Online adaptive space vector modulation

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

1 Citation (Scopus)
46 Downloads (Pure)

Abstract

In this paper, we present a new modulation method for multilevel three-phase inverters, called online adaptive space vector modulation (oaSVM). The task of a modulator is to reconstruct the desired voltage υ* from the available discrete voltage vectors that correspond to the inverter switch positions. State-of-the-art SVM chooses three voltage vectors that form the closest triangle containing υ*. On the other hand, oaSVM explores every possible triangle that contains υ* and selects the three voltage vectors such that the trade-off between inverter switching losses and load current total harmonic distortion (THD) is improved. Inverter switching constraints and neutral-point voltage balancing are also included. The resulting mixed-integer optimization problem is solved using a branch and bound method. Through MATLAB-simulations, the loss-THD trade-off between SVM and oaSVM will be compared and we show that oaSVM can improve the inverter's efficiency.
Original languageEnglish
Title of host publication12th International Conference on Power Electronics, Machines and Drives, PEMD 2023
PublisherInstitution of Engineering and Technology
Pages426-433
Number of pages8
ISBN (Electronic)978-1-83953-950-3
DOIs
Publication statusPublished - 21 Nov 2023
Event12th International Conference on Power Electronics, Machines and Drives (PEMD 2023) - Brussels, Belgium
Duration: 23 Oct 202324 Oct 2023

Publication series

NameIET Conference Proceedings
Number17
Volume2023

Conference

Conference12th International Conference on Power Electronics, Machines and Drives (PEMD 2023)
Country/TerritoryBelgium
CityBrussels
Period23/10/2324/10/23

Keywords

  • MIXED-INTEGER OPTIMIZATION
  • NEUTRAL-POINT CLAMPED INVERTER
  • SPACE VECTOR MODULATION
  • SWITCHING LOSSES
  • TOTAL HARMONIC DISTORTION

Fingerprint

Dive into the research topics of 'Online adaptive space vector modulation'. Together they form a unique fingerprint.

Cite this