Optimal Parameter Extraction and Performance Analysis of Proton Exchange Membrane Fuel Cell

In this article, accurate parameter extraction of pro-ton exchange membrane fuel cell (PEMFC), which is considered to be a complex, non linear and multi variable problem, has been carried out by using six different nature inspired metaheuristic algorithms. Algorithm used in this study are Bald Eagle Search (BES), Coyote Optimization Algorithm (COA), Brain Storm Op-timization (BSO), Harris Hawks Optimization (HHO), Gradient-Based Optimizer (GBO), Swarm Robotics Search and Rescue (SRSR). The main aim of this study is to find the optimal value of seven parameters of PEMFC model by using given nature inspired metaheuristic algorithms, and secondly to find the best algorithm among all nature inspired algorithm used and gives optimum values of these parameters. In this study, a voltage based objective function has been expressed as a mean of sum of squared error between obtained and experimental values of voltage. Ballard Mark V fuel cell has been used to carry out the performance analysis of various polarization curves such as current voltage, current power and current efficiency curves. Also, the effect of different temperatures and pressures on polarization curves has been studied after obtaining optimal values of unknown parameters. Furthermore, statistical analysis and box plot study has also been carried out to find the best algorithm and also to validate the accuracy and reliability of best algorithm among all metaheuristic algorithm used. It is found that SRSR optimization algorithm is best suitable metaheuristic algorithm for the optimal parameter estimation and also evaluated parameters by using this algorithm are helpful for the study of impact of pressure and temperature.