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复杂气象条件下考虑结冰风险的无人机飞行策略研究(除冰专栏)

郭琪磊1,桑为民2,牛俊杰2,袁烨3   

  1. 1. 中国民用航空飞行学院
    2. 西北工业大学
    3. 上海飞机设计研究院
  • 收稿日期:2022-05-25 修回日期:2022-09-12 出版日期:2022-09-13 发布日期:2022-09-13
  • 通讯作者: 桑为民
  • 基金资助:
    国家重大项目

UAV flight strategy considering icing risk under complex meteorological condi-tions

  • Received:2022-05-25 Revised:2022-09-12 Online:2022-09-13 Published:2022-09-13

摘要: 为解决无人机在复杂气象条件下易受结冰影响而威胁其飞行安全的问题,提出了一种考虑结冰风险的无人机航迹规划方法。首先,构建基于中尺度天气预报WRF模式的结冰气象预测模型,通过基于最佳参数化方案组合的结冰气象模拟获得模拟时段内海南乐东地区的温度、压力、LWC空间分布及时序变化。其次,构建基于代理模型的水滴收集质量快速预测方法。在获取FAR 25部附录C中连续最大结冰条件下40个采样点处水滴收集质量分布的基础上,利用POD降阶模型和Kriging插值算法,建立温度、压力、LWC、MVD等结冰气象参数与水滴收集质量之间的代理模型,可快速预测出目标区域水滴收集质量的空间分布与时序变化。最后,根据飞机结冰强度划分等级,以不同结冰强度下水滴收集质量阈值为结冰安全约束,利用基于PSO的结冰容限航迹规划方法进行考虑结冰风险的无人机飞行策略研究。研究结果表明:1) 利用WRF模式可获得温度、压力、LWC等结冰气象参数,预测值与观测值匹配良好;2) 基于POD降阶模型和Kriging插值算法,构建的气象参数与水滴收集量间代理模型可快速准确地获取目标区域内水滴收集质量的空间分布与时序变化;3) 基于PSO的结冰容限航迹规划方法可在不同结冰安全约束条件下,规划出无人机最优航迹。

关键词: 无人机, 结冰气象, WRF, 代理模型, 水滴收集量, 快速预测, 航迹规划, 粒子群优化

Abstract: In order to solve the problem that UAVs are vulnerable to icing and further threaten flight safety under complex meteoro-logical conditions, a UAV trajectory planning method considering the icing risk is proposed. Based on the WRF model, the icing meteorological environment in the Ledong area of Hainan from May to July 2021 is predicted, and the optimal pa-rameterization scheme is determined through the sensitivity analysis, and then the spatial distribution and temporal evolu-tion of temperature, pressure and LWC in the target area during the simulated period are obtained. At the same time, the OLHS method is employed to sample the continuous maximum icing conditions in Appendix C of FAR Part 25, and the droplet impact characteristics are calculated for 40 sampling points to obtain the distribution of droplet collections at each sampling point. Based on the POD reduced-order model and the Kriging interpolation method, a surrogate model between the droplet collection and meteorological parameters, such as temperature, pressure, LWC and MVD, is established. On the basis of the predicted icing meteorological parameters and the established surrogate model, the spatial distribution and temporal evolution of droplet collections in the target area are obtained. Finally, taking the threshold of droplet collections under the light/moderate icing intensity as the icing safety constraint, the PSO-based icing tolerance trajectory planning method is utilizing to optimize the flight strategy of the UAV considering the risk of icing. The results show that icing mete-orological parameters predicted by the WRF model, such as temperature, pressure, and LWC, match well with the obser-vations. Based on POD and Kriging, the constructed surrogate model between meteorological parameters and water droplet collection has the great performance on quickly and accurately prediction of the spatial distribution and temporal evolution of water droplet collection in the target area. The PSO-based icing tolerance trajectory planning method is com-petent to plan the optimal trajectory of the UAV under different icing safety constraints.

Key words: UAV, icing meteorology, WRF, surrogate model, water droplet collection, rapid prediction, trajectory planning, PSO

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