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.

Albatrosses can achieve long-distance migrations without flapping their wings by utilizing the horizontal wind gradient above the sea. Their gliding mode is known as dynamic soaring, which has great potential in improving the range, endurance, and wind resistance of Unmanned Aerial Vehicles (UAVs). However, current UAVs are suffering from low energy harvesting efficiency, which hinders the full realization of the advantages of dynamic soaring, and poses a bottleneck for UAV applications. This paper aims to address the problem of UAV dynamic soaring energy harvesting efficiency. Based on the results of previous research on wing morphing, research on the albatross-inspired morphing wing is conducted to analyze the impact of wing morphing on the characteristics of dynamic soaring energy harvesting. An albatross-inspired morphing wing is designed, and its aerodynamic performance and morphing modes are simulated. An aerodynamic surrogate model and trajectory optimization are used to investigate the influence of wing morphing on dynamic soaring trajectories and energy harvesting efficiency, as well as to analyze the underlying mechanisms of wing morphing. The results show that wing morphing increases the endurance of UAV dynamic soaring by 12.7%, and improves the overall energy harvesting efficiency by over 16.8%. The UAV can choose the corresponding wing morphing pattern in different dynamic soaring phases to increase lift or reduce drag, so as to ensure the best lift-drag ratio. The lift-drag ratio of the morphing wing is greater than the fixed wing in flight, with a maximum of 20.1% higher lift-drag ratio. The optimal wing morphing pattern of UAV dynamic soaring obtained is similar to the real wing deformation law of the albatross, and the influence of wing morphing on UAV dynamic soaring energy harvesting efficiency and the feasible morphing patterns are defined.

Dynamic soaring, which harvests energy from the wind, can enhance Unmanned Aerial Vehicles’ (UAVs’) range and endurance. However, energy harvesting efficiency issues hinder UAV applications, which can be addressed by wing morphing. Therefore, this study investigates the influence of albatross wing morphing during dynamic soaring. By constructing a parametric model, the shape of the albatross wing can be modeled and achieve morphing based on joints. From the video data, this paper summarizes the typical wing morphing patterns of the albatross and notices that changes primarily occur during the leeward descent phase. This paper first analyzes the aerodynamic performance of different wing morphing patterns and finds that the drag coefficient can be reduced by 7.75% with a suitable morphing pattern. This paper also explores the drag coefficient reduction mechanism and finds that downwash airflow decreases by 30.32% after wingtip anhedral. Interestingly, the lift-to-drag ratio shows minimal variation under different morphing patterns, within 2%. From the stability perspective, this study finds that the neutral point position changes after morphing. The maximum longitudinal static margin change is 4.9%, enhancing longitudinal stability by increasing the restorative moment arm. The lateral neutral point is 4.87% closer to the center of gravity, decreasing the roll and yaw moments. It can be observed that wingtip anhedral significantly increases the stability of the albatross. Moreover, a flight simulation is carried out to study the morphing influence on trajectory and energy harvesting. The results show that maximum energy gained is improved by 47.99%, and endurance is increased by 13.05%. The results also indicate that the effects of wing morphing are global rather than limited to the phase of morphing occurrence. Finally, based on the results, this paper proposes wing morphing regularity about the wingtip for UAVs. Wingtip bends downward can significantly increase the UAVs’ stability and reduce drag, but the overall trajectory needs to be reconsidered after introducing wing morphing.

Near-space airship is a frontier and hotspot in current military research and development, and the near-space composite propeller is the key technology for its development. In order to obtain higher aerodynamic efficiency at an altitude of 22 km, a certain near-space composite propeller is designed as a long and slender aerodynamic shape with a 10 m diameter, which brings many challenges to the composite structure design. The initial design is obtained by the composite structure variable stiffness design method using based on fixed region division blending model. However, it weighs 23.142 kg, exceeding the required 20 kg. In order to meet the structural design requirements of the propeller, a variable stiffness design method using the adaptive region division blending model is proposed in this paper. Compared with the methods using the fixed region division blending model, this method optimizes region division, stacking thickness and stacking sequence in a single level, considering the coupling effect among them. Through a more refined region division, this method can provide a more optimal design for composite tapered structures. Additionally, to improve the efficiency of optimization subjected to manufacturing constraints, a hierarchical penalty function is proposed to quickly filter out the solutions that do not meet manufacturing constraints. The above methods combined with a Genetic Algorithm (GA) using specific encoding are adopted to optimize the near-space composite propeller. The optimal design of the structure weighs 18.831 kg, with all manufacturing constraints and all structural response constraints being satisfied. Compared with the initial design, the optimal design has a more refined region division, and achieves a weight reduction of 18.6%. This demonstrates that a refined region division can significantly improve the mechanical performance of the composite tapered structure.