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.

This paper presents a nonlinear hybrid field model to predict the open-circuit magnetic field distribution in surface-mounted permanent-magnet machines. It combines the complex permeance model (CPM) with the magnetic equivalent circuit (MEC). The saturation effect is accounted for in the CPM by considering the magnetic potential distribution on the stator bore, which is calculated by the MEC and can be transformed to the virtual current on the slot. The proposed model significantly improves the calculation accuracy for saturated machines, which is verified by the finite-element analysis and the experimental results.

This paper develops an improved hybrid field model (IHFM) to predict the on-load performance of interior permanent-magnet (IPM) motors considering both iron saturation and slotting effect. It combines the air-gap analytical model based on modified conformal mapping with the reluctance mesh method for stator and rotor. The reluctance mesh method can accurately predict the rotor saturation and tooth-tip saturation even their field distribution is complicated due to armature reaction. Besides, IHFM will significantly accelerate computation speed using analytical model for air-gap region while keeping high accuracy. The finite-element analysis and experimental results of flat-type and V-type IPM motors are demonstrated to verify the effectiveness of the proposed model.

This article proposes two kinds of asymmetric flux reversal permanent magnet linear machine (AFR-PMLM) for long excursion application. By utilizing asymmetric permanent magnet excitation, the AFR-PMLM can effectively generate and fully exploit the second-order harmonic magnetomotive force (MMF), leading to a significant enhancement in thrust force density. First, the machine topology and operation principle are introduced. Then, the thrust force generation mechanism under multi MMFs is analytically calculated based on an improved MMF-permeance model, and further verified by finite element analysis. Various electromagnetic performances, including open-circuit characteristics, thrust force performances, and power factor, are comparatively studied. It shows that the proposed AFR-PMLM with consequent pole structure can provide 40.1% higher average force than conventional FR-PMLM under rated condition. In addition, it consumes only about 39.5% of the PMs volume while providing approximately 90.4% of the thrust force compared with switched flux PMLM. More importantly, the AFR-PMLM consumes only 1/80 PMs volume while achieving 75.0% of the thrust force density compared with conventional PMLM for a long excursion with 10 m. Finally, two prototypes of AFR-PMLM are manufactured for experimental validation.

This article proposes a modified deadbeat predictive current control (M-DPCC) method to improve the dynamic performance of permanent magnet synchronous motor (PMSM). Classical DPCC only predicts one control cycle of the PMSM, which restricts the dynamic performance since multiple control cycles are required for the transient state under heavy load and rated speed working condition. The proposed M-DPCC extends the single-step prediction to the entire dynamic interval in the transient state, by which the comprehensive optimization on the angle of the stator voltage vector can be implemented. Moreover, M-DPCC performed multi-step deadbeat calculation to keep the computation modest. To verify the effectiveness of the proposed M-DPCC, transient-state performance of PMSM using the M-DPCC method, the modulated model predictive control and classical DPCC are explored under a wide range of working condition. Comparative simulation and experimental results indicate that dynamic performance of the PMSM can be improved, especially under rated speed and heavy load conditions. Besides, the parameter sensitivity to inductance mismatch of the three methods is carried out. The stable operation range of the M-DPCC under inductance mismatch is larger than the other two methods. Moreover, the computation complexity of the three methods were investigated. The M-DPCC acquired less computation time than the modulated model predictive control.

This paper presents a comprehensive study on the fractional slot concentrated winding (FSCW) interior permanent magnet synchronous motors (IPMSMs) with different pole slot combination for the application of electric vehicle (EV) and hybrid electric vehicle (HEV). Three motors with the same dimension constraint and rated parameters are designed and optimized. With the optimized motors, winding factors and magnetomotive force (MMF), inductances, torque capacity, constant power speed range (CPSR), the losses, the efficiency, demagnetization capability and vibration are investigated and compared. The comparison results show that 12/8 motor and 12/10 motor have their respective unique advantages while 12/14 motor is not as good as the others.