Detail publikace

OPTIMIZATION OF INTERIOR PERMANENT MAGNET SYNCHRONOUS MOTOR USING EVOLUTIONARY OPTIMIZATION ALGORITHM

Knebl L.

Originální název

OPTIMIZATION OF INTERIOR PERMANENT MAGNET SYNCHRONOUS MOTOR USING EVOLUTIONARY OPTIMIZATION ALGORITHM

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

Maxwell, SOMA, Optimization, evolutionary optimization algorithm, Finite element analysis, Interior permanent magnet

Autoři

Knebl L.

Vydáno

25. 4. 2019

Nakladatel

Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií

Místo

Brno

ISBN

978-80-214-5735-5

Kniha

Proceedings of the 25th Conference STUDENT EEICT 2019

Číslo edice

První

Strany od

664

Strany do

668

Strany počet

768

URL

http://www.feec.vutbr.cz/conf/EEICT/archiv/sborniky/EEICT_2019_sbornik.pdf

BibTex

@inproceedings{BUT156810,
  author="Ladislav {Knebl}",
  title="OPTIMIZATION OF INTERIOR PERMANENT MAGNET SYNCHRONOUS MOTOR USING EVOLUTIONARY OPTIMIZATION ALGORITHM",
  booktitle="Proceedings of the 25th Conference STUDENT EEICT 2019",
  year="2019",
  number="První",
  pages="664--668",
  publisher="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií",
  address="Brno",
  isbn="978-80-214-5735-5",
  url="http://www.feec.vutbr.cz/conf/EEICT/archiv/sborniky/EEICT_2019_sbornik.pdf"
}