Fuel Cell Output Current Prediction with a Hybrid Intelligent System

الملخص EN

A fuel cell is a complex system, which produces electricity through an electrochemical reaction.

For the formal application of control strategies on a fuel cell, it is very important to have a precise dynamic model of it.

In this paper, a dynamic model of a real hydrogen fuel cell is obtained to predict its response.

The data used in this paper to obtain the model have been acquired from a real fuel cell subjected to different load patterns by means of a programmable electronic load.

Using this data, a nonlinear model based on a hybrid intelligent system is obtained.

This hybrid model uses artificial neural networks to predict the output current of the fuel cell in a very precise way.

The use of a hybrid scheme improves the performance of neural networks reducing to half the mean squared error obtained for a global model of the fuel cell.