Air-taxi trajectory optimization with aerodynamic and motor models

TL;DR

This paper develops an optimal control framework incorporating physics-based models to design energy-efficient and safe transition trajectories for urban air-taxis, considering aerodynamic, motor, and acoustic factors.

Contribution

It introduces a comprehensive optimization approach that integrates multiple physics-based models to generate realistic transition trajectories for air-taxis.

Findings

Minimum-energy transition takes 80s with 13.3MJ energy use.

Minimum-time transition takes 28s with 16.4MJ energy.

Constraints on pitch and acoustics significantly affect trajectory design.

Abstract

To fulfill the vision for large-scale urban air mobility, air-taxi concepts must be carefully designed and optimized for their intended mission. Proposed air-taxi missions contain dynamic segments that are dominated by nonlinear dynamics. One such segment is the transition to and from hover and cruise that occurs at the start and end of the mission. Because this transition involves low-altitude and high-power flight, analyzing transition trajectories is critical for safe and economical urban air mobility. Optimization of the transition maneuver requires an optimal control approach that characterizes the trajectories of the system states through time. In this paper we solve this optimal control problem for air-taxi transition within a large-scale design-optimization framework. This framework allows us to include five physics-based models that describe flight dynamics, rotor aerodynamics, wing aerodynamics, motor performance, and acoustics with which we create a low-fidelity model of NASA's Lift-plus-Cruise air-taxi concept. We use this optimization problem formulation to compute transition trajectories that minimize time or minimize energy. Our results show that the Lift-plus-Cruise aircraft completes a minimum-energy transition in 80s with an energy expenditure of 13.3MJ and a minimum-time transition in 28s with an energy expenditure of 16.4MJ. We find that these trajectories contain large pitch angles and high sound pressure levels which are both undesirable for practical urban air mobility. Consequently, we explore trajectories that include pitch angle and acoustic constraints, and find that minimum time trajectories are significantly more affected by these constraints than minimum energy trajectories.