An enhanced sparrow search algorithm for model order reduction of proton exchange membrane fuel cell system

Abstract

Recently, proton exchange membrane fuel cells (PEMFCs) have gotten attention due to their many advantages such as low operating temperature, fast start-up capability, and high current density. As a result of growing interest in PEMFC technology, issues related to the operation and control of the PEMFC are also showing an increasing trend. A PEMFC system consists of several subsystems and thus is described by a higher-order model. It is known that such models have some drawbacks in terms of difficulty in controller design and computational complexity in real-time analysis. Considering the importance of applying proper control actions in a short time to avoid any damage, the need to develop a reduced-order model for the PEMFCs arises. This paper proposes an enhanced variant of the sparrow search algorithm (SSA), named ESSA, for model order reduction of the PEMFC system. The aim is to get a second-order model with minimum loss in important features of the original model. To examine the performance of the proposed method, a comparison is done with other meta-heuristic-based methods and some other literature approaches. Results validate the robustness of the proposed method for PEMFC system order diminution as well as its applicability to other complex systems.