Voltage source inverter (VSI) nonlinearity self-learning has become an important function of high-performance motor drives, which is conducive to sensorless control and parameter identification. In this paper, an accurate VSI nonlinearity self-learning method based on error voltage transformation is proposed for dual three-phase permanent magnet synchronous motor (DTP-PMSM) drives. First, the characteristics of phase voltage error and zero-axis voltage are analyzed, based on which the voltage error transformation between$xy-\mathbf{plane}$current injection$(xy-\mathbf{PCI})$and$dq-\mathbf{plane}$current injection$(dq-\mathbf{PCI})$is proposed. Then the self-learning current injection sequence in the$xy$plane is designed, and the voltage errors of$xy-\mathbf{PCI}$are transformed into that of$dp$by the proposed transformation. Finally, the 2D linear interpolation is adopted to compensate for the inverter nonlinearity under different rotor positions and$dq- \mathbf{plane}$current. The proposed method well addresses the problem of zero-axis voltage and has higher accuracy compared with the existing method. Experimental validation is conducted to verify the effectiveness of the proposed method.

The flux linkage characters of synchronous reluctance motors (SynRM) are usually tested offline due to a significant cross-saturation effect. In this paper, a self-commissioning method with current injection is proposed, in which the cross-saturation effect is considered. The reference equation for the injection current is derived in order to avoid potential rotor motion during the injection, and it ensures that sufficient valid data is distributed in the current plane after the injection. Considering the difficulty of PI tuning under unknown motor pa-rameters, a current controller based on general-integral extended state observer (GI-ESO) is applied to track the given current. Experiments are performed on a 3kW SynRM platform to verify the validity of the proposed method. The proposed method offers a promising solution for industrial applications of SynRM.

Dual Redundancy Permanent Magnet Synchronous Motor (DR-PMSM) has been widely used in the aviation electrical actuation system, the two sets of windings of DR-PMSM are independently driven by two inverters with isolated bus. When one set of winding or inverter fails, the other set of winding and inverter can work normally. However, the two sets of windings of DR-PMSM share one stator, which leads to strong coupling between the two sets of windings. In order to realize open-circuit fault (OCF) diagnosis of DR-PMSM, voltage disturbance observer of decoupled virtual current loops is designed. The voltage disturbance is observed with four luenberger observers of virtual current loops, the estimated voltage disturbance will be transformed to that of each winding to detect OCF. Then the voltage disturbance is combined with electrical position to locate the faulty switch.

This paper presents an improved position-sensorless field-oriented control strategy for a surface-mount permanent magnet synchronous motor (PMSM). In this algorithm, a high-pass filter (HPF) has been applied to the rotor flux estimation to solve the DC drift or offset problem caused by the integration part. The rotor position and speed signal extraction is achieved by mean of a phase-lock loop (PLL) as well as a phase compensation unit. This paper explains the design details of the adopted position-sensorless methodology. On the basis of this method, PMSM field orientation control strategy has been implemented to verify its correctness and reliability. Simulation has been carried out with MATLAB/Simulink. And a motor-generator experimental prototype setup has been built in the laboratory to testify its performance. Simulation and experimental results consistently prove the feasibility and precision of this estimation method.