Identification of the most influential variables on the power generation of an automotive thermoelectric generator through a global sensitivity analysis

A methodology to determine the most influential independent input variables on the maximum power generation of an automotive thermoelectric generator is developed. A validated numerical model is used to predict the maximum power generation of a thermoelectric generator composed of several thermoelec...

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Detalles Bibliográficos
Autores: Cozar, Ivan R., Massaguer, Albert, Massaguer, Eduard, Cabot i Codina, Andreu, Pujol, Toni
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/219448
Acceso en línea:https://hdl.handle.net/2445/219448
Access Level:acceso abierto
Palabra clave:Termoelectricitat
Contaminants
Generadors elèctrics
Thermoelectricity
Pollutants
Electric generators
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spelling Identification of the most influential variables on the power generation of an automotive thermoelectric generator through a global sensitivity analysisCozar, Ivan R.Massaguer, AlbertMassaguer, EduardCabot i Codina, AndreuPujol, ToniTermoelectricitatContaminantsGeneradors elèctricsThermoelectricityPollutantsElectric generatorsA methodology to determine the most influential independent input variables on the maximum power generation of an automotive thermoelectric generator is developed. A validated numerical model is used to predict the maximum power generation of a thermoelectric generator composed of several thermoelectric modules installed in the exhaust pipe of an internal combustion engine. The Morris sensitivity analysis and the least absolute shrinkage and selection operator feature selection approach are employed to identify the most influential variables. The amount of independent variables selected to carry out the analysis are 18 and they are embedded in different fields such as hydraulic, thermal, electrical, chemical, geometrical and design. Results show that the most influential variables are the inlet temperature of the hot fluid and the Seebeck coefficient and electric resistance of the thermoelectric modules. The thickness of the thermoelectric modules has the least influence on the maximum power generation. These findings could be useful to other researchers to develop simpler mathematical models without compromising the accuracy.Elsevier B.V.2025202520232025info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion1 p.application/pdfapplication/pdfhttps://hdl.handle.net/2445/219448Articles publicats en revistes (Ciència dels Materials i Química Física)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésReproducció del document publicat a: https://doi.org/10.1016/j.csite.2023.103584Case Studies In Thermal Engineering, 2023, vol. 51https://doi.org/10.1016/j.csite.2023.103584cc-by (c) Cozar Ivan R. et al., 2023http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:2445/2194482026-05-29T05:05:01Z
dc.title.none.fl_str_mv Identification of the most influential variables on the power generation of an automotive thermoelectric generator through a global sensitivity analysis
title Identification of the most influential variables on the power generation of an automotive thermoelectric generator through a global sensitivity analysis
spellingShingle Identification of the most influential variables on the power generation of an automotive thermoelectric generator through a global sensitivity analysis
Cozar, Ivan R.
Termoelectricitat
Contaminants
Generadors elèctrics
Thermoelectricity
Pollutants
Electric generators
title_short Identification of the most influential variables on the power generation of an automotive thermoelectric generator through a global sensitivity analysis
title_full Identification of the most influential variables on the power generation of an automotive thermoelectric generator through a global sensitivity analysis
title_fullStr Identification of the most influential variables on the power generation of an automotive thermoelectric generator through a global sensitivity analysis
title_full_unstemmed Identification of the most influential variables on the power generation of an automotive thermoelectric generator through a global sensitivity analysis
title_sort Identification of the most influential variables on the power generation of an automotive thermoelectric generator through a global sensitivity analysis
dc.creator.none.fl_str_mv Cozar, Ivan R.
Massaguer, Albert
Massaguer, Eduard
Cabot i Codina, Andreu
Pujol, Toni
author Cozar, Ivan R.
author_facet Cozar, Ivan R.
Massaguer, Albert
Massaguer, Eduard
Cabot i Codina, Andreu
Pujol, Toni
author_role author
author2 Massaguer, Albert
Massaguer, Eduard
Cabot i Codina, Andreu
Pujol, Toni
author2_role author
author
author
author
dc.subject.none.fl_str_mv Termoelectricitat
Contaminants
Generadors elèctrics
Thermoelectricity
Pollutants
Electric generators
topic Termoelectricitat
Contaminants
Generadors elèctrics
Thermoelectricity
Pollutants
Electric generators
description A methodology to determine the most influential independent input variables on the maximum power generation of an automotive thermoelectric generator is developed. A validated numerical model is used to predict the maximum power generation of a thermoelectric generator composed of several thermoelectric modules installed in the exhaust pipe of an internal combustion engine. The Morris sensitivity analysis and the least absolute shrinkage and selection operator feature selection approach are employed to identify the most influential variables. The amount of independent variables selected to carry out the analysis are 18 and they are embedded in different fields such as hydraulic, thermal, electrical, chemical, geometrical and design. Results show that the most influential variables are the inlet temperature of the hot fluid and the Seebeck coefficient and electric resistance of the thermoelectric modules. The thickness of the thermoelectric modules has the least influence on the maximum power generation. These findings could be useful to other researchers to develop simpler mathematical models without compromising the accuracy.
publishDate 2023
dc.date.none.fl_str_mv 2023
2025
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/219448
url https://hdl.handle.net/2445/219448
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.1016/j.csite.2023.103584
Case Studies In Thermal Engineering, 2023, vol. 51
https://doi.org/10.1016/j.csite.2023.103584
dc.rights.none.fl_str_mv cc-by (c) Cozar Ivan R. et al., 2023
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc-by (c) Cozar Ivan R. et al., 2023
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 1 p.
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier B.V.
publisher.none.fl_str_mv Elsevier B.V.
dc.source.none.fl_str_mv Articles publicats en revistes (Ciència dels Materials i Química Física)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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