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Technical Lecture

Magnetics Modeling and Simulations

T36.3 - A Two – Stage Artificial Neural Network (ANN) – based Design and Optimization of High Frequency Transformers for Dual Active Bridge Converter

Thursday, March 20, 2025
10:50 AM – 11:10 AM ET
Location: Level Three, A312
With the increase in high-frequency applications such as electric vehicles, finding a transformer that can handle high frequency, high power density, and high efficiency while ensuring effective thermal management is crucial. This paper presents a novel two-stage model-based design optimization methodology for high-frequency transformers based on Artificial Neural Networks (ANN): electromagnetic (EM) and thermal modelling. This methodology accelerates the design process based on FEM simulations, enabling the selection of the most suitable transformer design from 70,784 design points in 5 minutes instead of 246 days. The relative errors between FEM simulations and ANN models for 99.7% of the dataset are less than 2.5% for EM modelling and 7% for thermal modelling. The methodology was verified experimentally with a 100 kHz litz wire E core transformer and a 75 kHz flat bar E core transformer. A U core-based transformer for a dual active bridge converter, selected from the pareto front using the ANN optimization method, is being built.