High-Frequency Core Loss Modeling Based on Knowledge-Aware Artificial Neural Network
Author:
Affiliation:
1. Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands
2. Yongjiang Laboratory, Ningbo, China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/63/10368210/10315145.pdf?arnumber=10315145
Reference17 articles.
1. Accurate prediction of ferrite core loss with nonsinusoidal waveforms using only Steinmetz parameters
2. Calculation of Ferrite Core Losses with Arbitrary Waveforms using the Composite Waveform Hypothesis
3. An Improved Empirical Formulation for Magnetic Core Losses Estimation Under Nonsinusoidal Induction
4. Artificial Neural Network (ANN) Based Fast and Accurate Inductor Modeling and Design
5. Artificial Neural Network Aided Loss Maps for Inductors and Transformers
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