Genetic Algorithm Based Charge Optimization of Lithium-Ion Batteries in Small Satellites

Small spacecraft that are powered by solar energy have limitations because of the size of their solar panels. With the limitations on the solar panel size, it is generally hard to comply with the demands from all the satellite subsystems, payloads and batteries at the same time. To overcome these problems we have developed and adopted a power management optimization scheme that runs in real time in the satellite. The proposed power management scheme primarily involves scheduling of loads (various subsystem operations, payload experimentation, battery charging, etc.) so that power utilization and thereby the charge of the batteries is at its optimum. We have developed a genetic algorithm based schedule optimizer and propose an FPGA based fitness evaluation function for it.