Preprint Article Version 1 This version is not peer-reviewed

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

Version 1 : Received: 9 July 2018 / Approved: 10 July 2018 / Online: 10 July 2018 (10:12:34 CEST)

A peer-reviewed article of this Preprint also exists.

Ariza, H.E.; Correcher, A.; Sánchez, C.; Navarro-Pérez, Á.; García, E. Thermal and Electrical Parameter Identification of a Proton Exchange Membrane Fuel Cell Using Genetic Algorithm. Energies 2018, 11, 2099. Ariza, H.E.; Correcher, A.; Sánchez, C.; Navarro-Pérez, Á.; García, E. Thermal and Electrical Parameter Identification of a Proton Exchange Membrane Fuel Cell Using Genetic Algorithm. Energies 2018, 11, 2099.

Journal reference: Energies 2018, 11, 2099
DOI: 10.3390/en11082099

Abstract

PEM fuel cell 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 let 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; 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 were taken from literature and two were proposed. Finally, the model with the parameters identified was validated with real.

Subject Areas

PEM fuel cell; identification; genetic algorithm; model; LabVIEW

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