• DocumentCode
    3146524
  • Title

    Application of genetic algorithm to both sides pressure optimization of PEMFC

  • Author

    Tafaoli-Masoule, M. ; Shakeri, M. ; Nemati, H. ; Safari, M.

  • Author_Institution
    Fuel cell Res. Technol. group, Babol Univ. of Technol., Babol, Iran
  • fYear
    2009
  • fDate
    14-15 Dec. 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Genetic algorithm is very powerful tool at different optimization domain. It´s known very well that pressure is one of the most important and effective parameter in fuel cell Performance. In this paper, two-variable GA was applied to determine the optimum value of anode and cathode pressure of a monocell PEMFC. A quasi two dimensional model is presented for the PEMFC and used as fitness function of genetic algorithm.
  • Keywords
    electrochemical electrodes; genetic algorithms; optimisation; proton exchange membrane fuel cells; PEMFC; anode pressure; cathode pressure; genetic algorithm; pressure optimization; Anodes; Biological cells; Cathodes; Current density; Fuel cells; Genetic algorithms; Genetic mutations; Mechanical engineering; Random number generation; Temperature;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multitopic Conference, 2009. INMIC 2009. IEEE 13th International
  • Conference_Location
    Islamabad
  • Print_ISBN
    978-1-4244-4872-2
  • Electronic_ISBN
    978-1-4244-4873-9
  • Type

    conf

  • DOI
    10.1109/INMIC.2009.5383158
  • Filename
    5383158