PMSM Drives and its Application: An Overview

Singh, Shweta; Singh, Shubham; Tiwari, Aditya

doi:10.2174/2352096515666220812091445

Cited by 7 publications

(4 citation statements)

References 49 publications

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“…In addition, we propose a gain-tuning procedure to find the optimal gains of observer and controller. This proposed method is expected to be suitable for stable operation in environments where the PMSM's parameters change due to long-term operation or torque changes rapidly [26,27].…”

Section: Introductionmentioning

confidence: 99%

Linear Matrix Inequality-Based Robust Model Predictive Speed Control for a Permanent Magnetic Synchronous Motor with a Disturbance Observer

Kim,

Kim

2024

Energies

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In this paper, a linear matrix inequality (LMI)-based robust model predictive speed control (RMPSC) with a disturbance observer (DOB) is proposed to guarantee stability and control performance against the parameter uncertainty and disturbance of a permanent magnetic synchronous motor (PMSM). All external torques applied to the PMSM are defined as disturbance, estimated by the DOB, and used to construct the RMPSC method. The proposed DOB and RMPSC are determined by a multiple LMI-based optimization approach. Furthermore, parameter uncertainty within a certain range, due to manufacturing errors or aging deterioration, is considered and a systematic tuning method is proposed to obtain the optimal gains. Finally, an offline optimization method is developed that ensures a low computational load to enable real-time processing. Simulation results demonstrate the effectiveness and validity of the proposed control method.

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Section: Introductionmentioning

confidence: 99%

Linear Matrix Inequality-Based Robust Model Predictive Speed Control for a Permanent Magnetic Synchronous Motor with a Disturbance Observer

Kim,

Kim

2024

Energies

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“…Permanent magnet synchronous motor (Permanent magnet synchronous motor, PMSM) is attractive for transportation, aerospace, household and the other application [1]- [12] due to simple structure, reliable operation, fast response and high efficiency. To implement coordinate transformation and decoupling control in the field-oriented control of PMSM, information about the speed and the position of the rotor must be known [13]- [16].…”

Section: Introductionmentioning

confidence: 99%

Effects of Electromagnet Interference on Speed and Position Estimations of Sensorless SPMSM

XUE,

YAN,

LIU

et al. 2024

IEICE Trans. Electron.

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Model-based sensorless control of permanent magnet synchronous motor (PMSM) is promising for high-speed operation to estimate motor state, which is the speed and the position of the rotor, via electric signals of the stator, beside the inevitable fact that estimation accuracy is degraded by electromagnet interference (EMI) from switching devices of the converter. In this paper, the simulation system based on Luenberger observer and phase-locked loop (PLL) has been established, analyzing impacts of EMI on motor state estimations theoretically, exploring influences of EMI with different cutoff frequency, rated speeds, frequencies and amplitudes. The results show that Luenberger observer and PLL have strong immunity, which enable PMSM can still operate stably even under certain degrees of interference. EMI produces sideband harmonics that enlarge pulsation errors of speed and position estimations. Additionally, estimation errors are positively correlated with cutoff frequency of low-pass filter and the amplitude of EMI, and negatively correlated with rated speed of the motor and the frequency of EMI. When the frequency is too high, its effects on motor state estimations are negligible. This work contributes to the comprehensive understanding of how EMI affects motor state estimations, which further enhances practical application of sensorless PMSM.

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“…R ECENTLY, the rapid advancement of permanent magnet material and power electronics technology has led to the wide usage of permanent magnet synchronous drives (PMSM) in electric vehicles, aeroplanes, wind turbines, and in-house appliances [1]. PMSM drives have unique advan-tages of a high power-to-weight ratio, excellent dynamics, high torque, and a wide range of operating conditions.…”

Section: Introductionmentioning

confidence: 99%

Robust Multiple-Fault Diagnosis of PMSM Drives Under Variant Operations and Noisy Conditions

Mahmoud,

Huynh,

Senanyaka

et al. 2023

IEEE Open J. Ind. Electron. Soc.

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With the rapid development of industrial applications using permanent magnet synchronous drives (PMSM) and the Internet of Things, the demand for using robust fault diagnosis methods working in noisy conditions has increased significantly. The current data-driven methods depend mainly on deep learning (DL) models due to the effectiveness of automated feature extraction. However, these models have shallow depths compared with benchmark convolution neural networks, limiting their accuracy in final predictions, and they are established based on the hypothesis that the measured data is noiseless. Despite this, electric machinery is subjected to various noise sources that interfere with measurements during operation. This article proposes a new scheme combining a transfer-learned pre-trained residual neural network (ResNet) and supervised machine learning (S-ML) to enhance the performance of deep learning models in noisy industrial environments. The effectiveness of the proposed scheme is validated using an in-house setup of a PMSM drive with demagnetization and intern-short circuit faults at variant operating conditions. The results show that the proposed method significantly reduced the computational burden by tenfold on average while improving the average accuracy to 96.84 % across all the datasets compared with other DL and S-ML methods, with high robustness in noisy working conditions.INDEX TERMS Deep transfer learning, data-driven fault diagnosis, hybrid learning, permanent magnet synchronous motors (PMSMs), pre-trained deep models, wavelet analysis.

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PMSM Drives and its Application: An Overview

Cited by 7 publications

References 49 publications

Linear Matrix Inequality-Based Robust Model Predictive Speed Control for a Permanent Magnetic Synchronous Motor with a Disturbance Observer

Linear Matrix Inequality-Based Robust Model Predictive Speed Control for a Permanent Magnetic Synchronous Motor with a Disturbance Observer

Effects of Electromagnet Interference on Speed and Position Estimations of Sensorless SPMSM

Robust Multiple-Fault Diagnosis of PMSM Drives Under Variant Operations and Noisy Conditions

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