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燃料电池空压机的建模及仿真
引用本文:卫国爱,全书海,苏林,魏五星,许岩.燃料电池空压机的建模及仿真[J].空军雷达学院学报,2010,24(3):200-202.
作者姓名:卫国爱  全书海  苏林  魏五星  许岩
作者单位:1. 空军雷达学院五系,武汉,430019;武汉理工大学自动化学院,武汉,430070
2. 武汉理工大学自动化学院,武汉,430070
3. 武汉理工大学自动化学院,武汉,430070;95829部队,湖北,孝感,432011
基金项目:国家"863"基金资助项目,湖北省自然科学基金资助项目 
摘    要:空压机的工作参数直接影响燃料电池的性能.为了控制空压机的压力,建立了空压机的压力控制模型,用RBF神经网络和Elman神经网络分别对同一组实验数据进行了拟合分析.仿真结果表明,空气压力控制系统采用RBF神经网络的空压机辨识模型,实时性好,偏差小.

关 键 词:质子交换膜燃料电池  空压机  神经网络  建模仿真

Modeling of Air Compressor With Fuel Cell and Its Simulation
WEI Guo-ai,QUAN Shu-hai,SU Lin,WEI Wu-xing,XU Yan.Modeling of Air Compressor With Fuel Cell and Its Simulation[J].Journal of Air Force Radar Academy,2010,24(3):200-202.
Authors:WEI Guo-ai  QUAN Shu-hai  SU Lin  WEI Wu-xing  XU Yan
Affiliation:1. No.5 Department, AFRA, Wuhan 430019, China; 2.School ofAutomation, Wuhan UniversityofTechnology, Wuhan 430070, China; 3.95829 Unit of the PLA, Xiaogan 432011, China)
Abstract:The operation parameters of air compressor exert directly an influence on the fuel cells’performance. A model of air compressor’s pressure control was set up, in order for controlling its pressure, the fitting analysis was made for the same group of experimental data respectively using RBF and Elman neural networks. By simulation it shows that the air pressure control system using the air compressor identification model with RBF neural network is of better real-time and lower offset.
Keywords:proton exchange membrane fuel cells (PEMFC)  air compressor  neutral networks (NN)  modeling and simulation
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