Estimation of equivalent internal-resistance of PEM fuel cell using artificial neural networks

• 作 者: LI Wei ZHU Xin-jian MO Zhi-jun
• 机 构: Department of Automation, Fuel Cell Research Institute, Shanghai Jiaotong University, Shanghai 20003
• 出 处: 中南工业大学学报（英文版）
• 发表日期: 2007年5期
• 关键词: polymer electrolyte membrane fuel cell(PEMFC) equivalent internal-resistance rad

A practical method of estimation for the intal-resistance of polymer electrolyte membrane fuel cell (PEMFC) stack was adopted based on radial basis function (RBF) neural networks. In the training process, k-means clustering algorithm was applied to select the network centers of the input training data. Furthermore, an equivalent electrical-circuit model with this intal-resistance was developed for investigation on the stack. Finally using the neural networks model of the equivalent resistance in the PEMFC stack, the simulation results of the estimation of equivalent intal-resistance of PEMFC were presented. The results show that this electrical PEMFC model is effective and is suitable for the study of control scheme, fault detection and the engineering analysis of electrical circuits.