Search

This article proposes an auxiliary notch design method for the interior permanent magnet (IPM) machines for suppressing torque ripple. The key principle of this design method is to identify the main source of torque ripple, then guides the modification of reluctance variation along the rotor surface. First, the theoretical analysis of the torque ripple in IPM machines are investigated to guide the auxiliary notches design. Based on this, a spoke-type IPM machine with permanent magnet torque as the main component and a U-type IPM machine dominated by reluctance torque are analyzed, respectively. Additionally, the relationship between the shifted angle of the auxiliary notch and the order of torque ripple is revealed. Furthermore, the electromagnetic performances are investigated by the finite-element method. After using auxiliary notch design, the torque ripple is significantly reduced and the torque amplitude is almost not sacrificed. Finally, a spoke-type IPM machine prototype is manufactured for experiments to evaluate the effectiveness of the theoretical analysis.

Recent literature has confirmed that a high-order radial pressure in airgap can induce significant low-order vibration due to the stator teeth modulation effect on radial pressure. The reported research on this modulation effect only focused on the conventional stator teeth topologies. However, for the permanent magnet (PM) machines, different stator teeth topologies lead to diverse paths for the transfer of pressure in airgap, resulting in varying vibration characteristics caused by the modulated radial pressures. It is plausible that dual or nonuniform modulation on radial pressure may be present. Therefore, to accurately predict and preferably reduce vibration, it is crucial to understand the diverse effects of different stator teeth modulation. In this article, first, the principle behind how the stator teeth modulate the radial pressure is explained. Second, the modulation effects of different stator teeth are detailedly analyzed, including single, dual, uniform, and nonuniform modulations. Lastly, taking a PM vernier machine as an example, its modulated radial pressures and resulting vibration are analyzed considering the nonuniform dual modulation. Results demonstrate that the stator teeth modulation effects on radial pressure are various and should be fully considered in accurate vibration prediction and low-vibration machine design.

The conventional fault-tolerant direct torque control (DTC) strategy not only needs to diagnose open-circuit fault phase but also needs reconfiguration of switching table, transformation matrix, and structure of control system according to the specific fault phase, thus increasing the complication of the control algorithm. To solve this problem, a switching-table-based diagnosis-free fault-tolerant DTC for five-phase permanent magnet synchronous motor was proposed in this article. The novelty of the proposed strategy is the development of fault-tolerant switching table. Based on this, the conventional DTC without diagnosis can operate smoothly under both healthy and open-circuit fault conditions. The switching table does not need to change the sector division or the basic voltage vector (VV) and its dwell time that constitutes the virtual voltage vector (V3) when open-circuit fault occurs in any phase. Thus, the open-circuit fault diagnosis and the reconfiguration of control system can be avoided. The proposed DTC strategy can not only restrain the torque fluctuations caused by any-phase open-circuit fault but also reduce the third harmonic currents and have good dynamic performance both under healthy and fault conditions. The feasibility of the proposed strategy was verified by the experimental results.

This article proposes a new method, simultaneously considering inter-turn short-circuit (ITSC) fault diagnosis and fault-tolerant control of a five-phase permanent magnet synchronous motor (FPMSM), to realize an online diagnosis and fault-tolerant operation. This article is focused on linking the signals required for fault-tolerant control with diagnostic algorithms. The method uses a disturbance observer to obtain the disturbance signal from the ITSC and directly utilizes the fault characteristics in the disturbance signal for fault-tolerant control. No additional fault parameters (short-circuit current and short-circuit turn ratio) and no additional hardware equipment are required in this process while reducing the complexity of the fault-tolerant control method of FPMSM. In addition, since fault-tolerant reference current and injected current are both ac signals, the deadbeat current prediction control is constructed for fault conditions to track the signals accurately. The effectiveness and feasibility of the method are verified by simulation and experiment.

Efficiently extracting long-term sequence features is the key for deep learning models to accurately predict the remaining useful life (RUL) of mechanical bearings. However, completely ignoring local features may result in losing a large amount of prediction information. In addition, the existing soft thresholding function loses a large number of feature values when denoising, which affects the prediction performance of the network. A new temporal convolutional neural network with an adaptive activation function and attention mechanism (TCNAAM) for RUL prediction is proposed in this article. The network consists of two branches; one branch is to be utilized to adaptively select key local information in the time series using an adaptive convolutional scale attention layer. The other branch is feature denoising by adding an improved activation function after the temporal convolutional neural network during training, to preserve most of the original features. Therefore, TCNAAM can simultaneously extract long-term and short-term information and constrain all eigenvalues within a certain interval. The bearing dataset on Xi'an Jiaotong University and IEEE PHM Challenge 2012 is used to validate the effectiveness of the proposed TCNAAM. Experimental results show that the proposed TCNAAM performs better than some existing prediction methods for bearings RUL prediction applications under different operating conditions.

Sensorless control methods based on flux observer have been widely used in motor drives with medium-high speed operation. However, the conventional methods have some shortcomings in estimation accuracy due to the dc bias caused by the integration, measurement, and parameter uncertainty. In this article, a new frequency adaptive disturbance observer with band-pass filter characteristics is proposed. It is insensitive to dc bias and high-frequency noise, hence improving the robustness of the system. Since the proposed method has no phase delay at any synchronous rotor frequency and can amplify the amplitude of the estimated active flux, it does not need a phase compensation module and can obtain a wider operating range. Moreover, an adaptive extended state observer is added to estimate the disturbance caused by parameter mismatch. The estimated disturbance is fed back to the estimated active flux, which further improves the accuracy of the system. Finally, experiments based on a triple redundant permanent magnet-assisted synchronous reluctance motor are accomplished to verify the effectiveness and accuracy of the proposed observer.

This article focuses on electromagnetic vibration analysis of the permanent magnet vernier machine (PMVM) and aims to reduce electromagnetic vibration of the PMVM. First, we analyze the magnetic field and radial force of the PMVM by finite-element method and analytical method. The results show that the 2nd radial force at 2fe can generate serious electromagnetic vibration. Then, an unequal stator modulated teeth structure is proposed to reduce the 2nd radial force to reduce the electromagnetic vibration. We compare the electromagnetic performance of the proposed PMVM with that of the original PMVM. The results show that the electromagnetic performance of the proposed PMVM is not influenced. What is more, we adopt the modal and the electromagnetic vibration analysis of the original PMVM and the proposed PMVM. The results indicate that the proposed PMVM can reduce electromagnetic vibration. Finally, we manufacture the prototype to verify the previous analysis results, the results of theoretical analysis and finite-element method are verified by the prototype test.