Insertion Loss Prediction of Differential Mode EMI Filter Based on Artificial Neural Network

Insertion loss (IL) is the main performance index of electromagnetic interference (EMI) filter, and the accuracy of its model directly affects the parameter design of EMI filter. In order to improve the prediction accuracy of insertion loss of EMI filters, accurately describe system behavior and predict EMI filter filtering performance. This paper uses artificial neural network to model the insertion loss of differential mode EMI filters, aiming to provide guidance for the design and optimization of EMI filters.