Modeling, Validation, and Operational Variables Optimization of a Solid Oxide Fuel Cell

Solid oxide fuel cells can generate electrical energy with electrical efficiency exceeding 50% and reduce pollutant emissions, particularly, when the fuel is hydrogen. They have numerous applications, such as stationary generation, aircraft, and hybrid plants producing hydrogen and electricity. This work uses a thermodynamics lumped model to obtain the voltage versus current density of an SOFC, and distinctively of other authors also use heuristic and deterministic optimization algorithms to determine the main operation variables to achieve maximum power for a single cell. Moreover, it also has a detailed discussion of the transport of each overpotential, particularly the concentration overpotential, along with a comprehensive set of equations for its calculation. It also connects the physical and chemical phenomena to the main modeling variables. Unlike other reviewed studies, the Butler-Volmer equation is solved using an implicit solution. The results demonstrate that higher pressures and temperatures improve power output, with both heuristic and deterministic algorithms producing similar results for maximum power. The model allows the SOFC to operate efficiently within a hybrid system and serves as a method for estimating key operating variables while assessing the influence of physical and chemical parameters on performance.