Casteleiro Roca, José LuisBarragán Piña, Antonio JavierSegura Manzano, FranciscaCalvo Rolle, José LuisAndújar Márquez, José Manuel2019-06-192019-06-192019-02Casteleiro Roca, J. L., Barragán, A. J., Segura, F., Calvo-Rolle, J. L., Andújar Márquez, J. M. (2019). Fuel Cell Output Current Prediction with a Hybrid Intelligent System. Complexity, 2019, 1–10. DOI: https://doi.org/10.1155/2019/63172701076-2787http://hdl.handle.net/10272/16430Afuel 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.engAtribución-NoComercial-SinDerivadas 3.0 Españahttp://creativecommons.org/licenses/by-nc-nd/3.0/es/Fuel CellOutput Current PredictionHybrid Intelligent Systemjournal article10.1155/2019/6317270open access