Particle Swarm Optimization based predictive control of Proton Exchange Membrane Fuel Cell (PEMFC)

被引：1
|
作者：
任远
曹广益
朱新坚
机构：
[1] Institute of Fuel Cell Department of Automation Shanghai Jiao Tong University Shanghai 20030 China
[2] Institute of Fuel Cell Department of Automation Shanghai Jiao Tong University Shanghai 20030 China
来源：
Journal of Zhejiang University Science A(Science in Engineering) | 2006年 / 03期
关键词：
Support Vector Regression Machine (SVRM); Proton Exchange Membrane Fuel Cell (PEMFC); Particle Swarm Optimization (PSO); Predictive control;
D O I：
暂无
中图分类号：
TM911.4 [燃料电池];
学科分类号：
摘要：
Proton Exchange Membrane Fuel Cells (PEMFCs) are the main focus of their current development as power sources because they are capable of higher power density and faster start-up than other fuel cells. The humidification system and output performance of PEMFC stack are briefly analyzed. Predictive control of PEMFC based on Support Vector Regression Machine (SVRM) is presented and the SVRM is constructed. The processing plant is modelled on SVRM and the predictive control law is obtained by using Particle Swarm Optimization (PSO). The simulation and the results showed that the SVRM and the PSO re-ceding optimization applied to the PEMFC predictive control yielded good performance.
引用
收藏
页码：458 / 462
页数：5
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