This article elaborates a novel online full parameter estimation method for permanent magnet synchronous motors (PMSMs). Usually, only two parameters can be estimated using voltage functions in the d-q frame due to the problem of rank deficiency. The α-β frame possesses the inherent advantage that full motor parameters can be estimated using voltage functions during steady and transient states. An algorithm based on recursive least squares in the α-β frame is proposed to estimate full motor parameters, including stator resistance, $d$ -axis and $q$ -axis inductances, and flux linkage simultaneously. Simulation and experimental results on the PMSM drive system are presented to verify the effectiveness of the proposed algorithm. Compared with the method in the d-q frame, the superiority of the proposed method in terms of faster convergence rate, less computational cost, and high accuracy is demonstrated.

Due to the requirements of industrial drive system for high output power, uniform torque distribution, and accurate synchronous movement, the synchronous control methods of multimotor system have drawn increasing attention. This article refers to a large number of research on synchronous control methods and summarizes and compares different control structures and algorithms. Based on the evaluation criteria of tacking error, synchronization error, and adjustment time, the advantages and disadvantages of three representative control algorithms, including proportional integral derivative (PID) control, model predictive control, and sliding mode control, are studied through experiments. Finally, the development trend of multimotor synchronous control is summarized and prospected.

Permanent magnet synchronous machines (PMSMs) work with controllers and controller parameters affect the machine's voltages and currents and thus the diagnosis of stator winding fault. One such parameter is the current controller bandwidth that affects the harmonic content in these signals. In the literature, the 2nd harmonics in both dq-axis currents and voltages have been used for fault detection, and the main advantage is that inter-turn short-circuit (ITSC) winding fault with a few shorted turns, specially one turn, can be detected. One indicator that combines the fault information in voltages and currents is the instantaneous reactive power (IRP). However, it has been shown that IRP does not perform robustly with respect to current controller bandwidth. The main contribution of this work is that it proposes and validates a new mathematical function for ITSCs detection, Rayleigh quotient, which combines the fault information present in voltages and currents to make ITSCs detection robust to current controller bandwidth. The validations from both co-simulation and experiment show that the proposed method is robust to the bandwidth and can detect ITSC faults faster than IRP.

To reduce the output current distortion, this article proposes a novel space vector overmodulation strategy for indirect matrix converter (IMC) in the overmodulation region I. First, the effect of error voltage vector on current harmonics based on minimum-phase-error (MPE) overmodulation strategy is analyzed. According to the characteristics analysis of current ripple, the proposed overmodulation strategy, without changing the selection or duty ratio of the two active voltage and current vectors, rearranges the action time and position of the zero-voltage vector to make the actual current approach the reference current value and reduces the output current ripple. Moreover, the zero-voltage vector is only used under the large current vector, which can reduce the switching times. The efficiency is improved due to the reduction of output current ripple and switching times. Finally, the effectiveness of the proposed overmodulation strategy is verified through experiments.

A maximum torque per ampere (MTPA) control based on virtual signal injection for interior permanent magnet synchronous motor (IPMSM) with fast dynamic response is proposed in this paper. A small square wave signal is mathematically injected into current angle for accurately tracking MTPA points. The extracted derivative of elctromagnetic torque is utilized to compensate the initially set current angle to the real MTPA operation current angle. Due to the absence of bandpass and lowpass filters which are essential in the sinusoidal injected signal scheme, this method shows good dynamic response. By incorporating a modified equation for the torque after signal injection, the steady-state accuracy is also enhanced. The d- and q-axes current references are obtained through the current vector magnitude and optimal current angle instead of using the torque equation with nominal motor parameters, which guarantees the accuracy of the output torque. The proposed scheme is parameter independent and no real signal is injected to the current or voltage command. Thus, the problems of high-frequency signal injection method are avoided. A prototype is set up and experiments are carried out to verify effectiveness and robustness of the proposed control scheme.

Due to detection difficulties, dc arc faults are one of the most dangerous risks in dc power systems. Most traditional studies are based on arc current, which may change during normal operation and cause unwanted trips. Another problem with the traditional methods is that the detection threshold may need to be adjusted for different photovoltaic (PV) systems; otherwise, it will cause malfunctions. To solve the aforementioned problems, a series arc fault detection method based on steady patterns of the frequency domain is proposed. The proposed method utilizes the electromagnetic radiation (EMR) emitted by an arc as a testing basis, avoiding the occurrence of unwanted trips. Patterns such as the structural similarity index (SSIM) and 6-dB bandwidth bins (6-dB BWBs) are calculated to extract the similarity of the steady-burning arc spectra. The experimental verification shows that the proposed steady-pattern-based method can accurately identify arc faults in different dc power systems, discriminate arc faults from normal operations, effectively avoid the occurrence of malfunctions, and can be used as a supplementary technique to traditional methods.