LAUSR

Abstract The article suggests an efficient methodology based-on a novel application of an optimization algorithm entitled Satin Bowerbird Optimizer (SBO) to realize the accurate parameters of solid oxide fuel cells (SOFCs). In this work, the fundamental necessary parameters to express dynamic and steady-state models of SOFCs are addressed. The objective function is adapted to minimize the mean squared deviations (MSD) between measured and computed output voltages of stacked SOFCs. Necessary scripts including dynamic models are formulated using MATLAB/SIMULINK. The proposed SBO-based methodology is demonstrated on number of case studies employing data of commercial SOFCs with subsequent comparisons to other optimizers such as genetic, particle swarm and grasshopper optimizers. Insignificant values of MSD for the three test cases under study confirm the good performance of the SBO. In addition, numerical simulations along with compulsory performance measures indicate that the ability of the SBO to generate competitive parameters for steady-state and dynamic models of SOFC which signifies its effectiveness. It can be emphasized that the SOFC models can be further enhanced.