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Data-Driven Modeling of Zero Voltage Switching of Non-Resonant DAB Converters under TPS Modulation

  • Xinze Li
  • , Fanfan Lin
  • , Josep Pou
  • , Suvajit Mukherjee
  • , Jiaxin Dong

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

DAB converters under triple phase shift (TPS) modulation can broaden the zero voltage switching (ZVS) range to improve efficiency and noise robustness. Conventionally, the piecewise approach and harmonic approach are two commonly used approaches to build analytical models for ZVS conditions under this modulation strategy. However, both two approaches fail to achieve good modeling accuracy as well as low computational cost simultaneously due to heavy human dependence. To solve this problem, this digest proposes a data-driven modeling approach for ZVS analysis (DM-ZVS) for non-resonant DAB converters under the TPS modulation strategy. The data-driven modeling process is conducted with the random forest algorithm automatically using ZVS performance data from simulation tools, greatly mitigating human dependence to improve accuracy and computational efficiency. With the trained data-driven classification model of ZVS, the optimal TPS modulation parameters can be found to ensure the full ZVS range. A design case is given, and 1 kW hardware experiments comprehensively validate the feasibility of the proposed DM-ZVS. © 2023 IEEE.
Original languageEnglish
Title of host publicationAPEC 2023 - Thirty-Eigth Annual IEEE Applied Power Electronics Conference and Exposition
PublisherIEEE
Pages1379-1383
ISBN (Electronic)9781665475396
ISBN (Print)9781665475402
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event38th Annual IEEE Applied Power Electronics Conference and Exposition (APEC 2023) - Orange County Convention Center, Orlando, United States
Duration: 19 Mar 2023 → 23 Mar 2023
https://ieeexplore.ieee.org/xpl/conhome/10131044/proceeding

Publication series

NameConference Proceedings - IEEE Applied Power Electronics Conference and Exposition - APEC
Volume2023-March
ISSN (Print)1048-2334
ISSN (Electronic)2470-6647

Conference

Conference38th Annual IEEE Applied Power Electronics Conference and Exposition (APEC 2023)
PlaceUnited States
CityOrlando
Period19/03/23 → 23/03/23
Internet address

Research Keywords

  • artificial intelligence
  • data-driven
  • efficiency
  • modeling
  • triple phase shift modulation
  • zero voltage switching

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