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    Three-dimension core loss analysis of transverse flux linear motor based on the improved Steinmetz equation

    Access Status
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    Authors
    Ali, S.
    Hasanien, H.
    Muyeen, S.M.
    Date
    2018
    Type
    Conference Paper
    
    Metadata
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    Citation
    Ali, S. and Hasanien, H. and Muyeen, S. 2018. Three-dimension core loss analysis of transverse flux linear motor based on the improved Steinmetz equation,in Proceedings of the Autralasian Universities Power Engineering Conferenc (AUPEC), Nov 19-22 2017, pp. 1-6. Melbourne, VIC, Australia: IEEE.
    Source Title
    2017 Australasian Universities Power Engineering Conference, AUPEC 2017
    Source Conference
    Australasian Universities Power Engineering Conference (AUPEC)
    DOI
    10.1109/AUPEC.2017.8282472
    ISBN
    9781538626474
    School
    School of Electrical Engineering, Computing and Mathematical Science (EECMS)
    URI
    http://hdl.handle.net/20.500.11937/69558
    Collection
    • Curtin Research Publications
    Abstract

    This paper presents a novel three-dimension (3D) core loss analysis of the transverse flux linear motor (TFLM) with inner mover type based on the improved Steinmetz equation. For more accurate results, the magnetic flux waveforms of the motor are predicted by performing 3D finite element (FE) transient analysis. The stator phase winding is excited in the FE model and a good meshing is created in the model including a high density through the air gap. The winding is fed from a dc source via a single-phase full bridge inverter. The magnetic material is exposed to non-sinusoidal magnetic flux waveforms. The improved Steinmetz equation is applied to estimate the core losses. The Steinmetz parameters are determined by using the genetic algorithm (GA) technique. MATLAB GA optimization toolbox is used for this purpose. The transient analysis of the TFLM is performed using MagNet software. The total core losses are estimated in the 3D FE model. With this proposed improved Steinmetz equation, the core losses of the TFLM can be accurately estimated.

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