Proton exchange membrane fuel cells modeling based on artificial neural networks

Yudong Tian, Xinjian Zhu, and Guangyi CaoFuel Cell Research Institute, Shanghai Jiaotong University, Shanghai 200030, China

摘 要：<正>To understand the complexity of the mathematical models of a proton exchange membrane fuel cell （PEMFC） and their shortage of practical PEMFC control, the PEMFC complex mechanism and the existing PEMFC models are analyzed, and artificial neural networks based PEMFC modeling is advanced. The structure, algorithm, training and simulation of PEMFC modeling based on improved BP networks are given out in detail. The computer simulation and conducted experiment verify that this model is fast and accurate, and can be used as a suitable operational model for PEMFC real-time control.

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