A new artificial bee swarm algorithm for optimization of proton exchange membrane fuel cell model parameters

作     者：Alireza ASKARZADEH Alireza REZAZADEH 

作者机构：Faculty of Electrical and Computer EngineeringShahid Beheshti University 

出 版 物：《Journal of Zhejiang University-Science C(Computers and Electronics)》 (浙江大学学报C辑（计算机与电子（英文版）)

年 卷 期：2011年第12卷第8期

页      面：638-646页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the Renewable Energy Organization of Iran (SANA) 

主　　题：Proton exchange membrane fuel cell stack model Parameter optimization Artificial bee swarm optimization algorithm 

摘      要：An appropriate mathematical model can help researchers to simulate,evaluate,and control a proton exchange membrane fuel cell (PEMFC) stack *** a PEMFC is a nonlinear and strongly coupled system,many assumptions and approximations are considered during ***,some differences are found between model results and the real performance of *** increase the precision of the models so that they can describe better the actual performance,opti-mization of PEMFC model parameters is *** this paper,an artificial bee swarm optimization algorithm,called ABSO,is proposed for optimizing the parameters of a steady-state PEMFC stack model suitable for electrical engineering *** studying the usefulness of the proposed algorithm,ABSO-based results are compared with the results from a genetic algo-rithm (GA) and particle swarm optimization (PSO).The results show that the ABSO algorithm outperforms the other algorithms.