About this document

ML Optimization for Solid-State Transformers by usher james is a document available to read on EtoBox.

This document summarizes a machine learning aided optimization framework for designing medium-voltage grid-connected solid-state transformers. The framework involves maximizing efficiency and power density through developing a hybrid local optimization algorithm to tackle challenges from computationally expensive magnetics design and correlations between magnetics and semiconductor performance. A limited number of optimal design datasets are used to train machine learning models to generate optimal design l

Author

usher james

Language

EN