Asymmetrically Driven HB-LLC Resonant Converter Integrated in Low-Power IoT Devices

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

1 Scopus citations

Abstract

This paper introduces a generalized time-domain analysis framework for asymmetrically driven half-bridge LLC (HB-LLC) resonant converters. It allows accurate gain derivation and monotonicity attributes characterization for both CCM and DCM, i.e. for high- and low-Q operating conditions with any arbitrary duty-cycle ratio. The analysis is carried out without using First-Harmonic Approximation (FHA) and takes into consideration the resonant capacitor ripple, thus truthfully obtaining the converter's load-dependent gain curves. The analysis framework is experimentally verified on a compact converter operating in the MHz range for low-power IoT applications, demonstrating the non-monotonicity attributes of asymmetrically driven HB-LLC resonant converter and validating the accuracy of its gain derivation procedure for various operating conditions.

Original languageEnglish
Title of host publicationAPEC 2023 - 38th Annual IEEE Applied Power Electronics Conference and Exposition
PublisherInstitute of Electrical and Electronics Engineers
Pages2105-2110
Number of pages6
ISBN (Electronic)9781665475396
DOIs
StatePublished - 1 Jan 2023
Event38th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2023 - Orlando, United States
Duration: 19 Mar 202323 Mar 2023

Publication series

NameConference Proceedings - IEEE Applied Power Electronics Conference and Exposition - APEC
Volume2023-March

Conference

Conference38th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2023
Country/TerritoryUnited States
CityOrlando
Period19/03/2323/03/23

Keywords

  • LLC
  • PFM
  • PWM
  • resonant converter
  • time-domain analysis

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Asymmetrically Driven HB-LLC Resonant Converter Integrated in Low-Power IoT Devices'. Together they form a unique fingerprint.

Cite this