Neural network model of 100 W portable PEM fuel cell and experimental verification

被引:68
作者
Sisworahardjo, N. S. [1 ,2 ]
Yalcinoz, T. [3 ]
El-Sharkh, M. Y. [1 ]
Alam, M. S. [1 ]
机构
[1] Univ S Alabama, Dept Elect Comp Engn, Mobile, AL 36688 USA
[2] Inst Technol Bandung, Sch Elect Engn & Informat, Bandung 40132, Indonesia
[3] Meliksah Univ, Dept Elect & Elect Engn, TR-38280 Kayseri, Turkey
关键词
Fuel cell; PEMFC; Neural network model; Portable fuel cell; Direct hydrogen fed fuel cell; DYNAMIC-MODEL; BEHAVIOR; SYSTEMS; PLANT; STACK;
D O I
10.1016/j.ijhydene.2010.05.124
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
The inherent properties of artificial neural networks (ANNs) such as low sensitivity to noise and incomplete information make the ANN a promising candidate to model the fuel cell system. In this paper, an ANN-based model of 100 W portable direct hydrogen fed proton exchange membrane fuel cell (PEMFC) is presented. The model is built based on experimentally collected data from a portable 100 W direct hydrogen fed PEMFC in the authors' laboratory. A multilayer feedforward ANN with back-propagation training algorithm is used to model the portable PEMFC. The ANN consists of fully connected four layers network with two hidden layers. The PEMFC ANN model is trained using extracted data from experimentally measured and calculated parameters. To validate the model, the outputs of the PEMFC ANN are compared against experimental data and results from a dynamic model of portable direct hydrogen fed PEMFC. In addition, three statistical indices to measure variations, unbiasedness (precision), and accuracy in voltage, power, and hydrogen flow are used to evaluate the PEMFC ANN model performance. The indices indicate that the maximum variations, unbiasedness, and accuracy of the voltage, power, and hydrogen flow are 1.45%, 2.04%, and 1.90%, respectively, which shows a close agreement between the outputs of the PEMFC ANN and the experimental results. (C) 2010 Professor T. Nejat Veziroglu. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:9104 / 9109
页数:6
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