Abstract: To enhance the endurance performance of hydrogen-fueled aircraft, an online energy management optimization strategy based on simulated annealing-particle swarm optimization (SA-PSO) was proposed. In the proposed strategy, the parameters of the fuzzy control membership functions were optimized and a fuzzy logic energy management model with power battery SOC and fuel cell demand power as inputs was constructed, enabling efficient energy distribution under dynamic operating conditions. The research results show that compared with the conventional thermostat strategy, the proposed strategy demonstrates superior adaptability and energy efficiency. The integrated SA-PSO algorithm is employed to deeply optimize the fuzzy control parameters, which exhibits fast convergence and strong optimization capabilities in large-scale parameter optimization. The optimized energy management strategy effectively reduces hydrogen consumption and improves energy utilization efficiency under complex dynamic conditions, providing a theoretical basis for online energy management of long-endurance hydrogen-fueled aircraft.

Key words: aeronautical engineering; hydrogen-fueled aircraft; hybrid powertrain; energy management strategy; fuzzy control

摘要： 为提高氢燃料飞行器续航性能，提出一种基于模拟退火-粒子群优化(SA-PSO)的在线能量管理优化策略。该策略通过优化模糊控制隶属度函数参数，构建以动力电池SOC和燃料电池需求功率为输入的模糊逻辑能量管理模型，实现动态工况下能量的高效分配。研究结果表明：与传统恒温器策略相比，所提出的策略在适应性与节能方面表现更优；采用融合型SA-PSO算法对模糊控制参数进行深度优化，该算法在大规模参数优化中收敛快、寻优能力强；优化后的能量管理策略有效降低了氢气消耗，提升了复杂动态工况下的能源利用效率，为长航时氢燃料飞行器的在线能量管理提供了理论依据。

关键词: 航空工程； 氢燃料飞行器； 混合动力； 能量管理策略； 模糊控制