Eccentricity in a permanent magnet synchronous motor (PMSM) can cause additional electromagnetic forces and resolver error, which in turn can lead to an aggravation of vibration and noise in the electric drive system. In this paper, the additional electromagnetic forces and the resulting vibration and noise under the conditions of the three-dimensional (3-D) static and dynamic motor eccentricities, the resolve error, and the coupling between these faults, are analytically derived and analyzed, with special emphasis on the coupling effect of the motor eccentricity and resolver error. The results of the present theoretical analyses agree well with those from the finite element simulations and the experimental measurements. It can be concluded from the results that the coupling between the 3-D motor eccentricity and the resolver error will induce additional electromagnetic forces with much more diverse spatial orders and frequencies.

Overheating of windings is one of the key factors limiting the power density of electric machines. However, thermal modeling of windings is challenging due to the extremely fine and heterogeneous structures. Without adequately addressing the microscopic heat flux field in windings, the commonly used models, even those with conductor insulation accounted for, may give divergent estimations for the equivalent thermal conductivity of windings. Considering the negligible thermal resistance of conductors, we propose a perfect-conductor methodology for thermal modeling of windings, which enables us to derive a closed-form solution to the heat flux field in the impregnation between round wires. From this heat flux solution, the effective thermal resistance of the impregnation, which constitutes the vast majority of that of the whole winding, can then be calculated, based on which a homogenization model is obtained for the equivalent thermal conductivity of the winding. A comparative study confirms that the present perfect-conductor model is more reliable than those commonly used ones. Although only windings formed with round wires are considered here, the perfect-conductor methodology can also facilitate addressing the heat flux profile for other winding constructions.

Due to the nonlinearity and dead time of the inverter, a great number of harmonic components is introduced into the motor input current, causing the torque ripple of the motor. The paper aims to suppress the torque ripple of a low-speed and high-torque permanent magnet synchronous motor (PMSM) with a two-step stator voltage optimization method, including a high precision harmonic voltage injection (HPHVC) method and a deep belief network (DBN)-deep neural network (DNN) voltage prediction model. Firstly, a closed-loop harmonic current detection system with Type-II Chebyshev filter is adopted to enhance the harmonic current extraction accuracy. Secondly, a harmonic voltage algorithm is designed considering the dq-axis current coupling relationship, which improves the accuracy of harmonic voltage calculation. Thirdly, a dq-axis voltage prediction model is constructed using DBN-DNN algorithm as the surrogate model, which further reduces the current harmonic components caused by the harmonic injection structure and the PI control algorithm, reduces the torque pulsation of the motor, and boosts the dynamic performance of the motor. Finally, the experimental platform is constructed by embedding the proposed strategy into the field oriented control system for reducing the torque pulsation. The experimental results verify the proposed strategy.

Since the temperature response of an electric machine under a constant duty can be obtained by a single experiment, it is the variable driving cycles that constitute the exact challenge in real-time thermal modeling. This article proposes an excitation-based methodology for real-time temperature estimation. Great detail is presented for the implementation procedure specific to estimating the end-winding temperature of a water-cooled interior permanent-magnet synchronous motor (IPMSM). In this methodology, a linear time-invariant (LTI) representation is devised for the speed-dependent parameter-varying heat-transfer problem of electric machines, followed by a generic solution via Duhamel’s theorem. Each of the response functions in the Duhamel’s integral thermal model is represented by a well-defined auxiliary problem. Computational fluid dynamics (CFD) simulations with calibrated parameters can be conducted to solve these auxiliary problems for the response functions. Because the CFD model features the least equivalent parameters that need experimental calibration, the present methodology can make the most of the geometry and material information and greatly reduce the experimental efforts compared to a data-driven method. Moreover, the present methodology can avoid the need for solving ill-posed inverse heat-transfer problems, and thus the resulted real-time thermal model is pretty reliable and robust.

In the permanent-magnet synchronous machines (PMSMs), the temperature of the permanent magnets (PMs) is hard to estimate, because the heat transfer involving the rotor includes speed-dependent heat convection processes. This paper presents a Duhamel’s integral thermal model for estimating the PM temperature of a water-cooled PMSM. In the present model, the PM temperature transient under highly varying driving cycles is presented as the superposition of the responses to all the major unit-step excitations. The accurate response of the PM temperature to each unit-step excitation can be directly obtained by numerical simulations of the corresponding auxiliary problem with the aid of a high-fidelity CFD model of the PMSM. The present PM temperature estimation model features a universal functional formula, of which the parameterization procedure does not involve the solution nonuniqueness of an inverse identification method. Therefore, it can be easily parameterized for the common radial-flux water-cooled PMSMs.

This article investigates the impact of Hall errors on the speed, rotor position, and current of joint motors in robots, focusing on brushless DC torque motors. On introducing the sensing principle of the Hall sensor in the torque motor system, the influence of circumferential installation errors and axial offset errors on the rotor position and current of the motor is derived analytically on the basis of the Hall vector signals. The results show that Hall errors generate rotor position errors characterized by the occurrence of specific harmonics with inherent deviations in rotor position, which in turn introduce the (2n-1)th current harmonics. The study proceeds to conduct simulations for a comparative evaluation of the degrees of influence exerted by circumferential installation errors and by axial offset errors on the motor speed, rotor position, and current. These findings are then validated through experiments, wherein the characteristics of Hall errors’ influence are elucidated via analysis of speed and current harmonics. This study provides a fresh methodology for analyzing errors in Hall sensors.