Jellyfish search algorithm for extracting unknown parameters of PEM fuel cell models: Steady-state performance and analysis

Abstract

In this paper, a novel attempt to employ the Jellyfish search algorithm (JSA) for solving parameters’ identifications problem of polymer exchange membrane fuel cells (PEMFCs) model is addressed. The minimization of the sum of squared errors (SSEs) between measured and estimated voltage dataset points define the fitness function to be optimized by the JSA subject to set of self-constrained inequality bounds. Three test cases are demonstrated complete with necessary verifications, comparisons and subsequent discussions. It can be quantified here that the best cropped values of SSEs are equal to 0.011699, 0.33598 and 2.14570 V2 for BCS 500-W module, 250-W stack and NedStack type PS6 unit; respectively. It can be confirmed that the maximum value of percentage voltage biased error is ±1% for all test cases under study. In addition, various performance measures are made to signify the robustness of the cropped results. At a later stage, various operating principal characteristics under changeable temperatures and varied regulating pressures are illustrated. It can be established that the JSA proves its ability to tackle this problem competently compared to others.