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Performance Analysis of Speed-Sensorless Induction Motor Drive Using Discrete Current-Error Based MRAS Estimators

Author

Listed:
  • Teresa Orlowska-Kowalska

    (Department of Electrical Machines Drives and Measurements, Wroclaw University of Science and Technology, wyb. Wybrzeze Wyspianskiego 27, 50-370 Wroclaw, Poland)

  • Mateusz Korzonek

    (Independent Researcher, 44-360 Grabowka, Poland)

  • Grzegorz Tarchala

    (Department of Electrical Machines Drives and Measurements, Wroclaw University of Science and Technology, wyb. Wybrzeze Wyspianskiego 27, 50-370 Wroclaw, Poland)

Abstract

In the literature on sensorless control of induction motors, many algorithms have been presented for rotor flux and speed estimation. However, all these algorithms have been developed in the continuous–time domain. The digital realization of the control systems, requires the implementation of those estimation methods in a discrete–time domain. The main goal of this article is comparison of the impact of different numerical integration methods, used in analogue emulation under the digital implementation of the control systems, to the operation of classical Model Reference Adaptive System; CC-based on two current models (MRAS CC ) speed estimator and its three modified versions developed for the extension of the estimator stability region. In this paper the generalized mathematical model of MRAS CC estimator is proposed, which takes into account all known methods for the extension of the stability region of classical speed estimator of this type. After the short discussion of the discretization methods used for the microprocessor implementation of control algorithms the impact of different numerical integration methods on the stable operation range of the classical and modified MRAS CC estimators is analyzed and validated in simulation and experimental tests. It is proved that Modified Euler discretization method is much more accurate than forward and backward Euler methods and gives almost as accurate results as Tustin method, however is much less complicated in practical realization.

Suggested Citation

  • Teresa Orlowska-Kowalska & Mateusz Korzonek & Grzegorz Tarchala, 2020. "Performance Analysis of Speed-Sensorless Induction Motor Drive Using Discrete Current-Error Based MRAS Estimators," Energies, MDPI, vol. 13(10), pages 1-23, May.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:10:p:2595-:d:360536
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    Citations

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    Cited by:

    1. Ahmed G. Mahmoud A. Aziz & Almoataz Y. Abdelaziz & Ziad M. Ali & Ahmed A. Zaki Diab, 2023. "A Comprehensive Examination of Vector-Controlled Induction Motor Drive Techniques," Energies, MDPI, vol. 16(6), pages 1-32, March.
    2. Tuan Pham Van & Dung Vo Tien & Zbigniew Leonowicz & Michal Jasinski & Tomasz Sikorski & Prasun Chakrabarti, 2020. "Online Rotor and Stator Resistance Estimation Based on Artificial Neural Network Applied in Sensorless Induction Motor Drive," Energies, MDPI, vol. 13(18), pages 1-16, September.

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