Size constraints restrict the surface area of solar arrays and thus the generated power for CubeSats. Therefore, the efficiency of the electrical power system (EPS) is the most important feature in the design of CubeSats. To maintain a high efficiency over long-term use of CubeSats, this work describes the implementation of a digital maximum power point tracking (MPPT) technique devised for EPS, which is based on an improved bat algorithm (BA) and runs on the lower computer. To ensure the universality of the designed control method, a typical system of a 6U CubeSat is constructed for subsequent simulations and experiments. The new proposed MPPT method utilizes the predicted degradation and telemetry temperature of solar arrays to change the initial population of BA, and refers to the convergence process of gray wolf optimization (GWO) to optimize tracking speed. Numerical simulation results show that the average efficiency of the new proposed algorithm is 97.29% across all simulations, compared to 94.48% for conventional BA. Meanwhile, the proposed algorithm shows a marked reduction in both standard deviation and coefficient of variation, providing a more stable tracking. Finally, a hardware testing system is established to validate the MPPT method based on the improved BA, and it can approach the maximum power point (MPP) of the simulated solar array within about 30 ms with a 2.5 ms control cycle.
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