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
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;
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
DOI :
10.1109/INMIC.2009.5383158
