Dynamic soaring improves the endurance of Unmanned Aerial Vehicles (UAVs) by obtaining energy from the horizontal wind shear gradient. The use of dynamic soaring in small solar UAVs can mitigate the trade-off between energy capacity and battery weight to achieve continuous all-day flight. The goal of this study is to determine the optimal energy acquisition methods for small solar UAVs using dynamic soaring and to decrease the battery weight to achieve all-day flight. A dynamic soaring UAV model that considers the influence of the wind shear gradient and a solar power energy model are established. The conditions to obtain a closed-loop energy system during daytime and nighttime flights are discussed, and the minimum mass of the energy system required for these conditions is determined. Simulations of single-cycle circular flights and a 72-h continuous flight of a small solar UAV are performed. The analyses and simulation results show that: (1) the combination of dynamic soaring and solar technology significantly reduces the energy consumption and reduces the required battery weight, (2) the flight speed and flight attitude angles have significant effects on the optimal total energy acquisition and (3) wind fields with a large horizontal gradient and strong solar illumination provide energy and load advantages.

The flatness of a six-degree-of-freedom (6DoF) aircraft model with conventional control surfaces – aileron, flap, rudder and elevator, along with thrust vectoring ability is established in this work. Trajectory optimisation of an aircraft can be cast as an inverse problem where the solution for control inputs that yield desired trajectories for certain states is sought. The solution to the inverse problems for certain systems is made tractable when they exhibit differential flatness. Flatness-based trajectory optimisation has a significant advantage over an equivalent collocation-based method in terms of computational efficiency and viability for real-time implementation. An application for the flatness of 6DoF aircraft is shown in the trajectory optimisation for dynamic soaring, and its connection with an equivalent 3DoF flatness-based implementation is also brought out. The results are compared with that from a collocation-based approach.

The latest attempts at improving small scale autonomously guided Uninhabited Aerial Vehicles (UAVs) have concentrated around the increase of range and speed. One of these ways is to incorporate dynamic slope soaring manoeuvres as part of the flight path. This is in contrast to most conventional path-planning algorithms where waypoint guidance is merged with terrain avoidance or contour following capability. Additionally, current trajectory optimization techniques are iterative and so have a considerable computational load. The proposed algorithm is based on Dubin's curves, and is therefore optimal by definition. Being non-iterative, it is comparatively a more efficient algorithm. Hence, a key advantage of the proposed technique is that the desired trajectory is generated quickly in real time with minimum computational load while satisfying the spatial constraints of dynamic slope soaring.