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Analysis of Dynamic Characteristics of Full-Pitch-Winding Switched Reluctance Motor Based on Reluctance Network Analysis
ISSN: 0148-7191, e-ISSN: 2688-3627
Published March 28, 2017 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
An electromagnetic and motion-coupled analysis is made for a Switched Reluctance Motor (SRM) based on a Reluctance Network Analysis (RNA). A full-pitch-winding SRM is promising since it has a high torque density. Since the motor characteristics such as driving torque significantly depend on commutation pattern, an analysis coupled with motor motion and its drive circuit is requisite for the performance prediction. However, in the full-pitch-winding SRM, the relationship between the coil magnetomotive force and the core flux is complicated, and thus Finite Element Method (FEM) has been major method to predict the motor characteristics, which takes too much computational time for cycle calculations. An RNA treats the relationship of coil magnetomotive force and core flux as lumped parameter circuit, and thus enables fast computation with a macroscopic view of magnetic phenomena. Then, the SRM is treated as a single reluctance network by replacing multiple elements of motor as reluctances. Through the intuitive modeling of geometric configurations of the motor with this method, the global characteristics of the motor should be computed potentially much faster than FEM. Based on this concept, we are currently applying this methodology to the analysis of the full-pitch-winding SRM for the first time. The present paper describes the reluctance network modeling of full-pitch-winding SRM in detail and the motor performance such as magnetomotive force, flux and torque are compared with FEM.
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CitationIshikawa, T., Ikebuchi, K., Nakamura, K., Ichinokura, O. et al., "Analysis of Dynamic Characteristics of Full-Pitch-Winding Switched Reluctance Motor Based on Reluctance Network Analysis," SAE Technical Paper 2017-01-1250, 2017, https://doi.org/10.4271/2017-01-1250.
Data Sets - Support Documents
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