关键词: 聚合-分体飞行器, 无人机集群, 翼尖对接, 翼尖涡, 计算流体动力学

Abstract:

Intelligent cluster networking is one of the important directions for the development of small and medium-sized unmanned aerial vehicles. However， traditional drone clusters are unable to meet the multiple requirements of long-term hovering， remote transportation， large-scale deployment， and rapid response. Therefore， wingtip-hinge aggregation-separation technology has emerged. Aggregating multiple homogeneous/heterogeneous drones into a high aspect ratio aircraft， and freely separating and combining them according to task requirements can fully consider the advantages of high maneuverability and high speed of the separated cluster， as well as the advantages of long endurance and strong survival of the aggregated whole， thus greatly enhancing the efficiency of cluster drones. This article adopts computational fluid dynamics method to analyze two important aerodynamic problems of wingtip-hinge aggregation-separation aircraft. This article first analyzes the aerodynamic changes of typical configurations of small unmanned aerial vehicles before and after aggregation， explores the drag reduction effects of different configurations and quantities of unmanned aerial vehicles after aggregation， and obtains the optimal aggregation parameters of the aggregation aircraft and the aerodynamic shape design rules of the aggregation-separation aircraft. Secondly， during the wingtip docking process， strong nonlinear vortex disturbances on both wingtips can seriously affect the attitude control of the plane. In response to this problem， the paper analyzed the evolution of wing tip vortices and aerodynamic disturbances based on three typical wing tip docking methods， and determined the optimal docking method and parameters. The study of wing tip vortex disturbance characteristics can also provide further support for flight control in the aggregation-separation process.

Key words: aggregation-separation aircraft, drone cluster, wingtip docking, wing tip vortex, computational fluid dynamics