A novel reliable parametric model for predicting the nonlinear hysteresis phenomenon of composite magnetorheological fluid

Abstract Magnetorheological fluid (MRF), as a novel intelligent composite material, possesses unique controllable properties in the presence of a magnetic field, thereby opening up new possibilities for its engineering applications. This study proposes a novel parametric model to predict the nonlinear hysteresis behavior of MRF using micron-scale carbonyl iron particles. Experiments with large-amplitude shear tests (10% strain amplitude, 0.1 Hz and 1 Hz frequencies) were conducted at five current levels (0 A, 0.5 A, 1 A, 1.5 A, and 2 A) to identify model parameters via a genetic optimization algorithm. The proposed model, with fewer parameters and no differential operators, outperforms existing models (e.g. Bouc–Wen and hyperbolic tangent models) in capturing MRF’s nonlinear behavior. This research provides a robust theoretical framework for predicting the nonlinear hysteresis in automotive dampers and semi-active suspension control.

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Publication Details

Journal
Smart Materials and Structures
Published
2025-03-01
DOI
https://doi.org/10.1088/1361-665x/adbf57
Citations
38
Primary Topic
Vibration Control and Rheological Fluids
Type
article
Field-Weighted Citation Impact
36.22

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article

A novel reliable parametric model for predicting the nonlinear hysteresis phenomenon of composite magnetorheological fluid

Qianwei Liu, Guinan Chen, Qing Ouyang, Teng Shen et al.
38 citations
Smart Materials and Structures
Vibration Control and Rheological Fluids
36.22
article

A novel reliable parametric model for predicting the nonlinear hysteresis phenomenon of composite magnetorheological fluid

Qianwei Liu, Guinan Chen, Qing Ouyang, Teng Shen, Jiong Wang, Min Sun, Ye Qiu, Jia-Hao Luo, Junyu Chen, Guang Zhang, Zheng Zhang, Bo Chen, Yang Yu
article en
38 citations

Abstract

Abstract Magnetorheological fluid (MRF), as a novel intelligent composite material, possesses unique controllable properties in the presence of a magnetic field, thereby opening up new possibilities for its engineering applications. This study proposes a novel parametric model to predict the nonlinear hysteresis behavior of MRF using micron-scale carbonyl iron particles. Experiments with large-amplitude shear tests (10% strain amplitude, 0.1 Hz and 1 Hz frequencies) were conducted at five current levels (0 A, 0.5 A, 1 A, 1.5 A, and 2 A) to identify model parameters via a genetic optimization algorithm. The proposed model, with fewer parameters and no differential operators, outperforms existing models (e.g. Bouc–Wen and hyperbolic tangent models) in capturing MRF’s nonlinear behavior. This research provides a robust theoretical framework for predicting the nonlinear hysteresis in automotive dampers and semi-active suspension control.

Smart Materials and StructuresVol. 34(3)
UNSW Sydney (AU), Nanjing University of Science and Technology (CN), Guangzhou University (CN), Jiaxing University (CN), Zhejiang University of Technology (CN), Zhejiang University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 0%
Vibration Control and Rheological Fluids
36.22
DOISourceOpenAlex
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