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

Yingzhou Peng, Huai Wang

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    37 Scopus citations

    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 languageBritish English
    Title of host publication2019 IEEE Energy Conversion Congress and Exposition, ECCE 2019
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages2199-2204
    Number of pages6
    ISBN (Electronic)9781728103952
    DOIs
    StatePublished - Sep 2019
    Event11th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2019 - Baltimore, United States
    Duration: 29 Sep 20193 Oct 2019

    Publication series

    Name2019 IEEE Energy Conversion Congress and Exposition, ECCE 2019

    Conference

    Conference11th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2019
    Country/TerritoryUnited States
    CityBaltimore
    Period29/09/193/10/19

    Keywords

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

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