• DocumentCode
    674785
  • Title

    A proposed artificial neural network model for PEM fuel cells

  • Author

    Sari, Ali ; Balikci, Abdul ; Taskin, Sezai ; Aydin, Serap

  • Author_Institution
    Electr. & Energy Technol, Celal Bayar Univ., Manisa, Turkey
  • fYear
    2013
  • fDate
    28-30 Nov. 2013
  • Firstpage
    205
  • Lastpage
    209
  • Abstract
    Fuel cells convert the chemical energy directly to the electrical energy and hence they are a very favorable alternative energy source. In the literature, there are many studies related to the modeling of fuel cells. Artificial neural networks (ANNs) is one of the promising techniques for modelling nonlinear systems such as fuel cells. The proposed model in this study doesn´t require many parameters like other studies. Firstly, training and testing data was obtained the dynamic model of a PEM fuel-cell. Then, proposed ANN model outputs are compared with dynamic model ouputs Simulation results shows that the proposed ANN model can be used very efficiently for PEM fuel-cells without using many parameters.
  • Keywords
    neural nets; power engineering computing; proton exchange membrane fuel cells; ANN model; PEM fuel cells; alternative energy source; artificial neural network model; chemical energy; dynamic model; electrical energy; fuel cell modeling; nonlinear systems; Artificial neural networks; Data models; Fuel cells; Hydrogen; Load modeling; Mathematical model; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Electronics Engineering (ELECO), 2013 8th International Conference on
  • Conference_Location
    Bursa
  • Print_ISBN
    978-605-01-0504-9
  • Type

    conf

  • DOI
    10.1109/ELECO.2013.6713832
  • Filename
    6713832