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OPTIMIZATION OF INTERIOR PERMANENT MAGNET SYNCHRONOUS MOTOR USING EVOLUTIONARY OPTIMIZATION ALGORITHM

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU132026" target="_blank" >RIV/00216305:26220/19:PU132026 - isvavai.cz</a>

  • Result on the web

    <a href="http://www.feec.vutbr.cz/conf/EEICT/archiv/sborniky/EEICT_2019_sbornik.pdf" target="_blank" >http://www.feec.vutbr.cz/conf/EEICT/archiv/sborniky/EEICT_2019_sbornik.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    OPTIMIZATION OF INTERIOR PERMANENT MAGNET SYNCHRONOUS MOTOR USING EVOLUTIONARY OPTIMIZATION ALGORITHM

  • Original language description

    The development of the interior permanent magnet synchronous motor has drawn a big interest over the last decade. This is due to the use of this kind of machine in the automotive industry, thanks to the machine high efficiency and high overload capability compare to other machine types. Using artificial intelligence or evolutionary optimization algorithms is possible to optimize the motor with maximum efficiency, lowest torque ripple and highest average torque, because a huge ammount and variety of geometry combinations are tested. This paper is focused on the overview of generally used optimization algorithms and optimization is demonstrated on Self-Organizing Migrating Algorithm (SOMA). Cost function and weight coefficients are also presented and used for optimization.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20201 - Electrical and electronic engineering

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2019

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 25th Conference STUDENT EEICT 2019

  • ISBN

    978-80-214-5735-5

  • ISSN

  • e-ISSN

  • Number of pages

    768

  • Pages from-to

    664-668

  • Publisher name

    Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií

  • Place of publication

    Brno

  • Event location

    Brno

  • Event date

    Apr 25, 2019

  • Type of event by nationality

    CST - Celostátní akce

  • UT code for WoS article