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Fuel Cell Output Current Prediction with a Hybrid Intelligent System

Author

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  • José-Luis Casteleiro-Roca
  • Antonio Javier Barragán
  • Francisca Segura
  • José Luis Calvo-Rolle
  • José Manuel Andújar

Abstract

A fuel cell is a complex system, which produces electricity through an electrochemical reaction. For the formal application of control strategies on a fuel cell, it is very important to have a precise dynamic model of it. In this paper, a dynamic model of a real hydrogen fuel cell is obtained to predict its response. The data used in this paper to obtain the model have been acquired from a real fuel cell subjected to different load patterns by means of a programmable electronic load. Using this data, a nonlinear model based on a hybrid intelligent system is obtained. This hybrid model uses artificial neural networks to predict the output current of the fuel cell in a very precise way. The use of a hybrid scheme improves the performance of neural networks reducing to half the mean squared error obtained for a global model of the fuel cell.

Suggested Citation

  • José-Luis Casteleiro-Roca & Antonio Javier Barragán & Francisca Segura & José Luis Calvo-Rolle & José Manuel Andújar, 2019. "Fuel Cell Output Current Prediction with a Hybrid Intelligent System," Complexity, Hindawi, vol. 2019, pages 1-10, February.
  • Handle: RePEc:hin:complx:6317270
    DOI: 10.1155/2019/6317270
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    References listed on IDEAS

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    7. Andújar, J.M. & Segura, F. & Durán, E. & Rentería, L.A., 2011. "Optimal interface based on power electronics in distributed generation systems for fuel cells," Renewable Energy, Elsevier, vol. 36(11), pages 2759-2770.
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    Cited by:

    1. José-Luis Casteleiro-Roca & Francisco José Vivas & Francisca Segura & Antonio Javier Barragán & Jose Luis Calvo-Rolle & José Manuel Andújar, 2020. "Hybrid Intelligent Modelling in Renewable Energy Sources-Based Microgrid. A Variable Estimation of the Hydrogen Subsystem Oriented to the Energy Management Strategy," Sustainability, MDPI, vol. 12(24), pages 1-18, December.
    2. Rasaki, S.A. & Liu, C. & Lao, C. & Zhang, H. & Chen, Z., 2021. "The innovative contribution of additive manufacturing towards revolutionizing fuel cell fabrication for clean energy generation: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).

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