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Prediction of Thermal Conductivity of Litz Winding by Least Square Method and GA-BP Neural Network Based on Numerical Simulations

Author

Listed:
  • Qi Dong

    (Wuhan Institute of Marine Electric Propulsion, Wuhan 430064, China)

  • Xiaoli Fu

    (College of Civil Engineering, Tongji University, Shanghai 200092, China)

Abstract

This paper proposes a Litz winding numerical-simulation model considering the transposition effect, and uses the transient-plane-source method to verify the numerical-simulation method. In addition, numerical methods were adopted to further investigate the impact of filling rate and epoxy-resin type, and their combined effects, on thermal conductivity. To facilitate engineering design, the discrete data points were fitted using the least square method to obtain a straightforward and application-friendly polynomial empirical formula. On this basis, the GA-BP neural network was used to analyze the data in order to seek out more accurate prediction results for the entire data set. As a result, compared with the least square method, the error between the prediction result and the target value in the x direction was reduced by 87.04%, and the error in the z direction was reduced by 84.97%.

Suggested Citation

  • Qi Dong & Xiaoli Fu, 2023. "Prediction of Thermal Conductivity of Litz Winding by Least Square Method and GA-BP Neural Network Based on Numerical Simulations," Energies, MDPI, vol. 16(21), pages 1-15, October.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:21:p:7295-:d:1268925
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    References listed on IDEAS

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    1. Junjie Zhao & Bin Zhang & Xiaoli Fu & Shenglin Yan, 2021. "Numerical Study on the Influence of Vortex Generator Arrangement on Heat Transfer Enhancement of Oil-Cooled Motor," Energies, MDPI, vol. 14(21), pages 1-17, October.
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