Thermal and Electrical Parameter Identification of a Proton Exchange Membrane Fuel Cell Using Genetic Algorithm

H. Eduardo Ariza, Antonio Correcher, Carlos Sánchez, Ángel Pérez-Navarro and Emilio García
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H. Eduardo Ariza: Grupo de Investigación en Sistemas Inteligentes, Corporación Universitaria Comfacauca, Popayán CP 190003, Colombia
Antonio Correcher: Instituto De Automática E Informática Industrial-ai2, Universitat Politècnica de València, Valencia 46022, Spain
Carlos Sánchez: Instituto Universitario de Ingeniería Energética—IUIIE, Universitat Politècnica de València, Valencia 46022, Spain
Ángel Pérez-Navarro: Instituto Universitario de Ingeniería Energética—IUIIE, Universitat Politècnica de València, Valencia 46022, Spain
Emilio García: Instituto De Automática E Informática Industrial-ai2, Universitat Politècnica de València, Valencia 46022, Spain

Energies, 2018, vol. 11, issue 8, 1-15

Abstract: Proton Exchange Membrane Fuel Cell (PEMFC) fuel cells is a technology successfully used in the production of energy from hydrogen, allowing the use of hydrogen as an energy vector. It is scalable for stationary and mobile applications. However, the technology demands more research. An important research topic is fault diagnosis and condition monitoring to improve the life and the efficiency and to reduce the operation costs of PEMFC devices. Consequently, there is a need of physical models that allow deep analysis. These models must be accurate enough to represent the PEMFC behavior and to allow the identification of different internal signals of a PEM fuel cell. This work presents a PEM fuel cell model that uses the output temperature in a closed loop, so it can represent the thermal and the electrical behavior. The model is used to represent a Nexa Ballard 1.2 kW fuel cell; therefore, it is necessary to fit the coefficients to represent the real behavior. Five optimization algorithms were tested to fit the model, three of them taken from literature and two proposed in this work. Finally, the model with the identified parameters was validated with real data.

Keywords: PEM fuel cell; identification; genetic algorithm; model; LabVIEW (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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