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191 results on '"Ding, Shichuan"'

13. The Leaf-Style Axial Field Variable Reluctance Resolver With an Efficient Decoding System

Author

Sun, Le, Kong, Tianxiang, Wu, Chun, Zhang, Luhua, Wang, Wei, and Ding, Shichuan

Abstract

The leaf-style slotless resolver has been proposed in the form of the stator permanent magnet (PM) variable reluctance resolver. The prototype is specially designed only for high-speed scenarios, as the PM cannot generate a significant motion electro-motive force (EMF) at zero- and very low speed. This article proposes a more practical prototype and its dedicated system, which has two valuable features. First, the resolver size and cost can further reduce to an ignorable level, including only two tiny pieces of iron and a small printed circuit board. The electrical high-frequency excitation is adopted instead of the magnets; then the decoding system can cover the speed range from zero to several kilo r/min. However, the limited space and slotless structure weaken the excitation and EMF signals. The square waveform injection is thus introduced to solve this issue. The hardware circuit and software computation requirements are friendly to be implanted into a cost-sensitive motor driver. The proposed resolver system has been integrated into a servo motor drive system and tested in experiments.

Published
2024
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21. Improved Fault Diagnosis Method for Permanent Magnet Synchronous Machine System Based on Lightweight Multisource Information Data Layer Fusion

Author

Hang, Jun, Qiu, Gaopeng, Hao, Menglu, and Ding, Shichuan

Abstract

Fault diagnosis is essential for the safe operation of a permanent magnet synchronous machine (PMSM) system. At present, the fault diagnosis method based on deep learning has been gradually studied due to its ability to automatically extract fault features and an end-to-end diagnostic model. However, this method often uses a single-source signal, resulting in poor fault diagnosis performance. On the other hand, deep learning model typically requires large amounts of storage and computational resources, especially when processing multisource signals. Hence, this article proposes an improved fault diagnosis method for PMSM systems based on lightweight multisource information data layer fusion. In this method, the original multisource information is fused at the data layer. Then the fused information is input into the constructed lightweight deep learning model to implement fault diagnosis of PMSM system, where a one-dimensional convolutional neural network with the combination of depth-separable convolution and global average pooling is first presented to reduce the computational time and complexity of the fault diagnosis method. The simulation and experimental results show that the proposed fault diagnosis method can achieve accurate fault identification of the PMSM system and can reduce the requirement for storage and computational resources, indicating the effectiveness of the proposed fault diagnosis method.

Published
2024
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22. Robust Diagnosis of Partial Demagnetization Fault in PMSMs Using Radial Air-Gap Flux Density Under Complex Working Conditions

Author

He, Wang, Hang, Jun, Ding, Shichuan, Sun, Le, and Hua, Wei

Abstract

Partial demagnetization fault (PDF) is a common problem for permanent magnet synchronous motor (PMSM). The PMSM usually operates under complex working conditions (dynamic speed and various load), leading to the difficulty in robust PDF diagnosis. Hence, how to reliably and accurately diagnose PDF under complex working conditions has become a key issue in ensuring its safe operation. To address this issue, a robust PDF diagnosis method for PMSM is proposed based on radial air-gap flux density in this article. First, the d-axis magnetic network model of PMSM is established to extract the fault feature from the radial air-gap flux density. Then, by subtracting the offline-calculated radial air-gap flux density of stator current excitation from the online measured value, the open-circuit radial air-gap flux density can be calculated. Next, the equiangular interval resampling method is used to obtain the open-circuit radial air-gap flux density with respect to rotor position angle. Finally, through analysis of open-circuit radial air-gap flux density in angular coordinates, not only PDF can be detected and the fault degree can be estimated, but also the demagnetized PM can be located under complex working conditions. Both the simulation and experimental results validate the effectiveness of the proposed PDF diagnosis method.

Published
2024
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23. Enhanced robust diagnosis of multiple‐type demagnetisation fault for permanent magnet synchronous motor based on D‐axis magnetic network model using magnetic field reconstruction.

Author

He, Wang, Hang, Jun, and Ding, Shichuan

Subjects
PERMANENT magnet motors, MAGNETIC fields, AIR gap flux, PERMANENT magnets, FAULT diagnosis, RADIAL distribution function
Abstract

Demagnetisation fault (DF) is a common rotor fault in the permanent magnet synchronous motor (PMSM). DF can cause obvious changes in the magnetic field of PMSMs. As a result, previous DF diagnosis methods mainly depends on magnetic field analysis. However, conventional analysis methods based on the magnetic potential‐permeability method, sub‐domain method and magnetic equivalent circuit method are not suitable for DF condition. In addition, DF diagnosis is further complicated by various operating conditions. To address these issues, a robust DF diagnosis method is proposed for PMSM based on d‐axis magnetic network model using magnetic field reconstruction. The proposed fault diagnosis method employs magnetic field reconstruction to obtain the radial air‐gap flux density under the open‐circuit condition. Subsequently, a d‐axis magnetic network is established to solve the demagnetisation coefficient matrix in the DF state. Finally, the effectiveness of the proposed method is validated through simulations and experiments. Both results demonstrate that the proposed method can accurately recognise uniform DF and partial DF with multiple demagnetised permanent magnets, exhibiting great robustness against different operating conditions. [ABSTRACT FROM AUTHOR]

Published
2024
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24. Optimized Control for MMCs with Reduced Power Loss and Extended Lifetime.

Author

Zhao, Jifeng, Pei, Jia, Sun, Yun, Wang, Rujin, Hang, Jun, and Ding, Shichuan

Subjects
POWER semiconductors, SEMICONDUCTOR devices, HIGH voltages, OPERATING costs
Abstract

Modular multilevel converters (MMCs) are widely applied to medium and high voltage occasions. The total power consumption of the submodule (SM) and the maximum power consumption of power devices in the SM are related to the operating costs and lifetime of the MMC. Existing literature only considers total power loss optimization or maximal power consumption optimization in MMC's SM. In this article, a reduced loss and extended lifetime power loss optimum control (RLEL-PLOC) is introduced to inject the first-best second harmonic circulation into the MMC's arm current. Compared with the conventional power loss optimization control, the proposed control could decrease the maximal power consumption of the semiconductor devices without increasing the total loss of the SM. According to study results of the MMC, compared with the circulating current suppression control (CCSC) method, the total power consumption of the SM could be reduced by 4.2% and the maximal power dissipation in the SM could be reduced by 5.4% with RLEL-PLOC. PSCAD simulation and MMC prototype experiment are also carried out, and the research results verified the availability of the put forward RLEL-PLOC for MMCs. [ABSTRACT FROM AUTHOR]

Published
2024
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48. A Voltage-Distortion-Based Method for Robust Detection and Location of Interturn Fault in Permanent Magnet Synchronous Machine.

Author

Hang, Jun, Hu, Qitao, Sun, Wushuang, Ren, Xixi, Ding, Shichuan, Huang, Yourui, and Hua, Wei

Subjects
PERMANENT magnets, FAULT location (Engineering), FAULT diagnosis, MACHINERY, MATHEMATICAL models, GEARING machinery vibration
Abstract

In this article, a voltage-distortion-based method is presented for robust detection and location of interturn fault (ITF) in permanent magnet synchronous machine (PMSM). The mathematical models of PMSM under healthy and fault conditions are presented. According to the mathematical model, the dq-axis voltage distortions owing to ITF are estimated through Luenberger observer. On the basis of the voltage distortions, a fault characteristic signal (FCS) is constructed for ITF diagnosis. Through analyzing FCS, the second harmonic component in FCS is chosen to construct the fault indicators for fault diagnosis. The simulation and experimental results show that the ITF diagnosis is effectively realized through the presented method. Additionally, the presented method requires no additional hardware and has good robustness against parameter mismatch and rotating speed variation. [ABSTRACT FROM AUTHOR]

Published
2022
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