Study on the dual-segment arctangent model of magnetorheological damper (MRD)

Abstract Magnetorheological fluid damper (MRD) is a damping device that utilizes the instantaneous variable characteristics of magnetorheological fluid in magnetic field to control damping force. At present, there are some problems with the existing mechanical parametric models of MRD, such as the complexity of parameters in the Bouc–Wen model, low model accuracy, and the inability of the Bingham model to accurately capture the hysteresis characteristics of damping force with velocity variation. In response to these issues, on the base of MRD performance testing, a dual-segment arctangent model based on arctangent function is proposed. This model uses the arctangent function to describe the nonlinearity of the damping force output curve. And using piecewise fitting method to accurately capture the hysteresis characteristics of the output curve. Compared with existing parametric models such as the Bingham model, Sigmoid model, Bouc–wen improved model, et al , the dual-segment arctangent model shows simpler parameters and higher model fitting accuracy. The comparative analysis of the fitting results based on experimental data confirms the effectiveness and accuracy of the proposed model, providing-valuable reference for the development of high-precision MRD mechanical models.

Authors

Institutions

Publication Details

Journal
Smart Materials and Structures
Published
2024-11-28
DOI
https://doi.org/10.1088/1361-665x/ad9877
Citations
2
Primary Topic
Vibration Control and Rheological Fluids
Type
article
Field-Weighted Citation Impact
0.52

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Study on the dual-segment arctangent model of magnetorheological damper (MRD)

Jiaxuan Guo, Yanjuan Zhang, Xin Li, Tianzhou Luo
2 citations
Smart Materials and Structures
Vibration Control and Rheological Fluids
0.52
article

Study on the dual-segment arctangent model of magnetorheological damper (MRD)

Jiaxuan Guo, Yanjuan Zhang, Xin Li, Tianzhou Luo
article en
2 citations

Abstract

Abstract Magnetorheological fluid damper (MRD) is a damping device that utilizes the instantaneous variable characteristics of magnetorheological fluid in magnetic field to control damping force. At present, there are some problems with the existing mechanical parametric models of MRD, such as the complexity of parameters in the Bouc–Wen model, low model accuracy, and the inability of the Bingham model to accurately capture the hysteresis characteristics of damping force with velocity variation. In response to these issues, on the base of MRD performance testing, a dual-segment arctangent model based on arctangent function is proposed. This model uses the arctangent function to describe the nonlinearity of the damping force output curve. And using piecewise fitting method to accurately capture the hysteresis characteristics of the output curve. Compared with existing parametric models such as the Bingham model, Sigmoid model, Bouc–wen improved model, et al , the dual-segment arctangent model shows simpler parameters and higher model fitting accuracy. The comparative analysis of the fitting results based on experimental data confirms the effectiveness and accuracy of the proposed model, providing-valuable reference for the development of high-precision MRD mechanical models.

Smart Materials and StructuresVol. 34(1)
Shanghai Tunnel Engineering Rail Transit Design & Research Institute (CN), Beijing University of Civil Engineering and Architecture (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 35%
Vibration Control and Rheological Fluids
0.52
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.