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垂直起降固定翼无人机串联混电系统优化设计
引用本文:陈刚,贾玉红,马东立,夏兴禄,张欣.垂直起降固定翼无人机串联混电系统优化设计[J].北京航空航天大学学报,2021,47(4):742-753.
作者姓名:陈刚  贾玉红  马东立  夏兴禄  张欣
作者单位:北京航空航天大学 航空科学与工程学院, 北京 100083
摘    要:针对垂直起降固定翼无人机的动力需求特点,提出了一种专用于该类无人机的串联混电系统(S-HES)优化设计方法。首先,建立了旋翼、固定翼及转换模式下的垂直起降固定翼无人机的功率需求模型和基于串联混电系统功率传递路径的混电功率解算方程,给出了计及功率约束、能量约束及电池充电的电池质量解算方法,并在大量统计数据的基础上建立了其他混电部件质量解算方程。其次,使用威兰氏线法建立了考虑发动机工作点变化的燃油消耗模型。使用柯西变异粒子群算法基于各物理数学模型在飞行剖面内的各个飞行阶段展开混电控制参数优化,从而完成垂直起降固定翼无人机的顶层设计要求向串联混电系统最佳供电策略、设计功率及质量分配方案的转化。在城市货运和山区货运2种应用场景下对所提方法进行了验证。最后,分析了优化设计结果对于不同飞行阶段性能要求的敏感性。研究结果表明:所提方法可较好地捕捉垂直起降固定翼无人机任务剖面的调整及各飞行阶段的性能要求变化对串联混电系统优化设计结果的显著影响,对垂直起降固定翼无人机的各类应用场景均具有较好的适应性。 

关 键 词:混电系统    垂直起降固定翼无人机    垂直起降    参数优化    总体设计
收稿时间:2020-01-14

Optimal design of series-hybrid electric system for unmanned convertiplane
CHEN Gang,JIA Yuhong,MA Dongli,XIA Xinglu,ZHANG Xin.Optimal design of series-hybrid electric system for unmanned convertiplane[J].Journal of Beijing University of Aeronautics and Astronautics,2021,47(4):742-753.
Authors:CHEN Gang  JIA Yuhong  MA Dongli  XIA Xinglu  ZHANG Xin
Institution:School of Aeronautic Science and Engineering, Beihang University, Beijing 100083, China
Abstract:A new method is proposed, for the optimal design of Series-Hybrid Electric System (S-HES) equipped on the unmanned convertiplane, to cope with the special power demand of this type of new aircraft. The method includes multiple physical and mathematical models to describe the characters of convertiplane's S-HES, such as the power requirement solving model in rotor, fixed-wing, and transition modes, the hybrid power solving model based on S-HES structures, and the battery mass sizing equation considering the power constraint, energy constraint, and battery charging. The mass sizing equations of other S-HES components are also established on large amounts of statistical data, and a fuel consumption analysis model considering the engine operating point variation is built based on the Willans line method. Based on the above physical and mathematical models, the hybrid control parameter optimization is carried out at each flight stage in the flight profile using the Cauchy mutation particle swarm optimization algorithm, and thus the top-level aircraft design demand can be translated into the optimal operating strategies, design power, and mass distribution scheme of S-HES. The proposed method was verified in urban freight and mountain freight application scenarios. The results reveal that the adjustment of the mission profile of the unmanned convertiplane and the performance requirement changes at each flight stage have an important impact on the final optimal S-HES design results, and the proposed method can well capture the impact and has good adaptability to various application scenarios of unmanned convertiplane. 
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