Resonant Frequency Tracking Control for a Linear Compressor with Assist Springs

Takahiro Suzuki, Masaki Koyama, Syuhei Nagata, Wataru Hatsuse, Masatsugu Takemoto, Satoshi Ogasawara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes a drive control method for a linear compressor driven by a linear motor. Generally, the efficiency of a linear motor itself is relatively lower than that of a rotational motor. However, higher efficiency should be achievable by adding assist springs and driving at the resonant frequency. We have developed a novel resonant frequency estimation method that calculates the phase difference between a supplied voltage and a mover position. Since the phase difference changes according to the drive frequency with respect to the resonant frequency, our method calculates the phase difference by using the arctangent of a Fourier coefficient, which controls the drive frequency to keep the phase difference at 90°. Experimental results show that the proposed method can successfully track to the resonant frequency dynamically even if the mechanical condition is changed.

Original languageEnglish
Title of host publicationECCE 2020 - IEEE Energy Conversion Congress and Exposition
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3016-3021
Number of pages6
ISBN (Electronic)9781728158266
DOIs
Publication statusPublished - Oct 11 2020
Event12th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2020 - Virtual, Detroit, United States
Duration: Oct 11 2020Oct 15 2020

Publication series

NameECCE 2020 - IEEE Energy Conversion Congress and Exposition

Conference

Conference12th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2020
CountryUnited States
CityVirtual, Detroit
Period10/11/2010/15/20

Keywords

  • linear compressor
  • linear motor drive
  • permananet magnet machines
  • resonant frequency

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Control and Optimization
  • Energy Engineering and Power Technology

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