On-line parameter identification of SPM motors based on MRAS technique

This article proposes a new parameter estimation method for surface-mounted permanent magnet (SPM) motors by employing the model reference adaptive system (MRAS) technique. The proposed algorithm is applied to an SPM motor used in washing machines. To determine washing and dewatering patterns, a washer tries to detect the size of load in the beginning of the operation. Hence it requires an accurate estimation of system parameters. The proposed estimation method identifies stator inductance and flux-linkage by using d- or q-axis current error, and its value is used for estimation independently with respect to each parameter. Therefore, the proposed scheme can get rid of the instability in inductance and flux estimation caused by the cross-coupling between d- and q- quantities. In this article, the stator resistance is detected by using the recursive least square (RLS) method to reduce measurement noises and to eliminate dead-time effect. Simulation results show that the proposed scheme tracks the parameters well even when there is transient states in rotor speed and the load conditions, and experimental results verify the validity and efficacy of the proposed algorithm.