A Machine Learning Modeling Method for Switched Reluctance Motors Based on Few Preprocessed Flux Linkage Data

This article proposes a machine learning method to build the model of a switched reluctance motor (SRM) using few preprocessed flux linkage data. Firstly, the improved torque balance method is used to obtain the accurate flux linkage data without redundant experiments. Secondly, two special data pre...

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Vydané v:	Journal of electrical engineering & technology Ročník 20; číslo 5; s. 3445 - 3456
Hlavní autori:	zhao, Yan, Zhu, Jingwei, Ren, Ping, Jing, Zhe
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Singapore Springer Nature Singapore 01.07.2025 Springer Nature B.V 대한전기학회
Predmet:	Electrical Engineering Electrical Machines and Networks Electronics and Microelectronics Engineering Instrumentation Original Article Power Electronics 전기공학 Nonlinear modeling Switched reluctance motor Data preprocessing Improved tuna swarm algorithm Support vector regression algorithm
ISSN:	1975-0102, 2093-7423
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