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A novel hybrid krill herd algorithm for modeling solid oxide fuel cells

Solid oxide fuel cells are globally recognized as a very promising technology in the area of highly efficient electricity generation with a low environmental impact. In this paper, a novel hybrid krill herd algorithm (nhKHA) is proposed for modeling the solid oxide fuel cells (SOFCs). In nhKHA, the operation inspired by the foraging behavior of fish-swarm is adopted to improve the global search ability, and the operation inspired by the virus search is used to improve the search efficiency and accuracy. The nhKHA is applied to optimize the parameters of the SOFC, the experiment results show that this nhKHA can achieve more higher precision between mathematical model and experimental data compared with some other optimization algorithms.