Steady-State and dynamic characterization of proton exchange membrane fuel cell stack models using chaotic Rao optimization algorithm

A detailed mathematical model that aids in comprehending the phenomena that occur inside the fuel cell (FC) and producing reliable simulation results is demonstrated by estimating the optimal values of proton exchange membrane fuel cell (PEMFC) unidentified parameters. Therefore, a recent modified optimization algorithm based on chaotic maps and Rao Optimization algorithm, which include three versions, i.e., Rao-1, Rao-2, and Rao-3, has been developed. The three standard Rao algorithms have been improved using six chaotic maps and the modified Chaotic Rao (CRao) algorithms as well as the standard algorithms are evaluated for solving the optimization problem of estimating PEMFC parameters. In this paper the objective function (OF), which has to be minimized, is formulated as the total squared deviations (TSD) between the experimental and estimated output voltages of the FC. On two different types of PEMFCs, namely the BCS-500 W and Temasek 1 kW stacks, the efficiency and stability of the improved algorithms are tested. Additionally, this study has presented sensitivity and statistical data analysis to validate the dependability and accuracy of the suggested modified optimization algorithm in identifying the optimal PEMFC parameters.