Robust Fuzzy Logic MPPT Using Gradient-Based Optimization for PEMFC Power System

Abstract

In this study, the design of fuzzy logic control (FLC) systems for proton exchange membrane fuel cells (PEMFCs) maximum power point tracking (MPPT) is improved. The improvement is made possible by using a gradient-based optimizer (GBO), which maximizes the FLC systems’ freedom and flexibility while enabling accurate and speedy tracking. During optimization, the parameters of the FLC membership functions are considered choice variables, and the error integral is assigned to be the objective function. The proposed GBO-FLC method’s results are contrasted with those of other computational methods. The results demonstrated that the proposed GBO-FLC beats the other strategies regarding mean, median, variance, and standard deviation. A thorough comparison between the regular FLC and the upgraded FLC was conducted using a variety of scenarios with varied temperatures and water content. The results demonstrate that the suggested FLC-based GBO design provides a dependable MPPT solution in PEMFCs. The advancement of FLC systems through optimizing power generation in fuel cells is made possible by this work, opening the door for more effective and reliable alternative energy sources.