Open AccessA Wavelet descriptor model of hysteresis loop phenomena
Author(s) -
Bisht Hrishitosh,
Gadre Vikram M.,
Kulkarni Shrikrishna V.,
Sai Ram Boggavarapu
Publication year - 2020
Publication title -
iet electric power applications
Language(s) - English
Resource type - Journals
ISSN - 1751-8679
DOI - 10.1049/iet-epa.2020.0363
Subject(s) - wavelet , harmonics , fourier series , fourier transform , hysteresis , fourier analysis , algorithm , computer science , multiresolution analysis , wavelet transform , mathematics , artificial intelligence , discrete wavelet transform , mathematical analysis , voltage , physics , quantum mechanics
An accurate and computationally efficient hysteresis model is required to perform transient finite element analysis of electrical machines and transformers. Numerical experiments performed in the current work suggest that there are severe limitations of the Fourier descriptor method. In this work, the authors build upon the idea of Fourier descriptors and propose a wavelet descriptor model to characterise magnetic hysteresis curves, with the advantages of Fourier descriptors while their disadvantages are mitigated. It is shown that wavelet descriptors can also be used to compute hysteresis losses. The motivation behind using a wavelet basis rather than a Fourier basis is the ability of wavelets to represent local features of the signal. The method can efficiently represent a complete B/H curve with only a few data‐points and allows for an automated representation of hysteresis loops. Wavelet descriptors are used for the first time to model a wide variety of hysteresis loops with asymmetric minor loops generated using higher‐order harmonics, and from a pulse‐width modulated source. The results obtained using the proposed method are compared with those of the Fourier descriptor method. In all cases, the proposed method outperforms the Fourier descriptor method. The proposed method is computationally efficient and simple to understand.