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

作　　者：任远 曹广益 朱新坚 

机构地区：[1]Institute of Fuel Cell, Department of Automation, Shanghai Jiao Tong University, Shanghai 20030, China

出　　处：《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》2006年第3期458-462,共5页浙江大学学报（英文版）A辑（应用物理与工程）

基　　金：Project (No. 2003AA517020) supported by the Hi-Tech Researchand Development Program (863) of China

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.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 receding optimization applied to the PEMFC predictive control yielded good performance.

关 键 词：Support Vector Regression Machine （SVRM） Proton Exchange Membrane Fuel Cell （PEMFC） Particle Swarm Optimization （PSO） Predictive control 

分 类 号：TM911.4[电气工程—电力电子与电力传动]