文章基本信息

标题：Parameter Identification of Switched Reluctance Motor Using Exponential Swept-Sine Signal
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作者：A. Ouannou ; F. Giri ; A. Brouri 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2022
卷号：55
期号：12
页码：132-137
DOI：10.1016/j.ifacol.2022.07.300
语种：English
出版社：Elsevier
摘要：AbstractSwitched reluctance motors (SRMs) present major interest in several domains, e.g., in electric vehicles, because of their wide range speed variation, high performances, low cost, and robustness to run under degraded conditions. This paper aims at developing a new analytical approach for modeling of SRM parameters. Specifically, an identification scheme is proposed to obtain estimates of SRM parameters. Since SRMs have a highly nonlinear behavior, their modeling proves to be challenging. Furthermore, to maximize the energy transfer, SRMs are always operated in magnetically saturated mode. Presently, we will show that SRMs can accurately be described by a generalized polynomial Hammerstein model. The latter is parallel connection of several Hammerstein models having polynomial nonlinearity. Based on this model structure, we design an identification method that consists in: (i) exciting the system with a swept-sine signal; (ii) estimating the model parameter by using finite element method analysis. The effectiveness of the proposed method is highlighted by numerical simulation.
关键词：KeywordsSwitched reluctance motornonlinear systemswept-sine signalgeneralized Hammerstein modelidentification parameters