Sequential Low-Thrust Orbit-Raising of All-Electric Satellites

Abstract

In this paper, we consider a recently developed formulation of the electric orbit-raising problem that utilizes a novel dynamic model and a sequence of optimal control sub-problems to yield fast and robust computations of low-thrust trajectories. This paper proposes two enhancements of the computational framework. First, we use thruster efficiency in order to determine the trajectory segments over which the spacecraft coasts. Second, we propose the use of a neural network to compute the solar array degradation in the Van Allen radiation belts. The neural network is trained on AP-9 data and SPENVIS in order to compute the associated power loss. The proposed methodology is demonstrated by considering transfers from different geosynchronous transfer orbits. Numerical simulations analyzing the effect of thruster efficiency and average power degradation indicate the suitability of starting the maneuver from super-geosynchronous transfer orbits in order to limit fuel expenditure and radiation damage. Furthermore, numerical simulations demonstrate that proposed enhancements are achieved with only marginal increase in computational runtime, thereby still facilitating rapid exploration of all-electric mission scenarios.