A Digital Twin based Estimation Method for Health Indicators of DC-DC Converters

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Abstract

This article proposes a health indicator estimation method based on the digital-twin concept aiming for condition monitoring of power electronic converters. The method is noninvasive, without additional hardware circuits, and calibration requirements. An application for a buck dc-dc converter is demonstrated with theoretical analyses, practical considerations, and experimental verifications. The digital replica of an experimental prototype is established, which includes the power stage, sampling circuit, and close-loop controller. Particle swarm optimization algorithm is applied to estimate the unknown circuit parameters of interest based on the incoming data from both the digital twin and the physical prototype. Cluster-data of the estimated health indicators under different testing conditions of the buck converter is analyzed and used for observing the degradation trends of key components, such as capacitor and MOSFET. The outcomes of this article serve as a key step for achieving noninvasive, cost-effective, and robust condition monitoring for power electronic converters.

Original languageEnglish
Article number9141430
JournalI E E E Transactions on Power Electronics
Volume36
Issue number2
Pages (from-to)2105-2118
Number of pages14
ISSN0885-8993
DOIs
Publication statusPublished - Feb 2021

Keywords

  • Condition monitoring
  • IGBT
  • dc-dc power converters
  • digital twin
  • parameter identification
  • reliability

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