International Journal of Energy and Power Engineering

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Speed Estimation of Three Phase Induction Motor Using Artificial Neural Network

Received: 26 January 2014    Accepted:     Published: 20 March 2014
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Abstract

Three phase induction motors being the most widely used motor for domestic, commercial and industrial applications, demands a more detailed understanding and improved analysis of its performance characteristics. The conventional method of using the equivalent circuit for assessing the motor performance cannot incorporate the non-linearities involved in the speed torque characteristics into the performance of the motor to the fullest extent. This paper presents an ANN based modeling of three phase induction motor to overcome this problem. The model has been tested and validated with actual experimental data. The performance of the model has been compared with that of a classical equivalent circuit technique both graphically and statistically and found to be superior. The model can thus offer a better method of speed estimation and control of the induction motor for input voltage variation with and without input frequency change.

DOI 10.11648/j.ijepe.20140302.13
Published in International Journal of Energy and Power Engineering (Volume 3, Issue 2, April 2014)
Page(s) 52-56
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Artificial Neural Networks, Three Phase Induction Motor

References
[1] Vasic, Veran, Slobodan N. Vukosavic and Emil Levi., "A stator resistance estimation scheme for speed sensorless rotor flux oriented induction motor drives", IEEE transactions on Energy Conversion, on 18, no. 4 pp. 476-483, (2003).
[2] Kohlsnez G. & Fodor D., "Comparison of scalar and vector control strategies of Induction Motor", Hungarian J. Industrial Chemistry, Veszprem, vol. 9 (2) pp. 265-270 (2011).
[3] Baradwaj, Raj Mohan, Alexander G. Parlos and Hamid A. Toliyat, "Adaptive neural network-based state filter for induction motor speed estimation." In Industrial Electronics Society, 1999. IECON’99 Proceedings. The 25th Annual Conference of the IEEE, vol. 3, pp. 1283-1288. IEEE, 1999.
[4] Geetha, E. K., T. Thyagarajan, and Vedam Subramanyam, "Robust speed sensorless induction motor drives." In Power Electronics, 2007, ICPE’07, 7th International Conference on Power Electronics, pp. 806-810. IEEE, 2007.
[5] O. Yuksel, D. Mehmet, "Speed estimation of vector controlled squirrel cage asynchronous motor with artificial neural network." Elsevier Energy Conversion and Management, vol. 52, pp. 675-686, 2009.
[6] dos Santos, T. H., A. Goedtel, S.A. O. da Silva, and M. Suetake, "A neural speed estimator in Three-Phase Induction Motors powered by a driver with scalar control." In Power Electronics Conference (COBEP), 2011 Brazilian, pp. 44-49. IEEE, 2011.
[7] S.J. Chapman, Electric Machines Fundamentals, McGrow-Hill (1998) pp. 430-436.
[8] Neural Network Toolbox TM User Guide, www.mathworks.in/help/pdf_doc/nnet/nnet_ug.pdf
[9] B.S. Grewal, Higher Engineering Mathematics, Khanna Publishers, 40th Edition.
[10] Digital Signal Processing Solution for AC Induction Motor, Application Note BPRA043 Texas Instruments.
Author Information
  • Department of Electrical Engineering, M.C.E.T., West Bengal University of Technology, Kolkata, India

  • Department of Electrical Engineering, M.C.E.T., West Bengal University of Technology, Kolkata, India

  • BIEMS, West Bengal University of Technology, Kolkata, India

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  • APA Style

    Moinak Pyne, Abhishek Chatterjee, Sibamay Dasgupta. (2014). Speed Estimation of Three Phase Induction Motor Using Artificial Neural Network. International Journal of Energy and Power Engineering, 3(2), 52-56. https://doi.org/10.11648/j.ijepe.20140302.13

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    ACS Style

    Moinak Pyne; Abhishek Chatterjee; Sibamay Dasgupta. Speed Estimation of Three Phase Induction Motor Using Artificial Neural Network. Int. J. Energy Power Eng. 2014, 3(2), 52-56. doi: 10.11648/j.ijepe.20140302.13

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    AMA Style

    Moinak Pyne, Abhishek Chatterjee, Sibamay Dasgupta. Speed Estimation of Three Phase Induction Motor Using Artificial Neural Network. Int J Energy Power Eng. 2014;3(2):52-56. doi: 10.11648/j.ijepe.20140302.13

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  • @article{10.11648/j.ijepe.20140302.13,
      author = {Moinak Pyne and Abhishek Chatterjee and Sibamay Dasgupta},
      title = {Speed Estimation of Three Phase Induction Motor Using Artificial Neural Network},
      journal = {International Journal of Energy and Power Engineering},
      volume = {3},
      number = {2},
      pages = {52-56},
      doi = {10.11648/j.ijepe.20140302.13},
      url = {https://doi.org/10.11648/j.ijepe.20140302.13},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijepe.20140302.13},
      abstract = {Three phase induction motors being the most widely used motor for domestic, commercial and industrial applications, demands a more detailed understanding and improved analysis of its performance characteristics. The conventional method of using the equivalent circuit for assessing the motor performance cannot incorporate the non-linearities involved in the speed torque characteristics into the performance of the motor to the fullest extent. This paper presents an ANN based modeling of three phase induction motor to overcome this problem. The model has been tested and validated with actual experimental data. The performance of the model has been compared with that of a classical equivalent circuit technique both graphically and statistically and found to be superior. The model can thus offer a better method of speed estimation and control of the induction motor for input voltage variation with and without input frequency change.},
     year = {2014}
    }
    

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  • TY  - JOUR
    T1  - Speed Estimation of Three Phase Induction Motor Using Artificial Neural Network
    AU  - Moinak Pyne
    AU  - Abhishek Chatterjee
    AU  - Sibamay Dasgupta
    Y1  - 2014/03/20
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    N1  - https://doi.org/10.11648/j.ijepe.20140302.13
    DO  - 10.11648/j.ijepe.20140302.13
    T2  - International Journal of Energy and Power Engineering
    JF  - International Journal of Energy and Power Engineering
    JO  - International Journal of Energy and Power Engineering
    SP  - 52
    EP  - 56
    PB  - Science Publishing Group
    SN  - 2326-960X
    UR  - https://doi.org/10.11648/j.ijepe.20140302.13
    AB  - Three phase induction motors being the most widely used motor for domestic, commercial and industrial applications, demands a more detailed understanding and improved analysis of its performance characteristics. The conventional method of using the equivalent circuit for assessing the motor performance cannot incorporate the non-linearities involved in the speed torque characteristics into the performance of the motor to the fullest extent. This paper presents an ANN based modeling of three phase induction motor to overcome this problem. The model has been tested and validated with actual experimental data. The performance of the model has been compared with that of a classical equivalent circuit technique both graphically and statistically and found to be superior. The model can thus offer a better method of speed estimation and control of the induction motor for input voltage variation with and without input frequency change.
    VL  - 3
    IS  - 2
    ER  - 

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