Dynamic modeling of stack giant magnetostrictive actuator with magnetic equivalent network considering eddy current effect

Author:

Chen Zekun1,Yang Xin1ORCID,Li Shuxun1,Zhang Zhihe1,Chen Yukai1

Affiliation:

1. College of Electrical and Information Engineering, Hunan University, Changsha 410082, China

Abstract

Stack giant magnetostrictive actuators (SGMAs) are widely used in various fields for its merits such as saving the space and improving the evenness of the bias magnetic field provided for the giant magnetostrictive material (GMM). In this paper, based on the flow path of the magnetic flux in SGMA, a magnetic equivalent network corresponding to quasistatic conditions is proposed taking flux leakage and fringing effect into account. Meanwhile, complex reluctances of the GMM rods are introduced to describe the decrease and phase shift of magnetic field intensities caused by eddy current under high-frequency excitation signals. Furthermore, the magnetic equivalent network, determining the relationship between excitation signals and magnetic field intensities, is combined with the Jiles–Atherton model, nonlinear constitutive theory of GMM concerning multi-field coupling, and structural dynamics of SGMA so as to derive a multi-field coupling model predicting the tracking behaviors of SGMA to the excitation signals. Moreover, a finite element method is conducted, an SGMA prototype is fabricated, and an experimental platform is set up to verify the proposed model. Comparison between results derived from the magnetic equivalent network and those calculated by the finite element method indicates that the proposed network is able to predict the magnetic field distribution inside the SGMA prototype in quasistatic conditions; further comparison between results obtained from the proposed multi-field coupling model and those from experiments indicates that the model can accurately predict tracking behaviors of the SGMA prototype to the excitation signals.

Publisher

AIP Publishing

Subject

General Physics and Astronomy

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