Torque Modeling of a Segmented-Rotor SRM Using Maximum-Correntropy-Criterion-Based LSSVR for Torque Calculation of EVs

High nonlinearities of switched reluctance motor (SRM) caused by its double salient structure limit its industrial application in electric vehicles (EVs). In this article, an algorithm called maximum-correntropy-criterion-based least-squares support vector regression (MCC-LSSVR) is applied to the no...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE journal of emerging and selected topics in power electronics 2021-06, Vol.9 (3), p.2674-2684
Hauptverfasser:	Sun, Xiaodong, Wu, Jiangling, Lei, Gang, Cai, Yingfeng, Chen, Xiaobo, Guo, Youguang
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation models Algorithms Computational modeling Computer simulation Couplings Criteria Electric vehicles Finite element method Industrial applications Mathematical model Mathematical models Maximum correntropy criterion (MCC) Model accuracy nonlinear modeling Nonlinearity Outliers (statistics) Reluctance motors Rotors Support vector machines support vector regression (SVR) switched reluctance motor (SRM) Torque torque modeling
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!