Enhancing UAV endurance: coupled optimization of dynamic soaring trajectory and high-fidelity powertrain energy management

Harvesting wind energy from gradient wind fields through dynamic soaring is considered an effective approach to enhance the endurance of fixed-wing unmanned aerial vehicles (UAVs). However, when applied to conventional fixed-wing UAVs, this principle still faces problems such as unsustainable unpowered gliding, low accuracy in energy consumption estimation, and incomplete path planning. Accordingly, this study proposes an end-to-end wind-energy harvesting path planning framework for long-endurance missions, deeply integrated with overall aircraft energy management. First, based on a three-degree-of-freedom dynamic model, the flight dynamics equations in a gradient wind field are derived, and by combining them with a coupled battery–Electronic Speed Controller(ESC)–motor–propeller powertrain model, a high-precision energy consumption evaluation framework suitable for complex flight profiles is established. On this basis, considering attitude rate constraints, an energy-optimal multi-segment composite dynamic soaring management strategy is proposed and, together with transition trajectory planning based on Dubins paths, a complete end-to-end wind-energy harvesting path planning framework is constructed. Results show that the proposed evaluation framework achieves power and efficiency prediction errors below 5%, reducing energy consumption calculation error by 44% compared with the constant-efficiency model. Compared with traditional continuous powered gliding, the multi-segment composite management strategy reduces energy consumption by 35%. The planned end-to-end path further decreases total energy consumption by 23% compared with straight-line flight, effectively enhancing UAV endurance and energy utilization efficiency.