PEM fuel cell modeling using genetic algorithm—A novel approach

Abstract

In order to analyze, model, and control of power generation, precise models of proton exchange membrane fuel cells (PEMFCs) are very important. As we know, there has been a lot of research on nanofluid coolants and how they improve the heat transfer properties of the base fluid. Hence, a PEM fuel cell modeling using genetic algorithm (GA) is presented in this paper that exactly tries to estimate the output of the fuel cell performance when Al2O3 nanofluid coolant is used. In this paper, we determine the thermal conductivity of Al2O3 nanofluid coolant with different concentrations of ethylene glycol and water and simulate the PEMFC performance by means of the data generated using GA.