A nonlinear full model of switched reluctance motor with artificial neural network

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Tarih

2009

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Pergamon-Elsevier Science Ltd

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

This paper presents a novel nonlinear full model developed by using artificial neural networks (ANNs) for switched reluctance motors (SRMs). The proposed ANN based nonlinear model consists of two different models, namely forward and inverse model. The purpose of the forward model is to estimate the flux linkage and torque of the SRM as a function of stator current and rotor position. And, the purpose of the inverse model is to estimate stator current and flux linkage of the SRM as a function of torque and rotor position. Also conversions can be achieved between torque, stator current and flux linkage with these models. Computational load of the processor has been considered and minimized to use the developed model in real industrial applications. The experimental tests are realized to verify the accuracy and feasibility of the proposed model. (C) 2009 Elsevier Ltd. All rights reserved.

Açıklama

Anahtar Kelimeler

Switched Reluctance Motors, Artificial Neural Networks, Digital Signal Processor, Nonlinear Modeling

Kaynak

Energy Conversion And Management

WoS Q Değeri

Q1

Scopus Q Değeri

Q1

Cilt

50

Sayı

9

Künye