Abstract
The demand for sensorless control of surface-mounted permanent magnet synchronous motor drives has grown rapidly. Among various sensorless control techniques developed, Matsui’s current model-based approach and the extended Kalman filter approach have gained much attention. However, the performance of these control methods can be severely worsened or may even become unstable under strong disturbances or sensing failures. This paper presents a comparative study of the extended Kalman filter, the resilient extended Kalman filter, and the unscented Kalman filter-based sensorless direct torque and flux control approaches for the surface-mounted permanent magnet synchronous motor drives. Computer simulation studies and hardware implementation results have shown the efficiency and superior performance of the resilient extended Kalman filter and the unscented Kalman filter over the traditional extended Kalman filter for sensorless direct torque control applications.
Highlights
There has been a rapid increase in the deployment of surface-mounted permanent magnet synchronous motors (SPMSM) in industrial and commercial applications, such as wind energy conversion systems, hybrid electric vehicles, robotics, home appliances, etc
To improve EKF performance under external disturbances, noise and measurement failures, this paper presents a comparative study of the extended Kalman filter (EKF), the resilient extended Kalman filter (REKF), and the unscented Kalman filter (UKF)-based sensorless direct torque control approaches for SPMSM drives
Direct torque control combines the benefits of direct flux and torque control into an adjustable speed drive, which does not require pulse-width-modulation or coordinate transforms
Summary
There has been a rapid increase in the deployment of surface-mounted permanent magnet synchronous motors (SPMSM) in industrial and commercial applications, such as wind energy conversion systems, hybrid electric vehicles, robotics, home appliances, etc. To improve the estimation of stator flux linkage, various estimators have been developed including the back-emf integration methods such as low-pass filtering [11,12,13], and stabilizing the integrator with a PI-corrector or current offset methods [14,15,16,17] These approaches are not designed for real-time estimation. To improve EKF performance under external disturbances, noise and measurement failures, this paper presents a comparative study of the extended Kalman filter (EKF), the resilient extended Kalman filter (REKF), and the unscented Kalman filter (UKF)-based sensorless direct torque control approaches for SPMSM drives. Computer simulation studies and hardware implementation results have shown the efficiency and superior performance of the resilient extended Kalman filter and the unscented Kalman filter over the traditional extended Kalman filter for sensorless direct torque control applications.
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