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高空太阳能无人机三维航迹优化

王少奇 马东立 杨穆清 张良

王少奇, 马东立, 杨穆清, 等 . 高空太阳能无人机三维航迹优化[J]. 北京航空航天大学学报, 2019, 45(5): 936-943. doi: 10.13700/j.bh.1001-5965.2018.0511
引用本文: 王少奇, 马东立, 杨穆清, 等 . 高空太阳能无人机三维航迹优化[J]. 北京航空航天大学学报, 2019, 45(5): 936-943. doi: 10.13700/j.bh.1001-5965.2018.0511
WANG Shaoqi, MA Dongli, YANG Muqing, et al. Three-dimensional optimal path planning for high-altitude solar-powered UAV[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(5): 936-943. doi: 10.13700/j.bh.1001-5965.2018.0511(in Chinese)
Citation: WANG Shaoqi, MA Dongli, YANG Muqing, et al. Three-dimensional optimal path planning for high-altitude solar-powered UAV[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(5): 936-943. doi: 10.13700/j.bh.1001-5965.2018.0511(in Chinese)

高空太阳能无人机三维航迹优化

doi: 10.13700/j.bh.1001-5965.2018.0511
详细信息
    作者简介:

    王少奇  男, 博士研究生。主要研究方向:飞行器总体设计

    马东立  男, 博士, 教授, 博士生导师。主要研究方向:飞行器总体设计、无人机技术

    杨穆清  男, 博士, 讲师。主要研究方向:飞行器总体设计

    张良  男, 博士研究生。主要研究方向:飞行器总体设计

    通讯作者:

    杨穆清. E-mail:buaa_yangli@163.com

  • 中图分类号: V221

Three-dimensional optimal path planning for high-altitude solar-powered UAV

More Information
  • 摘要:

    为提升高空太阳能无人机的飞行性能和载荷能力,综合考虑无人机运动状态和能量获取、存储、消耗之间的耦合关系,建立了三维航迹优化模型。采用高斯伪谱法在离散点上近似状态变量和控制变量,且在一系列配点上满足动力学方程的约束,将最优控制问题转化为非线性规划问题。针对典型的点到点飞行任务开展了航迹优化,并与常规定高定速航迹进行了对比。结果表明:通过调整飞行姿态,可以使高空太阳能无人机的净吸收能量提高9.2%;综合调整飞行姿态和改变飞行高度两种措施可以获得更大的能量优势,使储能电池剩余电量提高18.8%。

     

  • 图 1  地面坐标系和机体坐标系示意图

    Figure 1.  Schematic diagram of earth-fixed coordinate system and aircraft body-fixed coordinate system

    图 2  常规航迹及优化航迹功率

    Figure 2.  Power of common flight path and optimized flight path

    图 3  航迹在x-y平面内的投影对比

    Figure 3.  Comparison of flight path projection on x-y plane

    图 4  常规航迹与优化航迹的飞行高度及飞行速度对比

    Figure 4.  Comparison of flight altitude and velocity between common and optimized flight path

    图 5  常规航迹与优化航迹的迎角、滚转角、航迹倾角和航迹偏角对比

    Figure 5.  Comparison of angle of attack, roll angle, flight path angle and heading angle between common and optimized flight path

    图 6  常规航迹与优化航迹的储能电池电量状态对比

    Figure 6.  Comparison of battery pack state of charge between common and optimized flight path

    表  1  系数Aij的值

    Table  1.   Value of coefficients Aij

    i j=0 j=1 j=2
    0 7.983×10-1 9.208×10-3 -9.792×10-5
    1 5.898×100 1.392×10-2 2.255×10-3
    2 -7.246×100 4.610×10-2 -1.894×10-2
    下载: 导出CSV

    表  2  系数Bij的值

    Table  2.   Value of coefficients Bij

    i j=0 j=1 j=2
    0 2.284×10-2 -6.603×10-4 1.493×10-5
    1 1.403×10-1 2.108×10-4 -8.493×10-5
    2 1.362×100 -6.438×10-2 2.983×10-3
    下载: 导出CSV

    表  3  系数Cij的值

    Table  3.   Value of coefficients Cij

    i j=0 j=1 j=2
    0 -2.481×100 2.783×100 -1.818×10-1
    1 6.882×100 -4.081×100 -1.432×100
    2 -3.640×100 8.042×10-1 2.200×100
    下载: 导出CSV

    表  4  高空太阳能无人机基本参数

    Table  4.   Basic parameters of high-altitude solar-powered UAV

    参数 数值
    m/kg 134
    S/m2 25.5
    Ssc/m2 20.4
    Dp/m 1.5
    c0.75R/m 0.10
    QB/(kW·h) 21.5
    VOC/V 120
    RI 0.12
    下载: 导出CSV

    表  5  各部件能量转换效率

    Table  5.   Energy conversion efficiency of components

    %
    参数 数值
    ηsc 21
    ηMPPT 95
    ηm 90
    下载: 导出CSV

    表  6  仿真结果对比

    Table  6.   Comparison of simulation results

    参数 常规航迹 优化航迹
    净吸收能量/(kW·h) 31.60 34.51
    SOC最小值 0.261 0.272
    SOCf 0.560 0.665
    最小飞行高度/km 15.0 15.0
    最大飞行高度/km 15.0 22.6
    下载: 导出CSV
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出版历程
  • 收稿日期:  2018-08-31
  • 录用日期:  2018-10-15
  • 刊出日期:  2019-05-20

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