Sensorless IPMSM drive system using saliency back-EMF-Based intelligent torque observer with MTPA control

Faa Jeng Lin, Ying Chih Hung, Jia Ming Chen, Chao Ming Yeh

Research output: Contribution to journalArticlepeer-review

49 Scopus citations

Abstract

A saliency back-electromotive force (EMF)-based wavelet fuzzy neural network (WFNN) torque observer using a new maximum torque per ampere (MTPA) control is proposed in this study to improve the speed estimating performance of a sensorless interior permanent magnet synchronous motor (IPMSM) drive system. First, the characteristics and mathematical model of the saliency back-EMF-based proportional-integral-derivative (PID) torque observer with the mechanical model-based phase-lock-loop (PLL) for the estimation of the rotor flux angle and speed of the IPMSM are discussed. Then, a new saliency back-EMF-based MTPA control suitable for the implementation using digital signal processor (DSP) is introduced. Moreover, the saliency back-EMF-based rotor flux angle and speed estimation method using WFNN torque observer is proposed. Furthermore, detailed network structure and online learning algorithms of WFNN are described. Finally, the feasibility of the proposed control schemes is verified through experimental results.

Original languageEnglish
Article number6736097
Pages (from-to)1226-1241
Number of pages16
JournalIEEE Transactions on Industrial Informatics
Volume10
Issue number2
DOIs
StatePublished - May 2014

Keywords

  • Interior permanent magnet synchronous motor (IPMSM)
  • Wavelet fuzzy neural network (WFNN)
  • maximum torque per ampere (MTPA)
  • saliency back-EMF
  • sensorless control

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