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

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%.

Keywords

• transposition effect
• Litz winding
• epoxy-resin type
• thermal conductivity
• least square method
• accurate prediction