Optimization of Battery Management System for Nano Satellite
A Battery Management system (BMS) is tasked to provide optimum and efficient control over the battery in any satellite EPS. Along with Efficiency, these systems also require intelligent safety measures to avoid catastrophic failure when working in the space environment. For a large-scale battery pack, the accumulation of the heat generated during the charging and discharging processes might increase the battery pack's temperature, which will posses a faster acceleration of electrochemical reaction that may cause battery damage. Thus, this study aims to optimize the charging current to minimize the charging time for fast battery charging before the satellite approaches eclipse. The BMS will be utilizing a Social Group Optimization Algorithm on MATLAB Simulink to overcome the state of charge (SOC) problem, improving the battery lifespan. The result shows that the total time taken for the algorithm to converge is 86.18s, having an optimized current at 2500mA to fast charge a lithiumion battery. This produces 524s decrease in the charging time without affecting the capacity and the life cycle for the battery life. The approach accounts for charge time reduction with an efficiency of 95.51%, having an improvement of 2.41% compared to the previous technique used. This result entitles that this method performed best over the previous technique and is easy to implement on Nano-Satellite, considering all the charging processes, allowing maximum battery protection from overvoltage, overcharging, and overheating conditions.