Energy Efficiency Estimation of Induction Motors with Artificial Neural Networks

被引：0

作者：

Sertsoz, Mine ^{[1
]}

Fidan, Mehmet ^{[1
]}

Kurban, Mehmet ^{[2
]}

机构：

[1] Eskisehir Tech Univ, Vocat Sch Transportat, Eskisehir, Turkey

[2] Bilecik Seyh Edebali Univ, Dept Elect & Elect Engn, Bilecik, Turkey

来源：

ENVIRONMENTALLY-BENIGN ENERGY SOLUTIONS | 2020年

关键词：

Induction motors; Efficiency estimation; Energy efficiency; Efficiency estimation methods; AIR-GAP TORQUE;

D O I：

10.1007/978-3-030-20637-6_26

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Induction motors make up 90% of today's motors in the industry. For this reason, the contribution of energy efficiency analyses to induction motors is very important. There are many techniques for measuring the efficiency of electric motors. These are the generally experimental ones as specified in certain standards. Experimental methods can also be divided into direct (IEEE 112-B, CSA-390) or indirect (IEC 34-2, JEC 37) methods. The use of experimental methods is not common due to the cost of installing and operating test laboratories worldwide. Therefore, energy efficiency estimation methods are used in worldwide. In this study, efficiency estimations are made with artificial neural network (ANN), which is an optimization-based estimation method with using data of 307 induction motors' (from small to large) from three different companies (AEG-TECO-GAMAK). The results are very close to the efficiency values given in catalog values. However, another noteworthy issue is that the estimation errors of the efficiency change from company to company. The errors of one company are higher than the others.

引用

页码：493 / 508

页数：16

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