An Implementation of a Programmable Cascaded Low-Pass Filter for a Rotor Flux Synthesizer for an Induction Motor Drive

2004 ◽  
Vol 19 (2) ◽  
pp. 257-263 ◽  
Author(s):  
B. Karanayil ◽  
M.F. Rahman ◽  
C. Grantham
Keyword(s):  
Induction Motor ◽  
Motor Drive ◽  
Induction Motor Drive ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass ◽  
Rotor Flux

A Rotor Flux Observer Based on Nonlinear Quadrature Double Compensation

2011 ◽  
Vol 128-129 ◽  
pp. 25-29
Author(s):  
Bo Fan ◽  
Xing Li ◽  
Jie Xin Pu ◽  
Jian Wei Ma ◽  
Ju Wei Zhang
Keyword(s):  
Induction Motor ◽  
Electromotive Force ◽  
Signal Frequency ◽  
Quick Response ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Flux Observer ◽  
Low Pass ◽  
Rotor Flux ◽  
Order Change

In order to solve the problem of integration saturation drift and hardship in compensation quantity calculation exist in rotor flux observation of induction motor, a rotor flux observer based on nonlinear quadrature double compensation method is presented in this paper. The quantity of compensation is determined dynamically according to the quadrature level between flux and back electromotive force. Through the order change of compensation and low-pass filter, quick response of flux when signal frequency leaps is realized. The simulation result shows that the method can improve the flux waveform, realize the accurate and swift track of flux.

scholarly journals A Very-Low-Speed Sensorless Control Induction Motor Drive with Online Rotor Resistance Tuning by Using MRAS Scheme

2019 ◽  
Vol 4 (1) ◽  
pp. 125-140 ◽  
Author(s):  
Youssef Agrebi Zorgani ◽  
Mabrouk Jouili ◽  
Yassine Koubaa ◽  
Mohamed Boussak
Keyword(s):  
Induction Motor ◽  
Reference Frame ◽  
Motor Drive ◽  
Induction Motor Drive ◽  
Adaptation Mechanism ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Speed ◽  
Rotor Resistance ◽  
Stator Flux

Abstract A sensorless indirect stator-flux-oriented control (ISFOC) induction motor drive at very low frequencies is presented herein. The model reference adaptive system (MRAS) scheme is used to estimate the speed and the rotor resistance simultaneously. However, the error between the reference and the adjustable models, which are developed in the stationary stator reference frame, is used to drive a suitable adaptation mechanism that generates the estimates of speed and the rotor resistance from the stator voltage and the machine current measurements. The stator flux components in the stationary reference frame are estimated through a pure integration of the back electro-motive force (EMF) of the machine. When the machine is operated at low speed, the pure integration of the back EMF introduces an error in flux estimation which affects the performance torque and speed control. To overcome this problem, pure integration is replaced with a programmable cascaded low-pass filter (PCLPF). The stability analysis method of the MRAS estimator is verified in order to show the robustness of the rotor resistance variations. Experimental results are presented to prove the effectiveness and validity of the proposed scheme of sensorless ISFOC induction motor drive.

scholarly journals Klasterisasi Kerusakan Bearing Motor Induksi 3 Fasa Menggunakan Metode Transformasi Wavelet Diskrit dan K-Medoids

ELKHA ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 54
Author(s):  
Eska Rizqi Naufal ◽  
Gigih Priyandoko ◽  
Fachrudin Hunaini
Keyword(s):  
Induction Motor ◽  
Extraction Method ◽  
Data Extraction ◽  
Working Environment ◽  
Discrete Wavelet ◽  
Clustering Method ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Group Data ◽  
Low Pass

The 3 phase induction motor is a reliable and strong motor also has cheap price. However induction motor are also vulnerable, from the result of survey conducted by Electric Power Research Institute (EPRI), there are 41% cases of damage occur in the bearing caused by working environment condition, bearing age, and several other factors. Bearing fault is not easily to identified, with applying the data extraction method using the Discrete Wavelet Transform (DWT) and the K-Medoids clustering method will facilitate the identification process. The extraction method will pass the data in the form of current signals into the digital filter (Low Pass Filter and High Pass Filter) to be mapped into the region of frequency and time simultaneously, and clustering method will group data based on certain characteristics. Based on the clustering tests that have been done on the 3 phase induction motor current signal data with 3 bearing conditions, the Discrete Wavelet Transformation with mother wavelet bior1.1 decomposition level 2 and K-Medoids produce an accuracy rate of 86.8%.

Improved Stator Flux Estimation for Direct Torque Control of Induction Motor Drives

2016 ◽  
Vol 7 (4) ◽  
pp. 1049
Author(s):  
Yahya Ahmed Alamri ◽  
Nik Rumzi Nik Idris ◽  
Ibrahim Mohd. Alsofyani ◽  
Tole Sutikno
Keyword(s):  
Induction Motor ◽  
Cutoff Frequency ◽  
Direct Torque Control ◽  
Motor Drives ◽  
Torque Control ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass ◽  
Flux Estimation ◽  
Stator Flux

<p>Stator flux estimation using voltage model is basically the integration of the induced stator back electromotive force (emf) signal. In practical implementation the pure integration is replaced by a low pass filter to avoid the DC drift and saturation problems at the integrator output because of the initial condition error and the inevitable DC components in the back emf signal. However, the low pass filter introduces errors in the estimated stator flux which are significant at frequencies near or lower than the cutoff frequency. Also the DC components in the back emf signal are amplified at the low pass filter output by a factor equals to . Therefore, different integration algorithms have been proposed to improve the stator flux estimation at steady state and transient conditions. In this paper a new algorithm for stator flux estimation is proposed for direct torque control (DTC) of induction motor drives. The proposed algorithm is composed of a second order high pass filter and an integrator which can effectively eliminates the effect of the error initial condition and the DC components. The amplitude and phase errors compensation algorithm is selected such that the steady state frequency response amplitude and phase angle are equivalent to that of the pure integrator and the multiplication and division by stator frequency are avoided. Also the cutoff frequency selection is improved; even small value can filter out the DC components in the back emf signal. The simulation results show the improved performance of the induction motor direct torque control drive with the proposed stator flux estimation algorithm. The simulation results are verified by the experimental results.</p>

scholarly journals Deadbeat-Based Model Predictive Voltage Control for a Sensorless Five-Phase Induction Motor Drive

2020 ◽  
Vol 2020 ◽  
pp. 1-30
Author(s):  
Mahmoud A. Mossa ◽  
Nguyen Vu Quynh ◽  
Hamdi Echeikh ◽  
Ton Duc Do
Keyword(s):  
Induction Motor ◽  
Direct Torque Control ◽  
Voltage Control ◽  
Torque Control ◽  
Computational Time ◽  
Motor Drive ◽  
Induction Motor Drive ◽  
Wide Range ◽  
Direct Model ◽  
Rotor Flux

This paper introduces a direct model predictive voltage control (DMP VC) for a sensorless five-phase induction motor drive. The operation of the proposed sensorless DMP VC is based on the direct control of the applied stator voltages instead of controlling the torque and flux as in model predictive direct torque control (MP DTC). Thus, the simplicity of the control system is enhanced, which saves the computational time and reduces the commutation losses as well. The methodology based on which the proposed sensorless DMP VC performs its operation depends on minimizing a cost function that calculates the error between the reference and actual values of the direct and quadrature (d-q) axes components of stator voltages. The reference values of d-q components of stator voltages are obtained through incorporating the deadbeat control within the proposed model predictive system. A robust back-stepping observer is proposed for estimating the speed, stator currents, rotor flux, and rotor resistance. The validity of the proposed sensorless DMP VC is confirmed through performing detailed and extensive comparisons between the proposed DMP VC and MP DTC approach. The obtained results state that the drive is exhibiting better performance under the proposed DMP VC with less ripples content and reduced computational burden. Moreover, the proposed back-stepping observer has confirmed its effectiveness in estimating the speed and other variables for a wide range of speed operation.

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