An improved rotating HF signal injection method based on FIR filters for state estimation of BPMSM sensorless control

Abstract

An improved rotating high-frequency signal injection method based on a finite impulse-response filter for state estimation of bearingless permanent magnet synchronous motor sensorless control is developed in this article. A novel equiripple optimal approximation finite impulse-response filter, which can achieve that the maximum error of pass-band and stop-band is minimum than other finite impulse-response filter under the conditions of the same-order magnitude, is introduced to extract the high-frequency current signal and realize minimum extraction error. The rotor position error signal can be extracted using heterodyning processing to the high-frequency current. The proposed method can effectively eliminate the synchronous shaft filter and reduce the complexity of the system. Linear-phase compensation is used in the finite impulse-response filter to achieve minimum delay of rotor speed and position estimation. The BPMSM sensorless vector control system is set up based on this estimation approach. Simulation results indicate that the proposed method integrated off-line optimization of a finite impulse-response filter and linear-phase compensation can accurately estimate the rotor position and speed in the full-speed range.

Research on Displacement Sensorless Control for Bearingless Synchronous Reluctance Motor Based on the Whale Optimization Algorithm–Elman Neural Network

“…However, this method requires the radial displacement obtained by the displacement sensor to determine the rotor angular position. References [8][9][10] studied the high-frequency injection method (HFI), which involves superimposing a high-frequency voltage pulse on the motor's output voltage at specific time intervals. By calculating the voltage and current at the sampling time in a two-phase stationary coordinate system or a synchronous rotating coordinate system, the estimation rotor displacement and speed estimation can be achieved.…”

Sensorless Control of Bearingless Permanent Magnet Synchronous Motor Based on LS-SVM Inverse System

“…Generally, photoelectric encoders and Hall displacement sensors are applied to measure the speed and radial displacement of the rotor. However, these sensors increase the weight, volume, and cost of the whole system, and the detection results are easily affected by environmental factors and are not suitable for extreme environments [13][14][15][16]. Therefore, the research on the self-sensing technology of the speed and radial displacement of the BPMSM is expected to enhance the integrated level and reliability of the system, reduce the axial length of the motor, and provide more application fields for the BPMSM [17][18][19][20].…”

“…However, the neural network itself has some problems, such as slow convergence and being easy to fall into local optimal solutions. In [16], a BPMSM speed sensorless control method based on an improved high-frequency signal injection method with a finite impulse-response filter is proposed. In [17], a displacement self-sensing method of the bearingless induction motor using the mutual inductances affected by the displacement is proposed.…”

“…In [18], the displacement self-sensing of the BPMSM is realized by using the highfrequency signal injection method. References [16][17][18] use high-frequency signal injection methods, where signal processing circuits are inevitably added and the complexity of the control system is increased. In [19], four search coils of a bearingless induction motor are added and connected to a high-frequency voltage source.…”

Numerical Study on Frequency Limitation of Sensing Signal for Maglev Rotor Displacement

“…HF-injection-based approaches for the rotor position or speed estimation of a permanent magnet synchronous motor were also reported. (16)(17)(18) Sensorless methods for detecting AMB rotor displacement are based on the dynamics of the magnetic field and the inductive reactance of AMB coils. Since the variations of the magnetic field and the coil inductive reactance are both highly nonlinear, a simple numerical analysis procedure was introduced in this work for the preliminary analysis of a sensorless AMB.…”