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Dynamic Modeling of a Proton-Exchange Membrane Fuel Cell Using a Gaussian Approach.
González-Castaño, Catalina; Lorente-Leyva, Leandro L; Alpala, Janeth; Revelo-Fuelagán, Javier; Peluffo-Ordóñez, Diego H; Restrepo, Carlos.
Afiliação
  • González-Castaño C; Department of Engineering Sciences, Universidad Andres Bello, Santiago 7500971, Chile.
  • Lorente-Leyva LL; Postgraduate Center, Universidad Politécnica Estatal del Carchi, Tulcán 040101, Ecuador.
  • Alpala J; Artificial Intelligence for Electrical Engineering Research Program, SDAS Research Group, Ben Guerir 47963, Morocco.
  • Revelo-Fuelagán J; Department of Electronics Engineering, Faculty of Engineering, Universidad de Nariño, Pasto 52001, Nariño, Colombia.
  • Peluffo-Ordóñez DH; Modeling, Simulation and Data Analysis (MSDA) Research Program, Mohammed VI Polytechnic University, Ben Guerir 47963, Morocco.
  • Restrepo C; Faculty of Engineering, Corporación Universitaria Autónoma de Nariño, Pasto 52001, Nariño, Colombia.
Membranes (Basel) ; 11(12)2021 Dec 01.
Article em En | MEDLINE | ID: mdl-34940454
This paper proposes a Gaussian approach for the proton-exchange membrane fuel cell (PEMFC) model that estimates its voltage behavior from the operating current value. A multi-parametric Gaussian model and an unconstrained optimization formulation based on a conventional non-linear least squares optimizer is mainly considered. The model is tested using experimental data from the Ballard Nexa 1.2 kW fuel cell (FC). This methodology offers a promising approach for static and current-voltage, characteristic of the three regions of operation. A statistical study is developed to evaluate the effectiveness and superiority of the proposed FC Gaussian model compared with the Diffusive Global model and the Evolution Strategy. In addition, an approximation to the exponential function for a Gaussian model simplification can be used in systems that require real-time emulators or complex long-time simulations.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Membranes (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Chile País de publicação: Suíça
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Membranes (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Chile País de publicação: Suíça