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Reduction of Unbalance Magnetic Force and Torque Ripple in a Special Permanent Magnet Synchronous Machine by Several Multi-Objective Meta-Heuristic Algorithms

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27730%2F25%3A10259289" target="_blank" >RIV/61989100:27730/25:10259289 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/11244158" target="_blank" >https://ieeexplore.ieee.org/document/11244158</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/OJIES.2025.3632189" target="_blank" >10.1109/OJIES.2025.3632189</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Reduction of Unbalance Magnetic Force and Torque Ripple in a Special Permanent Magnet Synchronous Machine by Several Multi-Objective Meta-Heuristic Algorithms

  • Original language description

    Reducing the unbalanced magnetic forces (UMFs) and torque ripple (TR) simultaneously is one of the most vital goals of electrical machines designed for a variety of applications, such as hybrid vehicles. Removing TR is causing vibration free performance as well as UMFs decreasing will increase the life of machine components. Although several quantities impact the mentioned indicators, the first one is type of magnetization. Hence, two conventional magnetization patterns including radial and 9-segment magnetization patterns are thought through. Furthermore, pole arc to pole pitch ratio is extremely influential. Therefore, two functions based on it are determined for UMF and TR. Several magnetization patterns are considered to provide suitable response. They are optimized by multiobjective meta-heuristic optimization algorithms. Three algorithms including Pareto envelope-based selection algorithm II, nondominate sorting genetic algorithm II, and multiobjective particle swarm optimization have been utilized because their performances depend on not only initial guess but also type of problem. Then, the optimization results have been compared. Next, the best machine&apos;s dimensions are selected. After that, cogging, reluctance and instantaneous torque, overload capability curve and torque-speed characteristic have been computed. Finally, the temperature impact on either UMF&apos;s and torque&apos;s average or mentioned indicators is analyzed. It should be noted that the function fitting and optimization process have been done using MATLAB software.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20200 - Electrical engineering, Electronic engineering, Information engineering

Result continuities

  • Project

  • Continuities

    O - Projekt operacniho programu

Others

  • Publication year

    2025

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    IEEE Open Journal of the Industrial Electronics Society

  • ISSN

    2644-1284

  • e-ISSN

    2644-1284

  • Volume of the periodical

    6

  • Issue of the periodical within the volume

    1-10

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    10

  • Pages from-to

    1821-1830

  • UT code for WoS article

    001631855400001

  • EID of the result in the Scopus database