Research on low-speed regenerative stability of sensorless induction motors

Abstract

With the rapid development of electrified railways, sensorless control technology for induction motors has attracted increasing attention in order to replace traditional mechanical speed sensors and improve system reliability and environmental adaptability. However, sensorless systems cannot directly measure rotor speed and rotor flux, and therefore rely on observers for state estimation. In low-speed regenerative operating conditions, problems such as reduced system stability and increased speed estimation error are likely to occur. To address these issues, this paper proposes a low-speed stability improvement method based on feedback matrix optimization. First, the mathematical model of the induction motor is established, and the theory of rotor flux oriented vector control is analyzed. Then, an adaptive full-order observer and a speed adaptive law are constructed to realize the estimation of rotor speed and rotor flux. To solve the stability problem of traditional full-order observers in the low-speed regenerative region, a feedback gain matrix is designed using the pole placement method, thereby improving the convergence speed of system errors and enhancing operating stability. Finally, simulations are carried out on the MATLAB/Simulink platform. By comparing the simulation results between the zero-feedback-matrix case and the designed-feedback-matrix case, it is verified that the proposed feedback matrix can effectively suppress instability in the low-speed regenerative region, improve speed tracking performance and rotor flux observation accuracy, and enhance overall system stability.