This study proposes an unscented Kalman filter (UKF)-based speed estimation method for sensorless permanent magnet synchronous motor drive systems. The proposed approach enhances low-speed estimation accuracy by jointly exploiting the stationary and synchronous reference frames. Practical guidelines for tuning the process and measurement covariance matrices, which critically influence the numerical stability and convergence behavior of the UKF, are presented to support reliable implementation under low-speed operating conditions. Compared with conventional UKF-based sensorless strategies, the proposed method achieves consistently improved estimation accuracy and reduced sensitivity to parameter perturbations. The experimental results validate the effectiveness and practical feasibility of the proposed estimation method.
Jeon et al. (Sat,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: