Identification of PEM fuel cells based on support vector regression and orthonormal bases
Document typeConference report
Rights accessOpen Access
ProjectESTIMACION, DIAGNOSIS Y CONTROL PARA LA MEJORA DE LA EFICIENCIA Y LA VIDA UTIL DE LAS PILAS DE COMBUSTIBLE DE TIPO PEM (MINECO-DPI2015-69286-C3-2-R)
Polymer Electrolyte Membrane Fuel Cells (PEMFC) are efficient devices that convert the chemical energy of the reactants in electricity. In this type of fuel cells, the performance of the air supply system is fundamental to improve their efficiency. An accurate mathematical model representing the air filling dynamics for a wide range of operating points is then necessary for control design and analysis. In this paper, a new Wiener model identification method based on Support Vector (SV) Regression and orthonormal bases is introduced and used to estimate a nonlinear dynamical model for the air supply system of a laboratory PEMFC from experimental data. The method is experimentally validated using a PEMFC system based on a ZB 8-cell stack with Nafion 115 membrane electrode assemblies
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CitationFeroldi, D., Gómez, J., Roda, V. Identification of PEM fuel cells based on support vector regression and orthonormal bases. A: IEEE International Symposium on Intelligent Control. "Intelligent Control (ISIC), 2016 IEEE International Symposium on". Buenos Aires: 2016, p. 173-178.