Performance of support vector regression machines on determining the magnetic characteristics of the E-core transverse flux machine

Authors : ÇİĞDEM GÜNDOĞAN TÜRKER, FERİHA ERFAN KUYUMCU, NURHAN TÜRKER TOKAN

Pages : 698-708

Doi:10.3906/elk-1301-84

View : 15 | Download : 9

Publication Date : 0000-00-00

Article Type : Research Paper

Abstract :The E-core transverse flux machine insert ignore into journalissuearticles values(ETFM); has major advantages with its different and unique structure in conventional electrical machines. It is a combination of transverse flux and reluctance principle. In this work, support vector regression machines insert ignore into journalissuearticles values(SVRMs); are used to obtain the magnetic characteristic parameters of the ETFM for the first time and it is compared with its artificial neural network model. The data for the training and testing of the SVRMs are obtained from experimental measurements. It is proven that SVRMs can conveniently be used in the modeling of the magnetic behaviors of highly nonlinear ETFM with better accuracy and efficiency.
Keywords : E core transverse flux machine, magnetic characteristics, artificial neural network, support vector regression machines