Research Article
Open Access
$J2$-Aware Joint Optimization of Fuel Station Placement and Satellite Assignment for SSO Satellite Clusters
1
School of Aeronautics and Astronautics, Sun Yat-sen University, Shenzhen 518107, China
2
Beijing Institute of Aerospace Control Devices, Beijing 100854, China
3
School of Automation and Intelligent Science, Jiangnan University, Wuxi 214122, China
4
National University of Defense Technology, Changsha 410073, China
* Corresponding Author:
Tianle Yin,
[email protected]
Volume 1, Issue 3
2026
Received: 16 July 2026
Revised: 16 September 2026
Accepted: 21 September 2026
Published: 24 September 2026
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CC BY 4.0 License
Article Information
Published in
Aerospace Engineering Communications
Volume/Issue
Volume 1, Issue 3, 2026
Pages
119-127
Abstract
On-orbit refueling of sun-synchronous-orbit (SSO) satellite clusters requires effective deployment of fuel stations (FSs). To this end, this paper investigates the deployment optimization problem of fuel stations for SSO clusters by considering orbital geometry, satellite-to-station assignment, and refueling mission feasibility. A \(J_2\)-aware optimization framework is proposed, in which a particle swarm optimizer searches for optimal fuel-station orbital parameters and satellite assignments. For each candidate deployment, a deterministic mission evaluator is employed to estimate natural alignment opportunities, transfer requirements, and fuel consumption. The proposed approach considers the variation of the relative right ascension of the ascending node (RAAN) between the station and each target during the service interval, and evaluates transfer costs using both departure and terminal orbital geometries. A multi-objective optimization model is formulated to trade off propellant consumption, cluster balance, servicing-spacecraft requirements, and constraint violation penalty. Simulation results for a 20-target SSO cluster show that the optimized three-FS deployment serves all targets with a total refueling-related propellant consumption of 3405.8~kg and a total servicing-spacecraft requirement of four.
Graphical Abstract
Keywords
on-orbit refueling
SSO
fuel-station placement
$J_2$ perturbation
Data Availability Statement
Data will be made available on request.
Funding
This work was supported without any funding.
Conflicts of Interest
The authors declare no conflicts of interest.
AI Use Statement
The authors declare that no generative AI was used in the preparation of this manuscript.
Ethical Approval and Consent to Participate
Not applicable.
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APA Style
Yin, T., Zhu, J., Qiao, Z., Xu, S., & Zhao, L. (2026). J2-Aware Joint Optimization of Fuel Station Placement and Satellite Assignment for SSO Satellite Clusters. Aerospace Engineering Communications, 1(3), 119-127. https://doi.org/10.62762/AEC.2026.761344
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TY - JOUR AU - Yin, Tianle AU - Zhu, Jiajing AU - Qiao, Zheng AU - Xu, Shijie AU - Zhao, Lei PY - 2026 DA - 2026/09/24 TI - $J2$-Aware Joint Optimization of Fuel Station Placement and Satellite Assignment for SSO Satellite Clusters JO - Aerospace Engineering Communications T2 - Aerospace Engineering Communications JF - Aerospace Engineering Communications VL - 1 IS - 3 SP - 119 EP - 127 DO - 10.62762/AEC.2026.761344 UR - https://www.icck.org/article/abs/AEC.2026.761344 KW - on-orbit refueling KW - SSO KW - fuel-station placement KW - $J_2$ perturbation AB - On-orbit refueling of sun-synchronous-orbit (SSO) satellite clusters requires effective deployment of fuel stations (FSs). To this end, this paper investigates the deployment optimization problem of fuel stations for SSO clusters by considering orbital geometry, satellite-to-station assignment, and refueling mission feasibility. A \(J_2\)-aware optimization framework is proposed, in which a particle swarm optimizer searches for optimal fuel-station orbital parameters and satellite assignments. For each candidate deployment, a deterministic mission evaluator is employed to estimate natural alignment opportunities, transfer requirements, and fuel consumption. The proposed approach considers the variation of the relative right ascension of the ascending node (RAAN) between the station and each target during the service interval, and evaluates transfer costs using both departure and terminal orbital geometries. A multi-objective optimization model is formulated to trade off propellant consumption, cluster balance, servicing-spacecraft requirements, and constraint violation penalty. Simulation results for a 20-target SSO cluster show that the optimized three-FS deployment serves all targets with a total refueling-related propellant consumption of 3405.8~kg and a total servicing-spacecraft requirement of four. SN - 3071-1967 PB - Institute of Central Computation and Knowledge LA - English ER -
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@article{Yin2026J2Aware,
author = {Tianle Yin and Jiajing Zhu and Zheng Qiao and Shijie Xu and Lei Zhao},
title = {\$J2\$-Aware Joint Optimization of Fuel Station Placement and Satellite Assignment for SSO Satellite Clusters},
journal = {Aerospace Engineering Communications},
year = {2026},
volume = {1},
number = {3},
pages = {119-127},
doi = {10.62762/AEC.2026.761344},
url = {https://www.icck.org/article/abs/AEC.2026.761344},
abstract = {On-orbit refueling of sun-synchronous-orbit (SSO) satellite clusters requires effective deployment of fuel stations (FSs). To this end, this paper investigates the deployment optimization problem of fuel stations for SSO clusters by considering orbital geometry, satellite-to-station assignment, and refueling mission feasibility. A \(J\_2\)-aware optimization framework is proposed, in which a particle swarm optimizer searches for optimal fuel-station orbital parameters and satellite assignments. For each candidate deployment, a deterministic mission evaluator is employed to estimate natural alignment opportunities, transfer requirements, and fuel consumption. The proposed approach considers the variation of the relative right ascension of the ascending node (RAAN) between the station and each target during the service interval, and evaluates transfer costs using both departure and terminal orbital geometries. A multi-objective optimization model is formulated to trade off propellant consumption, cluster balance, servicing-spacecraft requirements, and constraint violation penalty. Simulation results for a 20-target SSO cluster show that the optimized three-FS deployment serves all targets with a total refueling-related propellant consumption of 3405.8~kg and a total servicing-spacecraft requirement of four.},
keywords = {on-orbit refueling, SSO, fuel-station placement, \$J\_2\$ perturbation},
issn = {3071-1967},
publisher = {Institute of Central Computation and Knowledge}
}
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