Energy management and system design for fuel cell hybrid unmanned aerial vehicles

Abstract

The growth in the use of unmanned aerial vehicles (UAVs) has created an increasing demand for energy-efficient and green power systems. In this paper, we have evaluated energy management strategies (EMSs) and system optimization design methodologies for fuel cell/battery-powered hybrid UAVs (HUAVs). EMSs aimed at the optimization of flight endurance and fuel cell durability were proposed based on fuzzy logic, dynamic programming, equivalent consumption minimization, and Pontryagin's minimum principle (PMP). System optimization design methodologies, including static design and synergistic sizing optimization design, were also devised. The synergistic sizing optimization was based on multiobjective optimization, while optimization of the EMS used a non-dominated sorting genetic algorithm. The effectiveness of the proposed EMSs and optimization design were then validated by simulation. Results showed that the proposed EMSs have both long flight time and good fuel cell durability, with the improved PMP prolonging the fight endurance by 4.64% and reducing the mean current of the fuel cell by 16.1% compared with fuzzy logic. Substantial improvements were obtained by using sizing optimization, and parameter sensitivity was addressed. The findings of this study can aid in the future development of fuel cell-powered UAVs.