Optimal tasks and heater scheduling applied to the management of CubeSats battery lifespan

Despite a growing interest in developing and launching CubeSats, areas related to their testing and simulation still need to improve systematization, especially within universities. Regarding the temperature of CubeSats, the battery is one of the most critical components, which is why it is common to use active control techniques such as heaters based on the Joule effect, which impacts the satellite’s task scheduling. Despite previous works in the literature, no study simultaneously contemplates the scheduling of tasks and the thermal control of the battery, under varying energy, with the rigor and advantages of exact optimization algorithms. This work proposes to address these two combined features: the analysis and modeling of the nanosatellite scheduling problem to optimize the use of energy resources and the maximize the mission value extraction while considering the battery temperature. In order to include the battery temperature control in the modeling, a proxy model will be used considering a Finite Volume Method based on the heat transfer equations that govern the thermal models of a battery. Thus, a mathematical model of task scheduling capable of considering the thermal control of the battery will be introduced.