Abstract

Fuel cells serve as devices that directly convert chemical energy into electricity via electrochemical reactions. Assessing and characterizing fuel cell performance typically involves the creation of polarization curves. Nevertheless, currently employed polarization curve models have shown limited effectiveness when it comes to evaluating the conversion of chemical energy into electrical energy. To address this knowledge gap, this study has developed a concise and integrable energy model of fuel cells. This model aims to predict output voltage with a high degree of reliability and precision, relying on current density. The validity of this model was through experimentation, involving a dataset of twenty results. Fitting outcomes from these experiments demonstrated the capacity of the proposed model to faithfully replicate experimental curves. Furthermore, this model permits the dependable and precise calculation of fuel cell energy density, contingent upon optimal model parameters. In addition, this study has established quantitative correlations between the inherent characteristics of fuel cells and their energy density. Lastly, the proposed model facilitates the interpolation and extrapolation of polarization curves that may not be attainable through direct experimentation. This capability is achieved through the utilization of a secondary model that quantitatively associates the intrinsic attributes of fuel cells with optimal model coefficients.

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