A Comparative Analysis of Energy Management Strategies for a Fuel-Cell Hybrid Electric System UAV

Abstract

Hybrid electric UAVs rely heavily on energy manage-ment strategy (EMS). For a small UAV fuel-cell (FC) hybrid system, a comparison of four EMSs is presented in this paper. The FC, lithium-ion battery, and dc/dc converters comprise the hybrid system. The management of hybrid electric power flow based on changes in load power and battery state of charge (SOC) is an important part of these strategies. The energy management schemes considered in this paper are the most commonly used energy management schemes in fuel-cell based UAVs, and they include the following: the classical proportional-integral (PI) control (CPIC) strategy, the state machine control (SMC) strategy, the rule-based fuzzy logic (RBFL) strategy, and an intelligent technique based on adaptive neuro-fuzzy control strategy (ANFIS). There are two primary metrics for comparing performance, hydrogen consumption and battery SOC (BSOC), which impacts their life cycle. Such an EMS should be designed to maximise fuel efficiency while also making sure each energy source is used responsibly. MATLAB/Simulink software is used to conduct an in-depth study of a simulated model. For better usage of hybrid system's energy, EMS identifies variations in transient load current, as well as fuel-cell power. These investi-gations give insight on EMS work and the power flow in hybrid power systems. The trade-off choice between EMS is ensuring optimal performance in accordance with selected criterion.