IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v71y2006i4p290-298.html
   My bibliography  Save this article

Neural network flux optimization using a model of losses in induction motor drives

Author

Listed:
  • Pryymak, Bogdan
  • Moreno-Eguilaz, Juan M.
  • Peracaula, Juan

Abstract

This paper focuses on loss minimization in induction motor (IM) drives. In many applications Induction Motor drives work below the nominal torque most of the time. In these circumstances the IM efficiency can be improved lowering the flux. For a given torque, this decreases iron looses and increases copper losses. With appropriate algorithms an optimum point for the flux can be achieved in order to minimize IM total power losses. Using an IM model, a neural network (NN) based approach is used to improve efficiency in a vector control of the induction motor drive. A complex loss model of the motor, including magnetic and thermal deviations of its parameters, is used to estimate losses. Based on this model, the neural network is trained to estimate the optimum rotor flux. Inputs to the NN are torque, speed and rotor resistance of the IM and the output is the rotor flux. Analysis, modeling and simulation results are presented to demonstrate the validity of the proposed method.

Suggested Citation

  • Pryymak, Bogdan & Moreno-Eguilaz, Juan M. & Peracaula, Juan, 2006. "Neural network flux optimization using a model of losses in induction motor drives," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 71(4), pages 290-298.
    • Handle: RePEc:eee:matcom:v:71:y:2006:i:4:p:290-298
    DOI: 10.1016/j.matcom.2006.02.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475406000486
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.matcom.2006.02.015?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pozna, Claudiu & Troester, Fritz & Precup, Radu-Emil & Tar, József K. & Preitl, Stefan, 2009. "On the design of an obstacle avoiding trajectory: Method and simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(7), pages 2211-2226.
    2. Sediki, Hamid & Bechouche, Ali & Abdeslam, Djaffar Ould & Haddad, Salah, 2013. "ADALINE approach for induction motor mechanical parameters identification," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 90(C), pages 86-97.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:matcom:v:71:y:2006:i:4:p:290-298. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/mathematics-and-computers-in-simulation/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.