| Particle Swarm Optimization based predictive control of Proton Exchange Membrane Fuel Cell （PEMFC） |
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| 引用本文： | 任远,曹广益,朱新坚.Particle Swarm Optimization based predictive control of Proton Exchange Membrane Fuel Cell （PEMFC）[J].浙江大学学报(A卷英文版),2006,7(3):458-462. |
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| 作者姓名： | 任远 曹广益 朱新坚 |
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| 作者单位： | Institute of Fuel Cell Department of Automation Shanghai Jiao Tong University Shanghai 20030 China，Institute of Fuel Cell Department of Automation Shanghai Jiao Tong University Shanghai 20030 China，Institute of Fuel Cell Department of Automation Shanghai Jiao Tong University Shanghai 20030 China |
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| 基金项目： | Project (No. 2003AA517020) supported by the Hi-Tech Researchand Development Program (863) of China |
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| 摘 要： | INTRODUCTION Fuel cells have attracted more attention in the last few years due to scarcity of the world energy source. The Proton Exchange Membrane Fuel Cell (PEMFC) is the focus of current development efforts because it is capable of higher power density and faster start-up than other fuel cells (Zhang et al., 2004). Research emphasis is on high power density with adequate energy conversion efficiency. PEMFC performance is related to many factors, among which electrolyte membrane …
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| 关 键 词： | 质子交换膜燃料电池 粒子群最优化 预测控制 支持向量机 |
| 收稿时间： | 2005-05-20 |
| 修稿时间： | 2005-11-21 |
Particle Swarm Optimization based predictive control of Proton Exchange Membrane Fuel Cell (PEMFC) |
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| Yuan Ren,Guang-yi Cao,Xin-jian Zhu.Particle Swarm Optimization based predictive control of Proton Exchange Membrane Fuel Cell (PEMFC)[J].Journal of Zhejiang University Science,2006,7(3):458-462. |
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| Authors: | Yuan Ren Guang-yi Cao Xin-jian Zhu |
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| Institution: | (1) Institute of Fuel Cell, Department of Automation, Shanghai Jiao Tong University, Shanghai, 20030, China |
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| Abstract: | 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. |
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| Keywords: | Support Vector Regression Machine (SVRM) Proton Exchange Membrane Fuel Cell (PEMFC) Particle Swarm Optimization (PSO) Predictive control |
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