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Fully predictive heat transfer coefficient modeling of an axial flux permanent magnet synchronous machine with geometrical parameters of the magnets

Alireza Rasekh (UGent) , Peter Sergeant (UGent) and Jan Vierendeels (UGent)
(2017) APPLIED THERMAL ENGINEERING. 110. p.1343-1357
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Abstract
This paper describes new correlations for the convective heat transfer assessment in an axial flux permanent magnet synchronous machine. The case-study here is composed of an open rotor-stator with sixteen magnets at the periphery of the rotor with an annular opening in the entire disk. Air can flow in a channel being formed between the magnets and in a small gap region between the magnets and the stator surface. The idea is to use the space in between adjacent rotor magnets as cooling air-channels. The rotor disk with the magnets then behaves as a centrifugal fan causing efficient air gap cooling. In order to construct the correlations, CFD simulations are performed at the practical ranges of important non-dimensional parameters including the gap size ratio, the rotational Reynolds number, the magnet angle ratio and the magnet thickness ratio. Considering the geometric periodicity of the computational domain, only one magnet on the rotor disk is investigated. Moreover, the Frozen Rotor method is used to simulate the rotary motion of the rotor together with the fluid around it. Unlike most precedent studies that considered ambient temperature as the reference temperature, therefore making the estimated convective heat coefficient dependent on the surface temperature, a different approach has been taken into account here. The reference temperature is computed through a minimization method in such a way that the mean Nusselt number becomes rather independent of the surface temperatures. It is found that the proposed correlations can strongly predict the heat transfer rates for all surfaces within the machine at the practical ranges of the magnet geometrical parameters and other significant factors. A more clear insight about the heat transfer in the rotor-stator system in this type of electrical machine is presented. It is shown that the overall heat transfer improves significantly with an increase in the magnet thickness ratio, whereas the opposite trend is observed as the magnet angle ratio goes up. Moreover, the results reveal that the stator heat transfer in the gap reaches a maximum for a certain gap thickness.

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Chicago
Rasekh, Alireza, Peter Sergeant, and Jan Vierendeels. 2017. “Fully Predictive Heat Transfer Coefficient Modeling of an Axial Flux Permanent Magnet Synchronous Machine with Geometrical Parameters of the Magnets.” Applied Thermal Engineering 110: 1343–1357.
APA
Rasekh, A., Sergeant, P., & Vierendeels, J. (2017). Fully predictive heat transfer coefficient modeling of an axial flux permanent magnet synchronous machine with geometrical parameters of the magnets. APPLIED THERMAL ENGINEERING, 110, 1343–1357.
Vancouver
1.
Rasekh A, Sergeant P, Vierendeels J. Fully predictive heat transfer coefficient modeling of an axial flux permanent magnet synchronous machine with geometrical parameters of the magnets. APPLIED THERMAL ENGINEERING. 2017;110:1343–57.
MLA
Rasekh, Alireza, Peter Sergeant, and Jan Vierendeels. “Fully Predictive Heat Transfer Coefficient Modeling of an Axial Flux Permanent Magnet Synchronous Machine with Geometrical Parameters of the Magnets.” APPLIED THERMAL ENGINEERING 110 (2017): 1343–1357. Print.
@article{8081714,
  abstract     = {This paper describes new correlations for the convective heat transfer assessment in an axial flux permanent magnet synchronous machine. The case-study here is composed of an open rotor-stator with sixteen magnets at the periphery of the rotor with an annular opening in the entire disk. Air can flow in a
channel being formed between the magnets and in a small gap region between the magnets and the stator surface. The idea is to use the space in between adjacent rotor magnets as cooling air-channels. The rotor disk with the magnets then behaves as a centrifugal fan causing efficient air gap cooling. In order to construct the correlations, CFD simulations are performed at the practical ranges of important non-dimensional parameters including the gap size ratio, the rotational Reynolds number, the magnet angle ratio and the magnet thickness ratio. Considering the geometric periodicity of the computational domain, only one magnet on the rotor disk is investigated. Moreover, the Frozen Rotor method is used to simulate the rotary motion of the rotor
together with the fluid around it. Unlike most precedent studies that considered ambient temperature as the reference temperature, therefore making the estimated convective heat coefficient dependent on the surface temperature, a different approach has been taken into account here. The reference temperature is computed through a minimization method in such a way that the mean Nusselt number becomes rather independent of the surface temperatures. It is found that the proposed correlations can strongly predict the heat transfer rates for all surfaces within the machine at the practical ranges of the magnet
geometrical parameters and other significant factors. A more clear insight about the heat transfer in the rotor-stator system in this type of electrical machine is presented. It is shown that the overall heat transfer improves significantly with an increase in the magnet thickness ratio, whereas the opposite trend is observed as the magnet angle ratio goes up. Moreover, the results reveal that the stator heat transfer in the gap reaches a maximum for a certain gap thickness.},
  author       = {Rasekh, Alireza and Sergeant, Peter and Vierendeels, Jan},
  issn         = {1359-4311},
  journal      = {APPLIED THERMAL ENGINEERING},
  language     = {eng},
  pages        = {1343--1357},
  title        = {Fully predictive heat transfer coefficient modeling of an axial flux permanent magnet synchronous machine with geometrical parameters of the magnets},
  url          = {http://dx.doi.org/10.1016/j.applthermaleng.2016.09.019},
  volume       = {110},
  year         = {2017},
}

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