arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1807.02685math.OCcs.CEcs.SYeess.SYphysics.space-ph
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利用多级库存控制的最优卫星编队备用策略

Optimal Satellite Constellation Spare Strategy Using Multi-Echelon Inventory Control

University of Illinois at Urbana-Champaign(伊利诺伊大学厄巴纳-香槟分校)

Pauline C. M. Jakob, Seiichi Shimizu, Shoji Yoshikawa, Koki Ho

AI总结:

本文提出了一种基于多级库存管理的新型卫星编队备用策略,通过考虑低轨道的备用存储轨道,利用多级(s,Q)型库存政策,将地球地面视为供应商,停车轨道视为仓库,平面备用库存视为零售商,以应对大规模卫星编队的维护需求。

摘要:

近年来,开发低成本小型卫星的大规模卫星编队(即超大规模编队)的趋势日益增长,带来了对高效且可扩展的维护策略决策计划的需求。传统的卫星编队备用策略无法处理这些超大规模编队,因为它们在卫星数量和故障频率的可扩展性方面有限。在本文中,我们提出了一种新颖的备用策略,采用库存管理方法。我们考虑一组位于编队下方较低轨道的停车轨道用于备用存储,并利用多级(s,Q)型库存政策建模卫星编队备用策略问题,将地球的地面视为供应商,停车轨道视为仓库,平面备用库存视为零售商。这种库存模型的独特之处在于,由于轨道力学的影响,停车轨道(仓库)会随时间逐渐远离轨道平面,而平面备用库存(零售商)会在交付时从最近的(即最小等待时间)可用仓库接收补给。此外,停车轨道(仓库)也会从地面(供应商)获得补给,由于订单处理和发射机会导致的随机交货时间,利用一次火箭发射多个卫星(即批量发射折扣)来实现成本节约效果。所提出的分析模型通过拉丁超立方抽样进行模拟验证。此外,基于所提出的模型,引入了一个优化公式来确定最优备用策略,包括停车轨道特征和所有位置政策,以在满足性能要求的前提下最小化系统的维护成本。所提出的模型和优化方法应用于实际的卫星超大规模编队案例研究,以展示其价值。

英文摘要:

The recent growing trend to develop large-scale satellite constellations (i.e., mega-constellation) with low-cost small satellites has brought the need for an efficient and scalable maintenance strategy decision plan. Traditional spare strategies for satellite constellations cannot handle these mega-constellations due to their limited scalability in number of satellites and/or frequency of failures. In this paper, we propose a novel spare strategy using an inventory management approach. We consider a set of parking orbits at a lower altitude than the constellation for spare storage, and model satellite constellation spare strategy problem using a multi-echelon (s,Q)-type inventory policy, viewing Earth's ground as a supplier, parking orbits as warehouses, and in-plane spare stocks as retailers. This inventory model is unique in that the parking orbits (warehouses) drift away from the orbital planes over time due to orbital mechanics' effects, and the in-plane spare stocks (retailers) would receive the resupply from the closest (i.e., minimum waiting time) available warehouse at the time of delivery. The parking orbits (warehouses) are also resupplied from the ground (supplier) with stochastic lead time caused by the order processing and launch opportunities, leveraging the cost saving effects by launching many satellites in one rocket (i.e., batch launch discount). The proposed analytical model is validated against simulations using Latin Hypercube Sampling. Furthermore, based on the proposed model, an optimization formulation is introduced to identify the optimal spare strategy, comprising the parking orbits characteristics and all locations policies, to minimize the maintenance cost of the system given performance requirements. The proposed model and optimization method are applied to a real-world case study of satellite mega-constellation to demonstrate their value.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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