IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i13p3420-d379567.html
   My bibliography  Save this article

A Simple Analytical Model of Static Eccentricity for PM Brushless Motors and Validation through FEM Analysis

Author

Listed:
  • Andrea Del Pizzo

    (Deptartment of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Napoli, Italy)

  • Luigi Pio Di Noia

    (Deptartment of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Napoli, Italy)

  • Emanuele Fedele

    (Deptartment of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Napoli, Italy)

Abstract

The paper firstly summarizes a simple analytical model of the air gap flux-density distribution for isotropic permanent magnet (PM) synchronous machines, in the presence of static eccentricity. The model was proposed by the authors in a previous paper and is based on an efficacious analytical expression of the variable length of air gap magnetic field lines which occur in eccentric brushless machines with surface-mounted permanent magnets. The approximate expression of the air gap field makes it possible to achieve a mathematical model with concentrated parameters close to that of a PM machine without eccentricity. The expression of the armature voltages and electromagnetic torque are found, also with reference to steady-state operating conditions at fixed rotor speed and impressed currents. The differences introduced by the considered type of eccentricity are evaluated and highlighted especially with reference to the air gap inductance and to waveforms and frequency spectra of voltages and shaft torque. Numerical results in a case-study of an 8-pole, 110 kW PM motor are compared to those obtained by using finite element analysis.

Suggested Citation

  • Andrea Del Pizzo & Luigi Pio Di Noia & Emanuele Fedele, 2020. "A Simple Analytical Model of Static Eccentricity for PM Brushless Motors and Validation through FEM Analysis," Energies, MDPI, vol. 13(13), pages 1-19, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:13:p:3420-:d:379567
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/13/3420/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/13/3420/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Karolina Kudelina & Bilal Asad & Toomas Vaimann & Anton Rassõlkin & Ants Kallaste & Huynh Van Khang, 2021. "Methods of Condition Monitoring and Fault Detection for Electrical Machines," Energies, MDPI, vol. 14(22), pages 1-20, November.
    2. Jin-Cheol Park & Soo-Hwan Park & Jae-Hyun Kim & Soo-Gyung Lee & Geun-Ho Lee & Myung-Seop Lim, 2021. "Diagnosis and Robust Design Optimization of SPMSM Considering Back EMF and Cogging Torque due to Static Eccentricity," Energies, MDPI, vol. 14(10), pages 1-19, May.

    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:gam:jeners:v:13:y:2020:i:13:p:3420-:d:379567. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.