NDLI: Nonlinear modeling for switched reluctance motor by measuring flux linkage curves

Content Provider	IEEE Xplore Digital Library
Author	Yan Cai Qingxin Yang Lihua Su Yanbin Wen Yiming You
Copyright Year	2010
Description	Author affiliation: School of Electrical Engineering & Automation, Tianjin Polytechnic University, China (Yan Cai; Qingxin Yang; Lihua Su; Yanbin Wen; Yiming You)
Abstract	Two kinds of modeling methods are studied based on measuring flux linkage curves for switched reluctance motor (SRM) which the machine geometry is unknowable. A simplified model of SRM is presented for general switched reluctance drive (SRD), which is easy to be built and its accuracy has been improved compared with the quasi-linear model. To get an accurate model, the BP Neural Network (BPNN) nonlinear model of SRM is developed based on Levenberg-Marquardt algorithm by measuring flux linkage characteristics. Compared with measured data of flux linkage and torque, the BPNN model of SRM is proved accurate and meet high performance SRD. Both kinds of the modeling methods are suitable for SRD with different control performance requirement respectively.
File Size	423570
File Format	PDF
ISBN	9781424463473
e-ISBN	9781424463497
DOI	10.1109/ICCET.2010.5486289
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-04-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Solid modeling Magnetization nonlinear model Reluctance machines Magnetic analysis Reluctance motors simplified model Couplings Geometry switched reluctance motor (SRM) BP Neural Network Neural networks Voltage Position measurement
Content Type	Text
Resource Type	Article

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