Modeling and Parameter Identification of MR Damper considering Excitation Characteristics and Current

Smart structures such as damping adjustable dampers made of magnetorheological (MR) fluid can be used to attenuate vibration transmission in vehicle seat suspension. The main research content of this paper is the nonlinearity and hysteresis characteristics of the MR damper. A hysteretic model consid...

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Main Authors: Shuguang Zhang, Wenku Shi, Zhiyong Chen
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Shock and Vibration
Online Access:http://dx.doi.org/10.1155/2021/6691650
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spelling doaj-5400cc65542d41268aab8685a5c584d72021-04-19T00:04:23ZengHindawi LimitedShock and Vibration1875-92032021-01-01202110.1155/2021/6691650Modeling and Parameter Identification of MR Damper considering Excitation Characteristics and CurrentShuguang Zhang0Wenku Shi1Zhiyong Chen2State Key of Automobile Simulation and Control LaboratoryState Key of Automobile Simulation and Control LaboratoryState Key of Automobile Simulation and Control LaboratorySmart structures such as damping adjustable dampers made of magnetorheological (MR) fluid can be used to attenuate vibration transmission in vehicle seat suspension. The main research content of this paper is the nonlinearity and hysteresis characteristics of the MR damper. A hysteretic model considering both excitation characteristics and input current is proposed to fit the damper force-velocity curve for the MR damper under different conditions. Multifactor sensitivity analysis based on the neural network method is used to obtain importance parameters of the hyperbolic tangent model. In order to demonstrate the fitting precision of the different models, the shuffled frog-leaping algorithm (SFLA) is employed to identify the parameters of MR damper models. The research results indicate that the modified model can not only describe the nonlinear hysteretic behavior of the MR damper more accurately in fixed conditions, compared with the original model, but also meet the fitting precision under a wide range of magnitudes of control current and excitation conditions (frequency and amplitude). The method of parameter sensitivity analysis and identification can also be used to modify other nonlinear dynamic models.http://dx.doi.org/10.1155/2021/6691650
collection DOAJ
language English
format Article
sources DOAJ
author Shuguang Zhang
Wenku Shi
Zhiyong Chen
spellingShingle Shuguang Zhang
Wenku Shi
Zhiyong Chen
Modeling and Parameter Identification of MR Damper considering Excitation Characteristics and Current
Shock and Vibration
author_facet Shuguang Zhang
Wenku Shi
Zhiyong Chen
author_sort Shuguang Zhang
title Modeling and Parameter Identification of MR Damper considering Excitation Characteristics and Current
title_short Modeling and Parameter Identification of MR Damper considering Excitation Characteristics and Current
title_full Modeling and Parameter Identification of MR Damper considering Excitation Characteristics and Current
title_fullStr Modeling and Parameter Identification of MR Damper considering Excitation Characteristics and Current
title_full_unstemmed Modeling and Parameter Identification of MR Damper considering Excitation Characteristics and Current
title_sort modeling and parameter identification of mr damper considering excitation characteristics and current
publisher Hindawi Limited
series Shock and Vibration
issn 1875-9203
publishDate 2021-01-01
description Smart structures such as damping adjustable dampers made of magnetorheological (MR) fluid can be used to attenuate vibration transmission in vehicle seat suspension. The main research content of this paper is the nonlinearity and hysteresis characteristics of the MR damper. A hysteretic model considering both excitation characteristics and input current is proposed to fit the damper force-velocity curve for the MR damper under different conditions. Multifactor sensitivity analysis based on the neural network method is used to obtain importance parameters of the hyperbolic tangent model. In order to demonstrate the fitting precision of the different models, the shuffled frog-leaping algorithm (SFLA) is employed to identify the parameters of MR damper models. The research results indicate that the modified model can not only describe the nonlinear hysteretic behavior of the MR damper more accurately in fixed conditions, compared with the original model, but also meet the fitting precision under a wide range of magnitudes of control current and excitation conditions (frequency and amplitude). The method of parameter sensitivity analysis and identification can also be used to modify other nonlinear dynamic models.
url http://dx.doi.org/10.1155/2021/6691650
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AT wenkushi modelingandparameteridentificationofmrdamperconsideringexcitationcharacteristicsandcurrent
AT zhiyongchen modelingandparameteridentificationofmrdamperconsideringexcitationcharacteristicsandcurrent
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