Multidisciplinary Design Optimization of an On-Orbit Servicing Constellation in Low Earth Orbit

View Video Presentation: https://doi.org/10.2514/6.2021-4190.vid On-Orbit Servicing (OOS) has the potential to extend the lifetime of deployed satellites through refueling, repairing and upgrading components. High-value satellites in geostationary orbit (GEO) have traditionally been viewed as desirable clients for OOS due to their outstanding reliability requirements, high production and launch costs. However, most satellites operational today were deployed in Low Earth Orbit (LEO), where they have typically shorter design lives and would supposedly lead to lower returns on investment for future OOS missions. In this paper, the team analyses the viability of building OOS constellations for client constellations located in LEO and focuses on a potential use case: the refueling a global coverage LEO communications constellation. The parameters of the Iridium constellation are used as the target constellation, due to extensive data availability. The architecture of the OOS constellation is optimized for both total cost of the servicing mission and for the increase in performance of the client constellation. Main design tradeoffs are explored through a multidisciplinary design optimization (MDO) framework implemented in MATLAB which includes 4 modules: astrodynamics and propulsion, mass calculation, cost analysis, and performance. Architectural considerations (design variables) for the OOS constellation include varying the number of servicers, the number of orbital planes being covered, the mass of fuel delivered to each satellite, and the altitude of the phasing orbit for synchronous rendezvous. Multi-objective optimization is conducted using a genetic algorithm (GA) to get an optimal design recommendation. Under the model assumptions, it is determined that viable solutions do exist in which an OOS mission could be deployed to extend optimally the life of an existing LEO constellation through refueling. Our OOS constellation would cover all 6 planes of the client constellation, with a single 2.4 tons (wet mass) servicer per plane, and service all satellites within 801 days, adding 6.6 years of operational years to the client constellations for a total cost of $1.3B. However, the optimal design recommendation was found to be highly dependent on characteristics of the targeted satellites constellation and its state at the time of the servicing mission – in particular, the fuel level distribution. Another contribution of the paper lies in the MDO tool and methodology developed by the team for designing future OOS constellations in LEO.