Multi-Objective Optimization Of Operating Parameters Of A PEM fuel cell under flooding conditions using the non-dominated sorting genetic algorithm (NSGA-II)

Abstract

In the present study, the performance of a PEMFC is studied under cathode flooding conditions. A two-dimensional model of water and heat management based on the laws of conservation and electrochemical equations is used. The performance of the PEM cell is evaluated on the basis of the computed average current density and its distribution along the channels. Operating parameters are optimized with the objective of maximizing average current density while minimizing its variations. The problem is formulated into a multi-objective form that is solved by the Non-dominated Sorting Genetic Algorithm (NSGA-II) to find the optimal Pareto front. The results of the base case are compared to those of the optimized cell. A 38.94% increase in average current density and a 38.8% decrease in standard deviation are obtained.