Hybrid flux predictor‐based predictive flux control of permanent magnet synchronous motor drives

Fu, Rong; Cao, Yang

doi:10.1049/elp2.12168

Cited by 3 publications

(2 citation statements)

References 25 publications

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“…( 4), T L is the load torque, ω m represents the mechanical angular velocity of the rotor, J represents the rotational inertia, and B m represents the friction coefficient. However, in practical situations, the inductance parameters are easily affected by factors such as saturation effects in the motor's magnetic circuit and changes in temperature, resulting in non-linear changes [17]. This study uses torque model reconstruction and numerical calculation to extract the MTPA criterion.…”

Section: Synrm-mtpa Control Based On Vsimmentioning

confidence: 99%

Optimal control of maximum torque current ratio for synchronous reluctance motor based on virtual signal injection algorithm

Cui

2024

Archives of Electrical Engineering

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This study focuses on the maximum torque current ratio control of synchronous reluctance motors and proposes an optimized control method for the maximum torque current ratio of synchronous reluctance motors based on virtual signal injection. Firstly, the research on the maximum torque current ratio control of synchronous reluctance motors based on the virtual signal injection method is conducted, and the existing virtual unipolar square wave signal injection method is analyzed and studied. Secondly, a non-parametric maximum torque current ratio control strategy based on a synchronous reluctance motor combined with the virtual signal injection method is proposed. This strategy does not involve complex parameter calculations, and the control accuracy is not limited by the accuracy of the parameters in the model. The experimental results showed that under the control of virtual bipolar and unipolar square wave signal injection methods, the load torque was converted from 2 Nm to 6 Nm at t = 2:5 s, and there was a significant change in the current amplitude and waveform of the current vector. Under the control of the bipolar injection method, the current amplitude waveform of the motor was lower than that of the unipolar waveform, and the current was smaller. After the load suddenly changed, it could enter a stable state faster. After the load changed at t = 2:5 s, the phase angle of the current vector was quickly adjusted and stabilized under the control of the bipolar signal. The designed method has a good optimization effect compared to the traditional virtual signal injection method, and can achieve high-performance maximum torque current ratio optimization control on synchronous reluctance motors.

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Section: Synrm-mtpa Control Based On Vsimmentioning

confidence: 99%

Optimal control of maximum torque current ratio for synchronous reluctance motor based on virtual signal injection algorithm

Cui

2024

Archives of Electrical Engineering

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“…According to the different voltage vector control sets, MPC is able to be divided into continuing control set model predictive control (CCSMPC) and limited control set model predictive control (FCSMPC). The FCSMPC makes perfect use of incontinuous features of inverter switching device [2]. Based on the predictive model of the control target, it directly traverses the voltage complexors matching to all possible on-off states of inverter, calculates matching predictive value, and identifies the first-rank voltage vector.…”

Section: Introductionmentioning

confidence: 99%

Finite control set model-free predictive current control of permanent magnet synchronous motor

Zou,

Yang,

Zhang

et al. 2024

J. Phys.: Conf. Ser.

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This thesis proposes finite control set model-free predictive current control (FCSMFPCC) algorithm of permanent magnet synchronous motor (PMSM). To address issue of degraded performance during motor operation due to parameter mismatch, a model-free predictive current control arithmetic is devised, which utilizes ultra-local model (ULM) of PMSM. This proposition takes sum of known and sealed disturbances of the system as an unknown quantity, and uses sliding mode observer (SMO) to take stock of sealed quantity. To address the issue of operation delay in predictive control, a two-step method is used to make up for the system. When using price function to choose the first-rank voltage vector, vector selection optimization link is added, which effectively simplifies the algorithm while optimizing the inverter switching action. The simulation outcomes highlight the advantages of the described control algorithm in terms of better dynamic response performance and stronger robustness.

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Monitoring Method of Permanent Magnet Synchronous Motor Temperature Variation Signal Based on Model Prediction

Liu,

Yin,

Sun

et al. 2024

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Hybrid flux predictor‐based predictive flux control of permanent magnet synchronous motor drives

Cited by 3 publications

References 25 publications

Optimal control of maximum torque current ratio for synchronous reluctance motor based on virtual signal injection algorithm

Optimal control of maximum torque current ratio for synchronous reluctance motor based on virtual signal injection algorithm

Finite control set model-free predictive current control of permanent magnet synchronous motor

Monitoring Method of Permanent Magnet Synchronous Motor Temperature Variation Signal Based on Model Prediction

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