无人机气动/风能获取一体化设计

Dynamic soaring, a special flight mode that enables unpowered long-distance flight by utilizing horizontal wind gradients, holds great potential for enhancing the range and endurance of unmanned aerial vehicles (UAVs). This paper focuses on the parametric design of fixed-wing UAVs, replacing dynamic deformation control with static shape optimization of bionic joint structures to achieve efficient energy harvesting while avoiding complex mechanisms. By calculating and analyzing aerodynamic results corresponding to different design parameters, this study proposes an aerodynamic and wind energy harvesting integrative design method for UAVs. This method employs neural networks to achieve rapid solutions for aerodynamic forces and uses the Gauss pseudospectral method to solve for the optimal wing shape, ultimately obtaining a wing configuration that meets the requirements of efficient energy harvesting. In addition, flight simulations are conducted to compare the energy harvesting efficiency of three different wing shapes during dynamic soaring: basic wing, maximum lift-to-drag ratio wing, and aerodynamic and wind energy harvesting integrative design result. Results show that the UAV with the integrated design achieves the highest energy harvest amount and efficiency, with an increase of 979.04% compared to the basic wing and 10.09% compared to the maximum lift-to-drag ratio wing. The energy gain rate (work) done by the integrated design UAV during the energy harvesting phase is improved by more than 50%, verifying the feasibility of the aerodynamic and wind energy harvesting integrative design method. This design method provides engineering support for breaking through the bottleneck of UAV dynamic soaring energy harvesting.