Sensorless control of permanent magnet synchronous motor based on interacting multiple model extended Kalman filter

Aiming at the problems of low estimation accuracy and narrow application range of sensorless control caused by inverter nonlinearity and motor parameter error, this paper studies a sensorless control technology of permanent magnet synchronous motor based on an interactive multi-model extended Kalman filter algorithm to realize high-precision and high-performance sensorless control of a permanent-magnet synchronous motor. Firstly, considering the influence of inverter nonlinearity, the mathematical model of PMSM including inverter disturbance voltage is established. Secondly, an interactive multi-model extended Kalman filter observer is designed based on this model to achieve high-precision sensorless control of PMSM. Thirdly, the nonlinear disturbance voltage of the inverter is fed back to the control system for dead-time compensation, thus eliminating the voltage disturbance caused by the dead-time effect. Finally, simulation experiments and dual-motor towing experiments demonstrate the efficacy of the interactive multi-model extended Kalman filter sensorless control algorithm in mitigating the effects of dead time. The results indicate that the proposed algorithm exhibits high precision in speed and angle estimation, robust anti-disturbance capabilities, and excellent overall performance.