Energy Minimization for Fixed-Wing AAV Inspection System in Multi-Hangar and Windy Environment

As critical enablers of the burgeoning low-altitude economy, unmanned aerial vehicles (UAVs) play pivotal roles in infrastructure inspection and logistics. However, their operational sustainability in urban environments is severely constrained by limited onboard energy and sensitivity to atmospheric dynamics, particularly wind field variations. Existing energy optimization studies often overlook the synergistic effects of turbulent wind patterns and communication reliability on UAV aerodynamics. This paper introduces a novel energy consumption model tailored for fixed-wing UAVs operating in wind fields. By optimizing the UAV's trajectory and traversal sequence based on this model, wind power is astutely harnessed to minimize energy consumption. Firstly, the optimal trajectory between two points is identified using graph-theoretical methods in accordance with the constraints related to communication quality and wind conditions. Subsequently, a weighted directed graph is constructed, and a refined Ant Colony Optimization (ACO) algorithm is introduced to determine the optimal UAV traversal sequence. Finally, simulation results demonstrate that for both constant and dynamic wind fields, the proposed algorithm maximizes the utilization of tailwinds while guaranteeing reliable communication with the ground base station. The proposed approach not only significantly reduces energy consumption during UAV inspection missions but also achieves rapid problem-solving.