137 / 2023-10-19 12:08:06
Neural Network-Based Design-Oriented Thermal Model for Natural Cooling Fin Heatsinks
heatsink,thermal,thermal model
全文被拒
Huizhong Sun / Aalborg University
Thermal management is an important part of power electronics converter design. Losses from power electronics converter are conveyed through media and finally dissipated into the air with, mostly, heatsink. Depending on the loss to dissipate, natural cooling or forced air cooling could be used. Traditionally, thermal designers use either empirical formulation or computational fluid dynamics software (CFD) to help heatsink design. However, this could be either ineffective or time-consuming. In this paper, we introduce the neural network tool. A three-layer neural network is used to predict the mean/max temperature on the heatsink based on input dimensional parameters. The average validation set error is 5.7% over a wide shape range, a significant improvement compared with the empirical or datasheet fitting method. Finally, we give two applications of the neural network. i) The thermal resistance boundaries are fitted for a given heatsink volume. Designers could easily utilize it to estimate how large a heatsink is required for their specific design.  ii), A simple thermal network considering heatsink thermal capacitance could be obtained from the neural network.
重要日期
  • 会议日期

    12月08日

    2023

    12月10日

    2023

  • 11月01日 2023

    初稿截稿日期

  • 12月10日 2023

    注册截止日期

主办单位
IEEE IAS
承办单位
Southwest Jiaotong University (SWJTU)
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