Based on neural network model, a method for quantitative sound quality (SQ) evaluation of the interior noise of a pure electric vehicle (PEV) is presented in this paper. The method can be divided into four steps. First, the interior noises under different speeds of a PEV are collected through the interior noise test of the PEV. Subsequently, one physical acoustic parameter (A-weighted sound pressure level) and six psychoacoustic parameters (loudness, fluctuation strength, tonality, roughness, articulation index, and sharpness) are applied to describe the noise samples for objective evaluation of SQ. In the third step, five semantic evaluation indexes, namely, “annoying or pleasing,” “harsh or sweet,” “weak or powerful,” “promiscuous and pure,” and “unobservable or perceptible,” are proposed based on semantic differential method, which are used for subjective evaluation of SQ by jury tests. Finally, the neural network model for SQ evaluation of the interior noise of the PEV is established, the SQ characteristics of the interior noise of the PEV are evaluated, as well as revealing the coefficient weight of influencing factors. This model can be used for SQ prediction and evaluation of the interior noise of the PEV considering that the average error is 9%.

By measuring the open-circuit radial stray magnetic flux density (RSMFD) of three spatial points, a novel diagnostic method for the eccentricity of interior permanent magnetic motors (IPMSMs) in electric vehicles is proposed. Outperforming traditional methods, the proposed method can noninvasively diagnose not only the severities of static eccentricity (SE), dynamic eccentricity (DE), and mixed eccentricity (ME), but also the eccentricity location. In this article, diagnosis results are described through three eccentricity parameters: SE ratio, DE ratio, and SE angle. First, an analytical model of the open-circuit RSMFD of the IPMSM is proposed, with its accuracy validated by experiments. The pattern of the impact of the eccentricity parameters on the open-circuit RSMFD is analyzed to form the basis of the proposed method. Then, an eccentricity prototype motor, which can continuously emulate the eccentricity according to any listed eccentricity parameters, is developed. A test rig is built to collect the open-circuit RSMFD and validate the analytical calculation results. Finally, an eccentricity diagnostic model based on the open-circuit RSMFD is established. The diagnosis results proved the noninvasiveness, effectiveness, and viability of the proposed method.

To accurately and quickly predict the open-circuit air-gap magnetic field in interior permanent magnet synchronous machines (IPMSMs), an analytical model based on magnetic equivalent circuit (MEC) method is proposed. The analytical model can provide radial and tangential components of open-circuit magnetic field in the slotless air gap. The radial component is obtained from the MEC model, and the tangential component is obtained from boundary conditions of macroscopic equations. Then, a complex relative air-gap permeance is applied to take the effect of slots into account. As a result, an accurate solution of both radial and tangential components of the flux density in the slotted air gap is obtained. Additionally, the no-load back electromotive force (EMF) and cogging torque are calculated based on the open-circuit air-gap magnetic field. All the analytical results are verified by the finite element (FE) analysis and they are well matched. In the end, a direct measurement experiment of open-circuit air-gap magnetic field is proposed to verify the validity of both radial and tangential open-circuit air-gap magnetic fields.

An analytical method for calculating the no-load magnetic field of external rotor permanent magnet brushless direct current motor (PMBLDCM) used as in-wheel motor of electric vehicle in the stator static coordinate and the rotor motion coordinate is presented in this paper. First, the analytic formulas of slotless permanent magnetic field in both coordinate systems are derived, respectively. Then, the complex relative permeance of external rotor PMBLDCM in both coordinate systems is calculated. Finally, the analytical solution of the no-load magnetic field in both coordinate systems is derived by applying the magnetic potential multiplied by the complex relative permeance. In this paper, a 46-pole-51-slot external rotor PMBLDCM is taken as an example, and the accuracy of the proposed analytical model is verified by the finite-element results. Based on the analytical model, the influences of the stator slotting effect on the no-load magnetic field of the external rotor and the inner stator are analyzed. The spatial order characteristics and frequency characteristics of the no-load magnetic field of the external rotor PMBLDCM in both coordinate systems are revealed, respectively.

In an interior permanent magnet synchronous motor (IPMSM) with segmented skewed poles, the armature reaction magnetic field (AR-MF) changes nonlinearly due to the saturation of the rotor magnetic barrier. Meanwhile, this varies under different excitation currents. As a result, it is difficult to be calculated by means of analytical methods. In this paper, the calculation model of AR-MF of IPMSM is first established by vector superposition method, without considering the saturation effect of rotor and the slotting effect of stator. In the second step, the virtual magnetic field of the rotor is introduced to quantitatively calculate the influence of local inhomogeneous saturation on the AR-MF. The latter is derived by combining both the subdomain method and equivalent magnetic circuit method. The complex relative permeance is also introduced to establish the AR-MF accounting for the stator slotting effect. To validate the AR-MF calculation method proposed, an 8-pole 48-slot IPMSM with segmented skewed poles is considered as a case study, showing a comparison by both with finite element (FE) results and the electromagnetic torque measured on a test bench. The model proposed in this paper shows high accuracy and fast computation with respect to FE analysis.

In this article, a new data-driven diagnosis method is proposed for mixed eccentricity (ME) in the external rotor permanent magnet motors (ERPMMs). Differently from the previous articles, the proposed method has the advantages of large sample size, high sample diversity, high efficiency, and strong generalization ability. First, the improved parametric analytical model (AM) of back electromotive force (EMF) of the ERPMMs is established. Then, the characteristics of the back EMF are analyzed. Accordingly, its amplitudes of fundamental waves and sideband harmonics are selected as the ME indexes. Afterwards, by using the proposed parametric AM, a database of ME signals is established efficiently, which contains tens of thousands of labeled samples. Furthermore, based on the back propagation neural network, a high-precision diagnosis model for ME in the ERPMM is established. Interference faults, such as unbalanced stator windings and uneven magnetization are also discussed. Finally, an experimental prototype for simulating the ME is manufactured and the effectiveness of the proposed method is verified. The maximum absolute diagnostic error is less than 4.0%. It provides a new idea for multiparameter diagnosis for ME.