Automatic Tuning of Extended Kalman Filter in Sensorless Synchronous Reluctance Motor Drives

A substantial reduction in the human environmental footprint can be achieved through the use of more efficient motors, such as synchronous reluctance motors (SynRM). As low-cost motors, SynRMs are commonly employed in sensorless AC drives. Sensorless algorithms based on the Extended Kalman Filter (EKF) offer several advantages, but they require a time-consuming trial-and-error tuning procedure. This paper proposes the automatic tuning of the EKF through a second Kalman Filter (KF) in a primary–secondary (PS) configuration. The two KFs work concurrently: the first estimates the required quantities for machine control, and the second updates the process noise statistics of the first KF. The second KF is much easier to tune, requiring only one non-critical parameter. Experimental results confirm the validity of this approach.