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Black-box modeling of DC-DC converters based on wavelet convolutional neural networks

Author
Rojas, G.; Riba, J.; Moreno-Eguilaz, J.M.
Type of activity
Journal article
Journal
IEEE transactions on instrumentation and measurement
Date of publication
2021-07-19
Volume
70
First page
1
Last page
9
DOI
10.1109/TIM.2021.3098377
Repository
http://hdl.handle.net/2117/353277 Open in new window
URL
https://ieeexplore.ieee.org/document/9490644 Open in new window
Abstract
This paper presents an offline deep learning approach focused to model and identify a 270 V-to-28 V DC-DC step-down converter used in on-board distribution systems of more electric aircrafts (MEA). Manufacturers usually do not provide enough information of the converters. Thus, it is difficult to perform design and planning tasks and to check the behavior of the power distribution system without an accurate model. This work considers the converter as a black-box, and trains a wavelet convolution...
Citation
Rojas, G.; Riba, J.; Moreno-Eguilaz, J.M. Black-box modeling of DC-DC converters based on wavelet convolutional neural networks. "IEEE transactions on instrumentation and measurement", 19 Juliol 2021, vol. 70, p. 1-9.
Keywords
Black box, Convolutional neural networks; (CNNs), DC–DC converter, Identification, Modeling, wavelet
Group of research
MCIA - Motion Control and Industrial Applications Research Group
PERC-UPC - Power Electronics Research Centre

Participants