Decoupling Algorithm for Online Identification of Inductance in Permanent Magnet Synchronous Motors Based on Virtual Axis Injection Method and Sensorless Control

Among the existing sensorless control algorithms for permanent magnet synchronous motors (PMSMs), the model reference adaptive system (MRAS) is widely utilized due to its merits of good robustness, high stability, and rapid response. Nevertheless, the performance of the sensorless control is largely determined by the identified inductance parameters. The virtual-rotary-axis high-frequency injection (VHFSI) method is an online identification strategy for PMSM inductance parameters which is not affected by the observed rotor position errors among inductance identification algorithms. However, the existing PMSM inductance online identification algorithm based on VHFSI has ignored the influence of the error components, resulting in low accuracy and the weak dynamic performance of the inductance identification algorithm. In response to the problems existing in the original method, this paper improves VHFSI by designing a feedforward decoupling algorithm to compensate for the error components. Theoretical verification and simulation results indicate that the improved identification algorithm enhances the accuracy of inductance parameter identification, significantly improves the dynamic tracking performance of inductance identification, and combines it with the MRAS sensorless control method to constitute a sensorless control system for the motor, thereby enhancing control performance and system stability.