Multi-objective optimization design of the solid oxide fuel cells using response surface methodology and genetic algorithm

To thoroughly investigate the enhancement of solid oxide fuel cell (SOFC) performance, trapezoidal convexities are employed to induce secondary flows in the cathode channels. Additionally, to comprehensively assess the combined effects of cathode operating conditions, response surface methodology is utilized to evaluate the impacts of temperature and trapezoidal convexity structure on SOFC performance targets, and their predictive correlations are fitted. The results indicate that gas concentration and velocity distributions demonstrate that the trapezoidal convexities significantly promote gas diffusion, thereby enhancing the electrochemical reaction within the SOFC. The addition of trapezoidal convexities in the cathode channels generates transverse vortices, enhancing gas disturbance, facilitating reactant diffusion, improving oxygen concentration distribution within the SOFC, and enhancing current density. Among the four parameters studied, temperature exhibits the most significant impact on the power density of the SOFC, followed by the top width, bottom width, and height of the trapezoidal convexity. Ultimately, the Pareto optimum was obtained using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The Pareto point set achieves higher power density and less flow resistance. The power density of the Pareto solution is enhanced by 34.8%-37.3%, while flow resistance is increased by 4.24%-17.03% compared to the initial state.