A Self-Validating Method via the Unification of Multiple Models for Consistent Parameter Identification in PEM Fuel Cells

Luis Blanco-Cocom, Salvador Botello-Rionda, Luis Carlos Ordoñez and Sergio Ivvan Valdez
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Luis Blanco-Cocom: Centro de Investigación en Matemáticas, A.C., Jalisco S/N, Col. Valenciana CP 36023, Guanajuato, Gto, Apartado CP 36000, Mexico
Salvador Botello-Rionda: Centro de Investigación en Matemáticas, A.C., Jalisco S/N, Col. Valenciana CP 36023, Guanajuato, Gto, Apartado CP 36000, Mexico
Luis Carlos Ordoñez: Unidad de Energía Renovable, Centro de Investigación Científica de Yucatán, Parque Científico Tecnológico de Yucatán, Mérida, Yucatán CP 97302, Mexico
Sergio Ivvan Valdez: CONACYT-Centro de Investigación en Ciencias de Información Geoespacial, CENTROGEO, A.C., Parque Tecnológico San Fandila, Querétaro CP 76709, Mexico

Energies, 2022, vol. 15, issue 3, 1-16

Abstract: Mathematical models are used for simulating the electrochemical phenomena of proton-exchange-membrane (PEM) fuel cells. They differ in the scale, modeling variables, precision in specific features, and the required parameters. Often, the input parameters are not measurable and need to be estimated by minimizing the error between the model output and experimental data; however, the estimated parameters could differ from one model to another, hence provoking uncertainty about the correct values and the model’s suitability for simulating the real phenomenon. To address these issues, we introduced a self-validating methodology using three different mathematical models: The first set of parameters was estimated with a semi-empirical (SE) model; then, it was used for computing several points of the polarization curve (PC). The SE parameters and points were used to estimate a second set of parameters and to compute a single point of the PC with a macro-homogeneous (MH) model. The parameters and concentration profiles from the MH solution were used to estimate the last set of parameters with the reaction–convection–diffusion (SP-RCD) model, increasing the detail of the simulation. The SP-RCD parameters were returned to the MH model to recover the complete PC. The proposed methodology requires a few data points to consistently recover the same PC from the three models through estimating parameters in one model and validating them in the others. As output, the method provides complete information about several variables and the physical properties of the catalysts. In addition to the consistent simulation, the numerical results are consistent with those reported in the literature, thus validating the proposed method.

Keywords: semi-empirical model; macro-homogeneous model; SP-RCD model; UMDA G (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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