A modified perturb and observe MPPT algorithm for PEMFC with rapid convergence and low power oscillation

Abstract

Abstract Proton Exchange Membrane Fuel Cells (PEMFCs) enable continuous energy production regardless of environmental conditions due to the storability of hydrogen. When examining the current–power (I–P) curve of a PEMFC under steady-state operating conditions, maximum power is observed at a specific current level. To extract this power, Maximum Power Point Tracking (MPPT) algorithms are employed. These algorithms should feature a simple structure and rapidly track the maximum power point. However, intelligent and optimization-based methods in the literature often involve high computational complexity. In this study, a modified Perturb and Observe (P&O)-based MPPT algorithm is developed to achieve a fast steady-state response under varying PEMFC operating conditions. The proposed algorithm also minimizes power oscillations in the steady state. Its performance is evaluated in a MATLAB/Simulink environment under five different scenarios. A comparative analysis is conducted against the conventional P&O and optimization-based MPPT algorithms, including Particle Swarm Optimization (PSO), Cuckoo Search Algorithm (CSA), and Genetic Algorithm (GA). The results, presented graphically, demonstrate the advantages of the proposed approach.