System identification of solid oxide fuel cell models using improved version of cat and mouse optimizer

Abstract

ABSTRACT The current work uses a novel modified algorithm to propose a new method for identifying parameters in solid oxide fuel cells. The method advocates using an improved design of a newly defined cat and mouse optimizer to find unknown parameters with the minimum sum of squared error (SSE) between experimental data and the results obtained from our constructed model. The technique is then applied to a studied case, and sensitivity evaluation based on pressure and temperature changes is used for its authentication. The method is then put in comparison with several other latest techniques to show its better effectiveness to deliver the highest confirmation with the experimental data. Sensitivity analysis showed that during temperature variation in 562.71°C, 650.81°C, 697.79°C, 747.87°C, and 780.80°C, the proposed method provides the minimum SSE, which are 9.53e-3, 6.95e-3, 5.53e-3, 5.08e-4, and 4.29e-4, respectively. Also, pressure variations from 1 atm to 5 atm by the proposed method, with 4.05e-3, 3.37e-3, 2.76e-3, 1.95e-3, and 1.62e-3, respectively, provides the minimum SSE.