Application of Digital Twin Concept in Condition Monitoring for DC-DC Converter

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Abstract

This paper presents a digital twin-based condition monitoring method for DC-DC power converters, which features non-invasive and without additional hardware. To demonstrate it, a buck converter is applied as a case study with theoretical analysis and experimental verification. The digital twin of the buck converter is established, which includes the power stage, sampling circuit, and close-loop controller. Particle Swarm Op-timization (PSO) algorithm is applied to minimize the difference between the digital twin and its physical counterpart. Compare to conventional methods, the proposed method is able to monitor the health indicators of the key components in the buck converter: capacitor and MOSFET, without adding extra measurement circuits. Moreover, because the digital twin is a replica of the physical buck converter, accessing to the internal buck converter is unnecessary, which is non-invasive.
Original languageEnglish
Title of host publicationProceedings of 2019 IEEE Energy Conversion Congress and Exposition (ECCE)
Number of pages6
PublisherIEEE Press
Publication dateSep 2019
Pages2199-2204
Article number8912199
ISBN (Electronic)9781728103952
DOIs
Publication statusPublished - Sep 2019
Event2019 IEEE Energy Conversion Congress and Exposition (ECCE) - Baltimore, United States
Duration: 29 Sep 20193 Oct 2019

Conference

Conference2019 IEEE Energy Conversion Congress and Exposition (ECCE)
CountryUnited States
City Baltimore
Period29/09/201903/10/2019
SeriesIEEE Energy Conversion Congress and Exposition
ISSN2329-3721

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Keywords

  • Component
  • Digital twin
  • DC-DC
  • Health condition
  • Parameter identification

Cite this

Peng, Y., & Wang, H. (2019). Application of Digital Twin Concept in Condition Monitoring for DC-DC Converter. In Proceedings of 2019 IEEE Energy Conversion Congress and Exposition (ECCE) (pp. 2199-2204). [8912199] IEEE Press. IEEE Energy Conversion Congress and Exposition https://doi.org/10.1109/ECCE.2019.8912199