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《Journal of Shanghai Jiaotong University》 2005-S1
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Fuel Cell Modeling Based on Fuzzy Neural Networks Identification and Its Voltage Control

MIAO Qing, CAO Guang-yi, ZHU Xin-jian (Fuel Cell Inst., Dept. of Automation, Shanghai Jiaotong Univ., Shanghai 200030, China)  
An electric characteristic model of direct methanol fuel cell (DMFC) was established by using fuzzy neural networks identification technique to cope with the problem that the output voltage of DMFC is significantly influenced by the fuel cell load variation. Based on the identification model, an adaptive fuzzy neural networks voltage controller was designed. The parameters of the controller are regulated by adopting the novel BP algorithm. The simulation results show that the fuzzy neural networks identification modeling method is correct, effective and the model has better accuracy. Moreover, the performance of the designed adaptive fuzzy neural networks voltage controller is very superior.
【Fund】: 国家高技术研究发展计划(863)项目(2003AA517020)
【CateGory Index】: TM911.4
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