基于BP神经网络的PEM FC电堆的静态热系统建模  

Modleing of Proton Exchange Membrane Fuel Cell Stack Thermal System Based on the Method of BP Neural Networks

作　　者：马宁[1] 邓先瑞[1] 杜学东[2] 

机构地区：[1]唐山师范学院计算机科学系,河北唐山063000 [2]唐山师范学院国资处,河北唐山063000

出　　处：《唐山师范学院学报》2007年第5期110-112,共3页Journal of Tangshan Normal University

摘　　要：质子交换膜燃料电池(PEMFC)电堆的温度是影响燃料电池性能的关键因素之一,建立电堆的热系统模型是准确控制电堆温度的基础。文章中利用反向传播(BP)神经网络对质子交换膜燃料电池的静态热系统进行建模。仿真结果表明,神经网络建模方法能够较好地拟合数据。The temperature of the proton exchange membrane fuel cell （PEMFC） stack is a key factor to influence the performance of the cell. It is necessary to build a model of PEMFC stack in order to control the temperature exactly. A approach using the method of BP neural networks to model the PEMFC stack was put forward and used to fit the experimental dates, the results was satisfying.

关 键 词：神经网络辨识 质子交换膜燃料电池 热系统 非线性系统辨识 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]