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ICREGA’14 - Renewable Energy: Generation and Applications pp 87–99Cite as

Dynamic Modeling of PEM Fuel Cell Using Particle Swarm Optimization

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Abstract

Fuel Cells are one of the green technologies that are currently undergoing rapid development. They have the tendency of someday replacing fossil fuels in supplying some of our everyday energy needs. In this paper, a dynamic model of the Nexa 1.2 kW Proton Exchange Membrane (PEM) Fuel Cell system was identified and developed using Particle Swarm Optimization. The developed dynamic model would serve as a good base for fault diagnosis studies on the fuel cell system.

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Acknowledgment

This research work is sponsored by the United Arab Emirates University (UAEU) in Al Ain—UAE.

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Authors and Affiliations

  1. UAE University, Al Ain, United Arab Emirates

    R. Salim, M. Nabag, H. Noura & A. Fardoun

Authors
  1. R. Salim
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  2. M. Nabag
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  3. H. Noura
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  4. A. Fardoun
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Corresponding author

Correspondence to R. Salim .

Editor information

Editors and Affiliations

  1. Faculty of Engineering Dept. Mechanical Engineering, United Arab Emirates University, Al-Ain, Utd.Arab.Emir.

    Mohammad O. Hamdan

  2. Faculty of Engineering Dept. of Electrical Engineering, United Arab Emirates University, Al-Ain, Utd.Arab.Emir.

    Hassan A.N. Hejase

  3. Faculty of Engineering Dept. of Electrical Engineering, United Arab Emirates University, Al-Ain, Utd.Arab.Emir.

    Hassan M. Noura

  4. Faculty of Engineering Dept. of Electrical Engineering, United Arab Emirates University, Al-Ain, Utd.Arab.Emir.

    Abbas A. Fardoun

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Salim, R., Nabag, M., Noura, H., Fardoun, A. (2014). Dynamic Modeling of PEM Fuel Cell Using Particle Swarm Optimization. In: Hamdan, M., Hejase, H., Noura, H., Fardoun, A. (eds) ICREGA’14 - Renewable Energy: Generation and Applications. Springer Proceedings in Energy. Springer, Cham. https://doi.org/10.1007/978-3-319-05708-8_8

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  • DOI: https://doi.org/10.1007/978-3-319-05708-8_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05707-1

  • Online ISBN: 978-3-319-05708-8

  • eBook Packages: EnergyEnergy (R0)

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