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A 3D Dynamic Lumped Parameter Thermal Network of Air-Cooled YASA Axial Flux Permanent Magnet Synchronous Machine

Author

Listed:
  • Abdalla Hussein Mohamed

    (Department of Electrical Machines, Metals, Mechanical Constructions and Systems, Ghent University, 9052 Ghent, Belgium
    EEDT, Flanders Make, the Research Centre for the Manufacturing Industry, B-8500 Kortrijk, Belgium
    Department of Electrical Power and Machines, Cairo University, Giza 12613, Egypt)

  • Ahmed Hemeida

    (Department of Electrical Power and Machines, Cairo University, Giza 12613, Egypt
    Aalto University, Department of Electrical Engineering and Automation, P.O. Box 13000, FI-00076 Espoo, Finland)

  • Alireza Rasekh

    (Department of Flow, Heat and Combustion Mechanics, Faculty of Engineering and Architecture, Ghent University, B-9000 Ghent, Belgium)

  • Hendrik Vansompel

    (Department of Electrical Machines, Metals, Mechanical Constructions and Systems, Ghent University, 9052 Ghent, Belgium
    EEDT, Flanders Make, the Research Centre for the Manufacturing Industry, B-8500 Kortrijk, Belgium)

  • Antero Arkkio

    (Aalto University, Department of Electrical Engineering and Automation, P.O. Box 13000, FI-00076 Espoo, Finland)

  • Peter Sergeant

    (Department of Electrical Machines, Metals, Mechanical Constructions and Systems, Ghent University, 9052 Ghent, Belgium
    EEDT, Flanders Make, the Research Centre for the Manufacturing Industry, B-8500 Kortrijk, Belgium)

Abstract

To find the temperature rise for high power density yokeless and segmented armature (YASA) axial flux permanent magnet synchronous (AFPMSM) machines quickly and accurately, a 3D lumped parameter thermal model is developed and validated experimentally and by finite element (FE) simulations on a 4 kW YASA machine. Additionally, to get insight in the thermal transient response of the machine, the model accounts for the thermal capacitance of different machine components. The model considers the stator, bearing, and windage losses, as well as eddy current losses in the magnets on the rotors. The new contribution of this work is that the thermal model takes cooling via air channels between the magnets on the rotor discs into account. The model is parametrized with respect to the permanent magnet (PM) angle ratio, the PM thickness ratio, the air gap length, and the rotor speed. The effect of the channels is incorporated via convection equations based on many computational fluid dynamics (CFD) computations. The model accuracy is validated at different values of parameters by FE simulations in both transient and steady state. The model takes less than 1 s to solve for the temperature distribution.

Suggested Citation

  • Abdalla Hussein Mohamed & Ahmed Hemeida & Alireza Rasekh & Hendrik Vansompel & Antero Arkkio & Peter Sergeant, 2018. "A 3D Dynamic Lumped Parameter Thermal Network of Air-Cooled YASA Axial Flux Permanent Magnet Synchronous Machine," Energies, MDPI, vol. 11(4), pages 1-16, March.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:4:p:774-:d:138534
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    References listed on IDEAS

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    1. Alireza Rasekh & Peter Sergeant & Jan Vierendeels, 2016. "Development of Correlations for Windage Power Losses Modeling in an Axial Flux Permanent Magnet Synchronous Machine with Geometrical Features of the Magnets," Energies, MDPI, vol. 9(12), pages 1-17, November.
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    Cited by:

    1. Federica Graffeo & Silvio Vaschetto & Alessio Miotto & Fabio Carbone & Alberto Tenconi & Andrea Cavagnino, 2021. "Lumped-Parameters Thermal Network of PM Synchronous Machines for Automotive Brake-by-Wire Systems," Energies, MDPI, vol. 14(18), pages 1-18, September.
    2. Guangchen Wang & Yingjie Wang & Yuan Gao & Wei Hua & Qinan Ni & Hengliang Zhang, 2022. "Thermal Model Approach to the YASA Machine for In-Wheel Traction Applications," Energies, MDPI, vol. 15(15), pages 1-18, July.
    3. Abdalla Hussein Mohamed & Ahmed Hemeida & Hendrik Vansompel & Peter Sergeant, 2018. "Parametric Studies for Combined Convective and Conductive Heat Transfer for YASA Axial Flux Permanent Magnet Synchronous Machines," Energies, MDPI, vol. 11(11), pages 1-18, November.
    4. Bin Li & Liang Yan & Wenping Cao, 2020. "An Improved LPTN Method for Determining the Maximum Winding Temperature of a U-Core Motor," Energies, MDPI, vol. 13(7), pages 1-18, March.

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