The high-altitude solar-powered unmanned aerial vehicle (SPUAV) offers incomparable advantages compared to other platforms, especially in enhancing aerial base stations, extending coverage to remote regions, supporting disaster response, and providing relay communication. However, the design feasible zones of SPUAVs are limited, requiring a coupling design of payload constraints and overall UAV characteristics. Focusing on the dual constraints of communication mission and UAV platform energy, this paper designed a morphing SPUAV, studying its overall design and optimization. Under the requirement of 24-hour energy closure while ensuring the mission’s effectiveness, the communication relay coverage was maximized. By establishing models for communication, solar irradiation, and mass prediction, setting energy balance constraints and communication constraints, and modeling optimization problems, the paper proposed a global optimization framework using a heuristic algorithm. The simulation results indicate that compared with the conventional configuration, the morphing SPUAV can significantly reduce total weight, especially under conditions of high altitude and heavy load, improving the overall effectiveness of the solution. Under simulation conditions, the total weight showed a 13.3% deduction. The improvement of communication payload specifications and the increase of cruise altitude can increase the coverage of relay communication but at the expense of increased total weight. When the communication payload is fixed, a low cruising altitude can improve the efficiency-to-cost ratio of communication coverage.

Modular Solar-Powered Aircraft (M-SPA) is a kind of High-Altitude Long-Endurance (HALE) aircraft which exploits the mission advantage of swarm UAV and the HALE advantage of large aspect-ratio SPA. M-SPA’s separated mode and combined mode give it the potential to maximize the mission efficiency with limited solar energy. In this paper, firstly, oriented by the mission of maximizing the cruise area, the overall design of the M-SPA is modeled, including the energy model, the aerodynamic model and the flight environment settings. Secondly, by analyzing the energy consumption of the flight modes, we design a multi-phase flight mission strategy. Then, a 24-hour three-dimensional (3D) flight profile of the M-SPA is optimized, including the sub-SPA cooperative path planning in the separation mode. Finally, inspired by the Traveling Salesman Problem (TSP), an improved Ant Colony Algorithm (ACA) is exploited to find the optimal path for each sub-SPA, which is further developed into a dynamic separation and combination scheme for the M-SPA. The simulation results show that the mission performance of the M-SPA outperforms that of the conventional SPA, and explicitly, the mission coverage of the M-SPA is slightly less than a linear increase under comparable simulation conditions.