Open AccessSensorless position estimation of switched reluctance motor at startup using quadratic polynomial regression
Author(s) -
Chang YanTai,
Cheng Ka Wai Eric
Publication year - 2013
Publication title -
iet electric power applications
Language(s) - English
Resource type - Journals
ISSN - 1751-8679
DOI - 10.1049/iet-epa.2012.0306
Subject(s) - switched reluctance motor , control theory (sociology) , quadratic equation , position (finance) , polynomial , polynomial regression , regression , mathematics , computer science , engineering , statistics , artificial intelligence , electrical engineering , economics , mathematical analysis , rotor (electric) , geometry , control (management) , finance
Sensorless position sensing of switched reluctance motor (SRM) has been of great interests to researchers for reducing costs and increasing reliability of the system. The startup position estimation is a difficult task. This study presents a new method to estimate motor phase positions during startup. It is based on the general magnetic characteristics of the inductance profile in an SRM. All phase positions are estimated without using any specific magnetic information. The calculation is simple and can be implemented easily and executed efficiently in a microcontroller.