<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></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.

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

Laboratory of Sciences and Techniques of Automatic Control & Computer Engineering (Lab-STA)

Laboratoire des Sciences de l’Information et des Systèmes (LSIS)

Power Electronics and Drives

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

A sensorless indirect stator-flux-oriented control (ISFOC) induction motor drive at very low frequencies is presented herein. The model reference adaptive...

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

Online veröffentlicht: 26. Nov. 2019

Seitenbereich: 125 - 140

Eingereicht: 02. Sept. 2018

Akzeptiert: 08. Okt. 2018

DOI: https://doi.org/10.2478/pead-2018-0021

Schlüsselwörter
Induction motor, Stator flux orientation model, Model reference adaptive system (MRAS), Rotor speed and resistance estimation, Programmable cascaded low-pass filters (PCLPF)

© 2019 Youssef Agrebi Zorgani et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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

Online veröffentlicht: 26. Nov. 2019

Seitenbereich: 125 - 140

Eingereicht: 02. Sept. 2018

Akzeptiert: 08. Okt. 2018

DOI: https://doi.org/10.2478/pead-2018-0021

SchlüsselwörterInduction motor, Stator flux orientation model, Model reference adaptive system (MRAS), Rotor speed and resistance estimation, Programmable cascaded low-pass filters (PCLPF)

© 2019 Youssef Agrebi Zorgani et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Induction motor, Stator flux orientation model, Model reference adaptive system (MRAS), Rotor speed and resistance estimation, Programmable cascaded low-pass filters (PCLPF)