Active Energy Management Based on Meta-Heuristic Algorithms of Fuel Cell/Battery/Supercapacitor Energy Storage System for Aircraft

This paper presents the application of an active energy management strategy to a hybrid system consisting proton exchange membrane fuel cell (PEMFC), battery, and supercapacitor. The purpose is control battery supercapacitor states charge (SOCs) as well minimizing hydrogen consumption. Energy should be applied systems created in this way increase efficiency working conditions. In study, optimization existing model literature with different meta-heuristic methods was further examined results similar those were obtained. Ant lion optimizer (ALO), moth-flame (MFO), dragonfly algorithm (DA), sine cosine (SCA), multi-verse (MVO), particle swarm (PSO), whale (WOA) algorithms flow power between sources. compared terms consumption calculation time. Simulation studies conducted Matlab/Simulink R2020b (academic license). contribution study that ant algorithm, for first It concluded most effective method computational burden algorithm. addition, provided better than At same time, equivalent minimization (ECMS) classical proportional integral (PI) benchmark done literature, it more