Three autoregressive-neural network hybrid models for energy efficiency estimation of induction motors

SERTSÖZ, MİNE; FİDAN, MEHMET; KURBAN, MEHMET

doi:10.1108/compel-02-2018-0093

Three autoregressive-neural network hybrid models for energy efficiency estimation of induction motors

COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING, cilt.38, sa.1, ss.431-451, 2019 (SCI-Expanded)

Yayın Türü: Makale / Tam Makale
Cilt numarası: 38 Sayı: 1
Basım Tarihi: 2019
Doi Numarası: 10.1108/compel-02-2018-0093
Dergi Adı: COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING
Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
Sayfa Sayıları: ss.431-451
Anahtar Kelimeler: Energy efficiency, Estimation, Autoregressive model, Back-propagation, Induction motors, AIR-GAP TORQUE
Anadolu Üniversitesi Adresli: Evet

Özet

Purpose - Improvements on the energy efficiency of the induction motors bear on not only these motors but also on the whole industry as a result of preference of these types of motors. In recent projects, energy efficiency of the induction motors is approaching to 90 per cent. The first necessary condition of the efficiency improvements is an accurate estimation of energy efficiency. This study aims to estimate the energy efficiency of induction motors by using three innovative estimation methods.