Integration of MPPT algorithms with spacecraft applications: Review, classification and future development outlook

The electric power system is one of the key subsystems of a spacecraft and is responsible for the acquisition, conversion, storage and control of energy during the spacecraft mission. Therefore, ensuring the adequacy and stability of energy sources has become an important part of the spacecraft design process. Currently, most spacecraft acquire energy through the solar cell arrays they carry, but the actual output power of the photovoltaic system is difficult to reach the peak power due to the influence of the on-orbit space environment such as alternating temperature changes and radiation. In order to improve the output efficiency of PV systems, researchers have proposed the maximum power point tracking method based on the operating characteristics of the PV cells, and the classical methods include the incremental conductance method, hill-climbing method, constant voltage method, and perturbation observation method. On its basis, in order to further improve the control accuracy and adaptability of MPPT under complex environment, related scholars have proposed several new MPPT algorithms, such as fuzzy algorithm and neural network algorithm based on the principle of intelligence, particle swarm optimization algorithm based on the principle of optimization, gray wolf algorithm and hybrid optimization algorithm based on multiple algorithms.