Open AccessHigh‐precision non‐linear modelling method for a switched reluctance linear machine by interpolation with using variant sigmoid function
Author(s) -
Nie Rui,
Chen Hao,
Wang Haiying,
Zhao Shuyan,
Wang Xing,
Pires Vitor,
Martins João,
Gorbounov Yassen
Publication year - 2020
Publication title -
iet electric power applications
Language(s) - English
Resource type - Journals
ISSN - 1751-8679
DOI - 10.1049/iet-epa.2019.0563
Subject(s) - sigmoid function , interpolation (computer graphics) , linear interpolation , switched reluctance motor , fourier series , computer science , flux linkage , finite element method , algorithm , process (computing) , control theory (sociology) , mathematics , artificial intelligence , engineering , mathematical analysis , pattern recognition (psychology) , artificial neural network , motion (physics) , mechanical engineering , direct torque control , electrical engineering , structural engineering , control (management) , voltage , rotor (electric) , induction motor , operating system
This study presents a non‐linear modelling method for a switched reluctance linear machine (SRLM), which achieves high modelling precision while requiring no prior knowledge regarding the specific structural dimensions of an SRLM. The proposed modelling method provides accurate flux linkage data based on limited experimental measurements through an interpolation process using a variant sigmoid function. The accuracy of the interpolation process is further increased by considering mutual coupling among the three phases. The performance of the proposed method is validated experimentally by comparing it with the performances of the Fourier series method and the two‐dimensional finite element method. The results demonstrate that the proposed method achieves greater modelling precision than the other methods considered in modelling an SRLM.