Loughborough University
Browse

Analytical multiphysics model for NVH prediction of a high-speed Surface-Permanent Magnet Synchronous Machine

Download (496.48 kB)
conference contribution
posted on 2024-01-30, 16:02 authored by Panagiotis Andreou, Amal Hajjej Ep Zemni, Mahdi Mohammad-PourMahdi Mohammad-Pour, Stephanos TheodossiadesStephanos Theodossiades

As demands for electric motor efficiency keep increasing, Electric Vehicle (EV) manufacturers are striving to design smaller and more power-dense machines, able to maintain performance standards through high-speed operation. However, increased operating loads and speeds in excess of 10,000 rev/min results in the amplification, or introduction of new noise components, which necessitate novel prediction techniques. The use of traditional finite element (FE) based optimisation methodologies therefore becomes challenging due to extensive computational loads. In this work, an analytical multi-physics methodology for e-NVH prediction of typical high-speed Surface-mounted Permanent Magnet Synchronous Machines (S-PMSMs) is presented. The model comprises analytical electromagnetics and vibro-acoustics to determine the radiated airborne noise of SPMSMs at speeds above 10,000 rev/min and correspondingly high frequencies. Preliminary results are presented to highlight the efficiency of the proposed method.

Funding

DTP 2020-2021 Loughborough University

Engineering and Physical Sciences Research Council

Find out more...

Automotive electric powertrain whistling and whining: fundamental root cause analysis to novel solutions

Engineering and Physical Sciences Research Council

Find out more...

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Proceedings of the Spanish Congress of Acoustics

Source

53rd Spanish Congress of Acoustics 2022

Publisher

SEA Acustica

Version

  • VoR (Version of Record)

Publication date

2022-12-12

Language

  • en

Location

Alicante, Spain

Event dates

2nd November 2022 - 4th November 2022

Depositor

Panagiotis Andreou. Deposit date: 29 January 2024

Usage metrics

    Loughborough Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC