Position sensorless driving of BLDCM using neural networks

Hai Jiao Guo; Seiji Sagawa; Osamu Ichinokura

doi:10.1002/eej.20240

Position sensorless driving of BLDCM using neural networks

Hai Jiao Guo, Seiji Sagawa, Osamu Ichinokura

New Industry Creation Hatchery Center (NICHe)

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

Abstract

A sensorless driving method of brushless DC motors (BLDCM) using neural networks has been studied in this paper. Considering the nonlinear characteristics and the parameter error of the modeling, neural networks are introduced to estimate the electromotive force (EMF). The results of simulation and experiment using offline trained neural networks show that the proposed method is useful. In addition, the robustness about the parameters is discussed.

Original language	English
Pages (from-to)	64-71
Number of pages	8
Journal	Electrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi)
Volume	162
Issue number	4
DOIs	https://doi.org/10.1002/eej.20240
Publication status	Published - 2008 Mar 1

Keywords

Brushless DC motor
Neural network
Position sensorless
Vector control

ASJC Scopus subject areas

Energy Engineering and Power Technology
Electrical and Electronic Engineering

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10.1002/eej.20240

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abstract = "A sensorless driving method of brushless DC motors (BLDCM) using neural networks has been studied in this paper. Considering the nonlinear characteristics and the parameter error of the modeling, neural networks are introduced to estimate the electromotive force (EMF). The results of simulation and experiment using offline trained neural networks show that the proposed method is useful. In addition, the robustness about the parameters is discussed.",

keywords = "Brushless DC motor, Neural network, Position sensorless, Vector control",

author = "Guo, {Hai Jiao} and Seiji Sagawa and Osamu Ichinokura",

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AU - Sagawa, Seiji

AU - Ichinokura, Osamu

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N2 - A sensorless driving method of brushless DC motors (BLDCM) using neural networks has been studied in this paper. Considering the nonlinear characteristics and the parameter error of the modeling, neural networks are introduced to estimate the electromotive force (EMF). The results of simulation and experiment using offline trained neural networks show that the proposed method is useful. In addition, the robustness about the parameters is discussed.

AB - A sensorless driving method of brushless DC motors (BLDCM) using neural networks has been studied in this paper. Considering the nonlinear characteristics and the parameter error of the modeling, neural networks are introduced to estimate the electromotive force (EMF). The results of simulation and experiment using offline trained neural networks show that the proposed method is useful. In addition, the robustness about the parameters is discussed.

KW - Brushless DC motor

KW - Neural network

KW - Position sensorless

KW - Vector control

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ER -

Position sensorless driving of BLDCM using neural networks

Abstract

Keywords

ASJC Scopus subject areas

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