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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

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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