A Novel Single-Source Eleven-level Quintuple-Boost Inverter with reduced Component Count

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

2 Scopus citations

Abstract

A single source eleven-level inverter with reduced component count with quintuple voltage boosting ability is presented in this paper. It comprises of thirteen power switches, one power diode, and three capacitors. The voltage stress across the switches is reduced as it does not require an H-bridge circuit to generate negative voltage levels. A simple nearest level control (NLC) which is a fundamental switching frequency-based technique is used to provide gate pulse to the inverter circuit. Comparison with recent topologies in terms of switches, diodes, sources, capacitors used in numbers, and the voltage boosting ability is done to show the merits of the presented topology. The total harmonic distortion (THD) is 8.6% which is near to acceptable limits as per IEEE 519-2014 standard. Finally, experimental and real-time results are presented to validate the operability of the proposed SCMLI topology for different loading conditions.

Original languageEnglish
Title of host publication2022 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages605-609
Number of pages5
ISBN (Electronic)9781665443579
DOIs
StatePublished - 2022
Externally publishedYes
Event1st IEEE IAS Global Conference on Emerging Technologies, GlobConET 2022 - Virtual, Arad, Romania
Duration: 20 May 202222 May 2022

Publication series

Name2022 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2022

Conference

Conference1st IEEE IAS Global Conference on Emerging Technologies, GlobConET 2022
Country/TerritoryRomania
CityVirtual, Arad
Period20/05/2222/05/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

  • Quintuple-boost
  • nearest level control
  • reduce switch count
  • switched-capacitor

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Safety, Risk, Reliability and Quality
  • Media Technology
  • Instrumentation

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