Proton Exchange Membrane Fuel Cell Modeling Based on Seeker Optimization Algorithm

被引：3

作者：

李奇 ^{[1
]}

戴朝华 ^{[1
]}

陈维荣 ^{[1
]}

贾俊波 ^{[2
]}

韩明 ^{[3
]}

机构：

[1] School of Electric Engineering,Southwest Jiaotong University

[2] School of Engineering,Temasek Polytechnic,Singapore School of Electrical and Electronic Engineering,Nanyang Technological University,Singapore

[3] School of Engineering,Temasek Polytechnic,Singapore

来源：

Journal of Southwest Jiaotong University(English Edition) | 2008年 / 02期

关键词：

D O I：

暂无

中图分类号：

TM911.4 [燃料电池];

学科分类号：

080811 [新能源发电与电能存储];

摘要：

Seeker optimization algorithm(SOA)has applications in continuous space of swarm intelligence.In the fields of proton exchange membrane fuel cell(PEMFC)modeling,SOA was proposed to research a set of optimized parameters in PEMFC polarization curve model.Experimental result showed that the mean square error of the optimization modeling strategy was only 6.9×10-23.Hence,the optimization model could fit the experiment data with high precision.

引用

页码：120 / 124

页数：5

共 5 条

[1]

Particle swarm optimization based predictive control of proton exchange membrane fuel cell (PEMFC) [J].