Induction motor stator faults identification using modified MRAS type estimator

• Autorzy: Majdański, Piotr , Dybkowski, Mateusz

Warianty tytułu

PL

Wykrywanie uszkodzeń stojana silnika indukcyjnego przy wykorzystaniu zmodyfikowanego estymatora typu MRAS

• Języki publikacji: EN

Abstrakty

EN

In the paper, the possibility of the MRAS (Model Reference Adaptive System) estimator application to estimate the stator resistance of an induction motor during stator short-circuits is presented. To increase the accuracy of the motor parameter reconstruction, a modified induction motor model was used, taking into account the possibility of simulating short circuits to develop a resistance estimator. The tests were performed in the DTC-SVM vector control system. The simulation results made in Matlab Simulink environment are presented under different drive conditions.

PL

W artykule przedstawiono możliwość wykorzystania estymatora typu MRAS (Model Reference Adaptive System) do estymacji rezystancji stojana silnika indukcyjnego podczas zwarć zwojowych. W celu zwiększenia dokładności odtwarzania parametru silnika estymator opracowano w oparciu o zmodyfikowany model maszyny, uwzględniający możliwość symulowania zwarć. Badania wykonano w układzie sterowania wektorowego DTC-SVM. Przedstawiono wyniki symulacyjne wykonane w środowisku Matlab Simulink.

Słowa kluczowe

PL

MRAS; estymacja rezystancji stojana; uszkodzenie stojana; DTC

EN

MRAS; stator resistance estimation; stator faults; DTC

• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2023
• Tom: R. 99, nr 5
• Strony: 214--219
• Opis fizyczny: Bibliogr. 16 poz., rys., tab.

Twórcy

autor

Majdański, Piotr

• Wroclaw University of Science and Technology, Department of Electrical Machines, Drives and Measurements, ul. Wybrzeze Wyspianskiego 27, 50-370 Wrocław,

autor

Dybkowski, Mateusz

• Wroclaw University of Science and Technology, Department of Electrical Machines, Drives and Measurements, ul. Wybrzeze Wyspianskiego 27, 50-370 Wrocław,

Bibliografia

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• [4] P. Zhang, Y. Du, T. G. Habetler, and B. Lu, “A Survey of Condition Monitoring and Protection Methods for Medium Voltage Induction Motors,” IEEE Transactions on Industry Applications, vol. 47, no. 1, pp. 34–46, Jan. 2011, doi: 10.1109/TIA.2010.2090839.
• [5] V. Vasic, S. N. Vukosavic, and E. Levi, “A stator resistance estimation scheme for speed sensorless rotor flux oriented induction motor drives,” IEEE Transactions on Energy Conversion, vol. 18, no. 4, pp. 476–483, Dec. 2003, doi: 10.1109/TEC.2003.816595.
• [6] M. H. Holakooie, M. Ojaghi, and A. Taheri, “Direct Torque Control of Six-Phase Induction Motor With a Novel MRAS-Based Stator Resistance Estimator,” IEEE Transactions on Industrial Electronics, vol. 65, no. 10, pp. 7685–7696, Oct. 2018, doi: 10.1109/TIE.2018.2807410.
• [7] S. M. N. Hasan and I. Husain, “A Luenberger–Sliding Mode Observer for Online Parameter Estimation and Adaptation in High-Performance Induction Motor Drives,” IEEE Transactions on Industry Applications, vol. 45, no. 2, pp. 772–781, Mar. 2009, doi: 10.1109/TIA.2009.2013602.
• [8] M. Jouili, Y. Agrebi, Y. Koubaa, and M. Boussak, “A Luenberger state observer for simultaneous estimation of speed and stator resistance in sensorless IRFOC induction motor drives,” in 2015 16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA), Dec. 2015, pp. 898–904. doi: 10.1109/STA.2015.7505225.
• [9] M. A. Usta, H. I. Okumus, and H. Kahveci, “A simplified three level SVM-DTC induction motor drive with speed and stator resistance estimation based on extended Kalman filter,” Electr Eng, vol. 99, no. 2, pp. 707–720, Jun. 2017, doi: 10.1007/s00202-016-0442-x.
• [10] Yildiz, M. Barut, E. Zerdali, R. Inan, and R. Demir, “Loadtorque and stator resistance estimations with unscented Kalman filter for speed-sensorless control of induction motors,” in 2017 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM) & 2017 Intl Aegean Conference on Electrical Machines and Power Electronics (ACEMP), May 2017, pp. 456–461. doi: 10.1109/OPTIM.2017.7975011.
• [11] B. Karanayil, M. F. Rahman, and C. Grantham, “Online Stator and Rotor Resistance Estimation Scheme Using Artificial Neural Networks for Vector Controlled Speed Sensorless Induction Motor Drive,” IEEE Transactions on Industrial Electronics, vol. 54, no. 1, pp. 167–176, Feb. 2007, doi: 10.1109/TIE.2006.888778.
• [12] T. Pham Van, D. Vo Tien, Z. Leonowicz, M. Jasinski, T. Sikorski, and P. Chakrabarti, “Online Rotor and Stator Resistance Estimation Based on Artificial Neural Network Applied in Sensorless Induction Motor Drive,” Energies, vol. 13, no. 18, Art. no. 18, Jan. 2020, doi: 10.3390/en13184946.
• [13] K. Klimkowski, M. Dybkowski, and S. A. Bednarz, “Influence of stator and rotor resistances changes to the properties of the Fault Tolerant Vector Control of induction motor drive,” in 2017 International Symposium on Electrical Machines (SME), Jun. 2017, pp. 1–5. doi: 10.1109/ISEM.2017.7993540.
• [14] C. H. D. Angelo, G. R. Bossio, S. J. Giaccone, M. I. Valla, J. A. Solsona, and G. O. Garcia, “Online Model-Based Stator-Fault Detection and Identification in Induction Motors,” IEEE Transactions on Industrial Electronics, vol. 56, no. 11, pp. 4671–4680, Nov. 2009, doi: 10.1109/TIE.2009.2012468.
• [15] C. Lascu, I. Boldea, and F. Blaabjerg, “A modified direct torque control for induction motor sensorless drive,” IEEE Transactions on Industry Applications, vol. 36, no. 1, pp. 122–130, Jan. 2000, doi: 10.1109/28.821806.
• [16] M. Dybkowski and S. A. Bednarz, “Modified Rotor Flux Estimators for Stator-Fault-Tolerant Vector Controlled Induction Motor Drives,” Energies, vol. 12, no. 17, Art. no. 17, Jan. 2019, doi: 10.3390/en12173232

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).

Identyfikatory

DOI

10.15199/48.2023.05.37