On-Orbit Servicing Optimization Framework with High- and Low-Thrust Propulsion Tradeoff

TL;DR

This paper introduces an advanced on-orbit servicing optimization framework that balances high- and low-thrust propulsion options for efficient scheduling and strategic planning of servicing missions.

Contribution

It generalizes existing methods by integrating user-defined trajectory models and propulsion tradeoffs, employing MILP and rolling horizon for comprehensive optimization.

Findings

Effective tradeoff between high- and low-thrust propulsion demonstrated.

Framework improves scheduling efficiency and strategic planning accuracy.

Potential for enhanced sustainability of on-orbit servicing infrastructures.

Abstract

This paper proposes an on-orbit servicing logistics optimization framework that is capable of performing the short-term operational scheduling and long-term strategic planning of sustainable servicing infrastructures that involve high-thrust, low-thrust, and/or multimodal servicers supported by orbital depots. The proposed framework generalizes the state-of-the-art on-orbit servicing logistics optimization method by incorporating user-defined trajectory models and optimizing the logistics operations with the propulsion technology and trajectory tradeoff in consideration. Mixed-Integer Linear Programming is leveraged to find the optimal operations of the servicers over a given period, while the Rolling Horizon approach is used to consider a long time horizon accounting for the uncertainties in service demand. Several analyses are carried out to demonstrate the value of the proposed framework in automatically trading off the high- and low-thrust propulsion systems for both short-term operational scheduling and long-term strategic planning of on-orbit servicing infrastructures.