This paper aims to investigate trajectory optimization and optimal control of an e-vertical take-off and landing (eVTOL) unmanned aerial vehicle (UAV) during the transition phase. The transition is a maneuver that guides the aircraft from hovering to forward flight. Electric vertical flight vehicles suffer from insufficient energy density of onboard storage devices, which causes a decrease in range and endurance of the aircraft. Therefore, searching for energy-saving solutions is vital in extending the mission time. This study uses methods of optimal control, addressing a gap in the literature and a need to mitigate the restrictions caused by modern batteries.
The approach presented in this study is centered around optimal control and mathematical modeling of a quad-plane eVTOL UAV and consists of two phases. In the first phase, the authors used direct nonlinear optimal control for a simplified 3-degrees-of-freedom (DOF) model, along with a set of constraints on the motion, to derive optimal trajectory with the objective of minimizing energy consumed during transition. In the second phase, a feedback control system (linear-quadratic regulator) is used to realize the trajectory for a full 6-DOF model. The mathematical models used in the derivation of equation of motion are based on CFD and wind tunnel tests. Optimal control problem was transcribed in the ICLOCS2 software, and the optimization problem was solved with interior point optimizer (IPOPT) solver.
The results show a 70% decrease of energy consumption in comparison to a simple zero-pitch reference trajectory. The results indicate that the undertaken approach is valid, and that the method could be used with success to improve the range and energy consumption of the quad-plane. Moreover, this approach can be also applicable to other eVTOL aircraft types with transitional flight phases.
This paper postulates that the most savings for and already designed and existing eVTOL can be obtained by optimizing the transition maneuver, as this flight phase offers the most freedom in shaping the trajectory. The findings show that significant savings can be achieved, and it is a promising method to use in UAV mission planning to mitigate the challenge of insufficient electric energy onboard the aircraft.
