The Application of Artificial Intelligent Algorithms in Electric Propulsion - Tian Bin, An Bingchen, Xie Kan, Yang Sulan (Hangkong bingqi)
Electric propulsion technology has garnered significant attention due to its much higher specific impulse compared to traditional chemical propulsion. Currently, many mature on-orbit electric propulsion products have been developed worldwide. However, with the increasing demands of space missions, research in this field continues to advance. In recent years, the rapid development of artificial intelligence algorithms, such as machine learning and deep learning, has provided new approaches for the study of electric propulsion. These algorithms can not only train models based on data to optimize the performance of electric thrusters, but also analyze and solve the mathematical and physical models of plasmas within electric thrusters. By integrating machine learning and deep learning techniques, the accuracy and efficiency of solving related partial differential equations can be significantly improved, and optimal solutions for equation solving can be achieved. This paper summarizes the applications of artificial intelligence algorithms in the physical mechanism, equation solving, and model design of electric propulsion, with a particular focus on the research progress in ion thrusters, Hall thrusters, pulsed plasma thrusters, and helicon plasma thrusters. These studies not only demonstrate the great potential of artificial intelligence algorithms in enhancing the performance of electric propulsion systems, optimizing design, and reducing computational costs, but also provide new directions for the future development of electric propulsion technologies.