that they can be conceived as multi-input multi-output nonlinear processes. Aiming at dynamic simulation and control, this work presents a modeling study of a SOFC stack following a gray-box modeling approach. For such purpose, a Modified Generalized Memory Polynomial (MGMP) model is identified based only on input–output data of the system. Additionally, dedicated estimation is dealt with in order to cope with the presence of possible model uncertainty. Simulation results are given to illustrate the quality of the obtained model which is compared with other modeling approaches.
Fil: Biagiola, Silvina Ines. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación En Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur; Argentina
Fil: Schmidt, Christian Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación En Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur; Argentina
Fil: Figueroa, Jose Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación En Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur; Argentina
description The dynamic nature of solid oxide fuel cells (SOFC) shows that they can be conceived as multi-input multi-output nonlinear processes. Aiming at dynamic simulation and control, this work presents a modeling study of a SOFC stack following a gray-box modeling approach. For such purpose, a Modified Generalized Memory Polynomial (MGMP) model is identified based only on input–output data of the system. Additionally, dedicated estimation is dealt with in order to cope with the presence of possible model uncertainty. Simulation results are given to illustrate the quality of the obtained model which is compared with other modeling approaches.
publishDate 2014
dc.date.none.fl_str_mv 2014-08
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/11784
Biagiola, Silvina Ines; Schmidt, Christian Andrés; Figueroa, Jose Luis; Model uncertainty estimation of a solid oxide fuel cell using a Volterra-type model; Elsevier Science; Journal Of The Franklin Institute; 351; 8; 8-2014; 4183-4197
0016-0032
url http://hdl.handle.net/11336/11784
identifier_str_mv Biagiola, Silvina Ines; Schmidt, Christian Andrés; Figueroa, Jose Luis; Model uncertainty estimation of a solid oxide fuel cell using a Volterra-type model; Elsevier Science; Journal Of The Franklin Institute; 351; 8; 8-2014; 4183-4197
0016-0032
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0016003214001392
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jfranklin.2014.04.025
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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