Estimating current derivatives for sensorless motor drive applications

David Hind, Mark Sumner, Chris Gerada

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

15 Citations (Scopus)

Abstract

The PWM current derivative technique for sensorless control of AC machines requires current derivative measurements under certain PWM vectors. This is often not possible under narrow PWM vectors due to high frequency (HF) oscillations which affect the current and current derivative responses. In previous work, researchers extended the time that PWM vectors were applied to the machine for to a threshold known as the minimum pulse width (tmin), in order to allow the HF oscillations to decay and a derivative measurement to be obtained. This resulted in additional distortion to the motor current New experimental results demonstrate that an artificial neural network (ANN) can be used to estimate derivatives using measurements from a standard current sensor before the HF oscillations have fully decayed. This reduces the minimum pulse width required and can significantly reduce the additional current distortion and torque ripple.

Original languageEnglish
Title of host publication2015 17th European Conference on Power Electronics and Applications, EPE-ECCE Europe 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9789075815221
DOIs
Publication statusPublished - 27 Oct 2015
Externally publishedYes
Event17th European Conference on Power Electronics and Applications, EPE-ECCE Europe 2015 - Geneva, Switzerland
Duration: 8 Sep 201510 Sep 2015

Publication series

Name2015 17th European Conference on Power Electronics and Applications, EPE-ECCE Europe 2015

Conference

Conference17th European Conference on Power Electronics and Applications, EPE-ECCE Europe 2015
Country/TerritorySwitzerland
CityGeneva
Period8/09/1510/09/15

Keywords

  • Estimation technique
  • Field Programmable Gate Array (FPGA)
  • Neural network
  • Self-sensing control
  • Sensorless control

ASJC Scopus subject areas

  • Fuel Technology
  • Electrical and Electronic Engineering
  • Energy Engineering and Power Technology

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