Modulated model predictive current control of an indirect matrix converter with active damping

Zhengfei Di, M. Rivera, Hanbing Dan, Luca Tarisciotti, Kehan Zhang, Demin Xu, Patrick Wheeler

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

5 Citations (Scopus)

Abstract

A modulated model predictive control (M2PC) scheme for an indirect matrix converter is proposed in this paper, including an active damping method to mitigate the input filter resonance. The control strategy allows the instantaneous power control and the output current control at the same time, operating at a fixed frequency. An optimal switching pattern is used to emulate the desired waveform quality features of space vector modulation and achieve zero-current switching operations. The active damping technique emulates a virtual resistor which damps the filter resonance. Simulation results present a good tracking to the output-current references, unity input displacement power factor, the low input-current distortions and a reduced common-mode voltage (CMV).

Original languageEnglish
Title of host publicationProceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1313-1318
Number of pages6
ISBN (Electronic)9781538611272
DOIs
Publication statusPublished - 15 Dec 2017
Event43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 - Beijing, China
Duration: 29 Oct 20171 Nov 2017

Publication series

NameProceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
Volume2017-January

Conference

Conference43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017
Country/TerritoryChina
CityBeijing
Period29/10/171/11/17

Keywords

  • active damping
  • Matrix converter
  • modulated model predictive control
  • unity input displacement power factor

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Control and Optimization
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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