In recent years, permanent magnet (PM) vernier machines have gained more and more attention due to their high torque density and simple mechanical structure. However, PM vernier (PMV) machines with lap windings always suffer from long end winding length, and regular nonoverlapping winding may result in torque reduction for PMV machines. In this paper, an advanced PMV machine topology with multiple working harmonics is proposed. With specially designed stator auxiliary teeth, this topology could achieve ~20% higher torque density than that of a regular nonoverlapping winding PMV machine, with the same magnet usage. Through finite element algorithm and theoretical analysis, the production of additional flux density harmonics and their contributions to back-electromotive force (EMF) are verified. Moreover, the electromagnetic performances of this novel machine topology, such as back-EMF and output torque, are quantitatively investigated with the geometric parameters' effect considered. Finally, analysis results are verified by experimental test on a 21 Nm prototype, which is designed to have similar volume and weight with a 14 Nm regular commercial PM machine.

In order to improve the efficiency, interior permanent magnet synchronous motors (IPMSMs) or the synchronous reluctance motors (SynRMs) need to be calibrated to obtain the maximum torque per ampere (MTPA) and flux-weakening (FW) curves. In industrial application, there are different types of IPMSMs and SynRMs. It is expensive and time-consuming to build test benches to calibrate each motor. In this letter, a physics-informed network is proposed to obtain the MTPA and FW operating curves. Only data from accelerating experiment, when motor operates without load, are adopted. The test bench is unnecessary. Experimental results show the validity of proposed method.

This paper introduces series work of common-mode (CM) voltage reduction for the paralleled inverters. The paralleled inverters’ phase-legs are connected through coupling inductors and the combined three phase currents are provided to the load. Interleaving is an approach to reduce the CM voltage for the paralleled inverters but cannot eliminate CM voltage. A novel PWM method for paralleled inverters which can theoretically achieve zero CM voltage is developed. Considering the basic voltage vectors in each inverter, novel paralleled voltage vectors which have zero CM voltage are proposed to combine the reference voltage. The action time’s distribution and voltage vectors’ sending sequence for each inverter are also introduced. The proposed PWM method can make sure the voltage of the two inverters balancing in each switching cycle and limiting the circulating current through small coupling inductors. Similar with interleaving SVPWM, the proposed zero CM PWM also have the ability to reduce the output current ripple and EMI, too. Simulation and experimental results are provided to show the advantage of paralleled inverters in CM voltage reduction and validate the proposed method has good performance to reduce CM current and CM EMI noise.

In voltage source inverters (VSI), dead-time is used to prevent shoot-through over switching devices. However, the existence of dead-time will distort output phase current which degrades the performance of inverter as well as influences the common-mode voltage (CMV), particularly in CMV elimination relevant modulation schemes, such as zero-CM PWM based paralleled inverters. On the basis of the situation that the normal sampling based dead-time compensation (DTC) methods are often disturbed by the current ripple, this paper introduces a novel DTC method for VSI which can mitigate the impact of current ripple and improve the accuracy of DTC. The proposed method deduces the real-time current ripple which can reconstruct the actual trajectory of phase-leg currents, and the peak values corresponding to rising and falling edges for pulse width modulation (PWM) signals can be predicted. In this way, DTC can be implemented based on the direction of relevant instantaneous switching currents and finally improve the accuracy. Especially, the current ripple prediction (CRP) based DTC can help to improve the CMV distortion caused by dead-time for paralleled inverters with zero-CM PWM. Simulation and experimental results are provided to validate that the proposed method can be applied with good performance.

Dueto various kinds of stator phase arrangements, existing fault diagnosis (FD) methods cannot be applied to different types of multiphase machines. Spurred by the era of big data and artificial intelligence, an improved machine-learning-based FD method with adaptive secondary sampling filtering is proposed for the multiphase drive systems. Experimental results of the proposed method on both five-phase and six-phase motor drive platforms validate its satisfying generalization capability as well as high accuracy and strong robustness.