氢燃料电池无人机实时分层能量管理系统研究

A hybrid power system topology based on fuel cells, lithium batteries, and supercapacitors for hydrogen-fueled unmanned aerial vehicles (UAVs) was designed to address the challenge of enhancing UAV endurance. A multi-time-scale hierarchical energy management framework was proposed, which can achieve the requirements of decision-making real-time performance and minimal fuel consumption for UAV hybrid power systems. At the short-time scale, an adaptive droop control algorithm suitable for UAV hybrid power systems was designed to solve the issues of insufficient accuracy in traditional droop control and bus voltage drop. At the long-time scale, a real-time hierarchical energy management strategy based on the minimum equivalent hydrogen consumption using model predictive control was designed. This strategy can make dynamical adjustments according to the instantaneous state and demands of the system, and perform graded management and optimized coordination among different types of energy storage devices internally, achieving optimal energy distribution of the system. The efficacy and reliability of the system were verified through simulation experiments and computational analysis. The results indicated that the strategy can reduce hydrogen consumption by 5.2% and increase the average working efficiency of the fuel cell by approximately 10% compared with state machine control strategies, while also reducing peak-to-valley power fluctuations by 92.8%.