Optimization of Electrochemical Performance of a Solid Oxide Fuel Cell using Artificial Neural Network

被引：0

作者：

Ansari, M. A. ^{[1
]}

Rizvi, Syed Mohd Aijaz ^{[1
]}

Khan, Shuab ^{[1
]}

机构：

[1] Gautam Buddha Univ, Sch Engn, Greater Noida, UP, India

来源：

2016 INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS, AND OPTIMIZATION TECHNIQUES (ICEEOT) | 2016年

关键词：

Optimization; Artificial Neural Network (ANN); Solid Oxide Fuel Cell (SOFC);

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A neural network model is developed for prediction of solid oxide fuel cell performance. The back propagation algorithm is used for the cell voltage and power prediction. As the model is developed, the neural network model's prediction is presented and compared with the physical non-linear model results. Hence, the neural network structure based on the Levenberg Marquardt back propagation algorithm has been concluded to be more appropriate for modeling the dependencies of the non-linearity on the performance of solid oxide fuel cell.

引用

页码：4230 / 4234

页数：5

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