Modeling and analyzing load profiles for fuel cell powered cargo bicycles

Detalhes bibliográficos
Autor(a) principal: Daniel José Damas da Silva Leal
Data de Publicação: 2019
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/122194
Resumo: Proton exchange membrane fuel cells (PEMFCs) are the forefront for transportation applications because of the high efficiency and low pollutant emissions. The Polymer Fuel Cell Group of the German Aerospace Center (DLR) is rolling out a demonstration project for the use of electrical cargo bicycles powered by fuel cells, in urban delivery services. The performance and degradation expected from these fuel cells are yet to be known when they are subject to real operating conditions. The goal of this master thesis is to analyze different load cycles that simulate real driving profiles and study the performance and degradation of the cell along time. To study this, Ex-Situ and In-situ characterization of the cell will be made. In-situ techniques will be based on Cyclic Voltammetry (CV) and Electrochemical Impedance spectroscopy (EIS). To evaluate the changes on the surface of different parts of the cell and assess its degradation, Ex-Situ analysis will be performed using scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS). Additionally a data acquisition unit will be developed to gather real-time information of the testing station.
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spelling Modeling and analyzing load profiles for fuel cell powered cargo bicyclesEngenharia electrotécnica, electrónica e informáticaElectrical engineering, Electronic engineering, Information engineeringProton exchange membrane fuel cells (PEMFCs) are the forefront for transportation applications because of the high efficiency and low pollutant emissions. The Polymer Fuel Cell Group of the German Aerospace Center (DLR) is rolling out a demonstration project for the use of electrical cargo bicycles powered by fuel cells, in urban delivery services. The performance and degradation expected from these fuel cells are yet to be known when they are subject to real operating conditions. The goal of this master thesis is to analyze different load cycles that simulate real driving profiles and study the performance and degradation of the cell along time. To study this, Ex-Situ and In-situ characterization of the cell will be made. In-situ techniques will be based on Cyclic Voltammetry (CV) and Electrochemical Impedance spectroscopy (EIS). To evaluate the changes on the surface of different parts of the cell and assess its degradation, Ex-Situ analysis will be performed using scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS). Additionally a data acquisition unit will be developed to gather real-time information of the testing station.2019-07-052019-07-05T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://hdl.handle.net/10216/122194TID:202390993engDaniel José Damas da Silva Lealinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T12:28:08Zoai:repositorio-aberto.up.pt:10216/122194Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:20:50.192548Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Modeling and analyzing load profiles for fuel cell powered cargo bicycles
title Modeling and analyzing load profiles for fuel cell powered cargo bicycles
spellingShingle Modeling and analyzing load profiles for fuel cell powered cargo bicycles
Daniel José Damas da Silva Leal
Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
title_short Modeling and analyzing load profiles for fuel cell powered cargo bicycles
title_full Modeling and analyzing load profiles for fuel cell powered cargo bicycles
title_fullStr Modeling and analyzing load profiles for fuel cell powered cargo bicycles
title_full_unstemmed Modeling and analyzing load profiles for fuel cell powered cargo bicycles
title_sort Modeling and analyzing load profiles for fuel cell powered cargo bicycles
author Daniel José Damas da Silva Leal
author_facet Daniel José Damas da Silva Leal
author_role author
dc.contributor.author.fl_str_mv Daniel José Damas da Silva Leal
dc.subject.por.fl_str_mv Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
topic Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
description Proton exchange membrane fuel cells (PEMFCs) are the forefront for transportation applications because of the high efficiency and low pollutant emissions. The Polymer Fuel Cell Group of the German Aerospace Center (DLR) is rolling out a demonstration project for the use of electrical cargo bicycles powered by fuel cells, in urban delivery services. The performance and degradation expected from these fuel cells are yet to be known when they are subject to real operating conditions. The goal of this master thesis is to analyze different load cycles that simulate real driving profiles and study the performance and degradation of the cell along time. To study this, Ex-Situ and In-situ characterization of the cell will be made. In-situ techniques will be based on Cyclic Voltammetry (CV) and Electrochemical Impedance spectroscopy (EIS). To evaluate the changes on the surface of different parts of the cell and assess its degradation, Ex-Situ analysis will be performed using scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS). Additionally a data acquisition unit will be developed to gather real-time information of the testing station.
publishDate 2019
dc.date.none.fl_str_mv 2019-07-05
2019-07-05T00:00:00Z
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dc.identifier.uri.fl_str_mv https://hdl.handle.net/10216/122194
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