Hardware-in-the-Loop Simulation of an On-Board Energy-Driven Scheduling Algorithm for CubeSats

Optimizing energy consumption and management in small satellites includes evaluating the most efficient electrical power system architecture. The primary goal is to improve energy harvesting using solar panels and techniques, such as maximum power point tracking (MPPT). In this sense, in this letter, an integrated thermal-electrical nanosatellite framework is employed to test different strategies of heater activation profiles in order to improve a state-of-the-art scheduling algorithm. Results show that a direct allocation of resources to heaters after the task selection phase leads to an increase in correlation between ideal and achieved power generation from solar panels and a more consistent battery temperature. The task scheduling strategy is then implemented in a hardware-in-the-loop simulation to verify its ability to meet real-time constraints and evaluate the impact on computation time.