A Method of Initial Position Estimation for a Low Saliency Machine Based on Eddy-Current Loss

The accuracy of the initial rotor position is essential to ensure the better performance of sensorless control for surface permanent magnet synchronous motor (SPMSM) drives. The sensorless control for SPMSM faces great challenges in achieving high precision of rotor position estimation due to the SPMSM with low and ultra-low saliency ratios. This paper presents the position estimation method based on eddy-current-reflected resistive saliency for extracting accurate initial position information for the motor with an ultra-low inductive saliency. This method separates high-frequency (HF) eddy-current-reflected resistance from HF impedance, extracts the HF resistive voltage vector, and utilizes the convolutional neural networks (CNN) to establish the mapping of the HF voltage image to the initial rotor position. Finally, the proposed method is experimentally evaluated and proven to have a promising performance on initial position estimation for a dual-stator motor with an ultra-low saliency machine.