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Study designs a scheduling and power management algorithm for CubeSats, suggesting enhanced efficiency under varying conditions.
CubeSats are used as a platform in modern space missions due to their standardized form factor, reduced development cost, and shortened launch timelines. Earth observation, space weather monitoring and even re-entry applications make use of the CubeSat standard. Despite their advantages, CubeSats are constrained by limited onboard resources, with electrical power availability being one of the most critical bottlenecks. This work presents a dynamic, hybrid offline/online task scheduling and power management algorithm for a re-entry CubeSat, combining pre-computed schedules with real-time adaptation to changing flight conditions. The algorithm employs a heuristic-based approach, ranking tasks by parameters including priority, execution delay, duration, and power consumption. It adapts to varying flight conditions and system failures. In critical battery State of Charge (SoC) scenarios, only high-priority tasks above a defined threshold are executed, conserving power. A simulation suite was developed to evaluate performance under realistic mission profiles and stress tests with high loads and numerous tasks. The metrics included average and maximum task delay and average power consumption. The results show that appropriate heuristic weight selection can yield significant improvements in reliability and efficiency. The proposed algorithm offers a flexible, scalable solution for CubeSat power management, which is capable of maintaining operational reliability under dynamic conditions.
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Keller et al. (2026) studied this question.
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