Magnetorheological dampers optimization based on surrogate model and experimental verification

Li, Jiahao; Zhou, Wei; Deng, Xixiang; Zhang, Feng; Luo, Jiayang; Wei, Xin; Liao, Changrong; Shou, Mengjie

doi:10.1016/j.ijmecsci.2024.109093

Cited by 3 publications

(2 citation statements)

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“…In order to determine the relationship between each of these parameters and multiple working condition variation factors, the materials test system(MTS) as shown in figure 1 was used to conduct sinusoidal vibration on the MRD prototype under variable combination working conditions, and the factors of MRD excitation current, vibration frequency, and amplitude were taken as working condition variation factors. Based on the common ranges of vibration parameters such as the vibration frequency in MRD vibration testing [46], a total of three groups of experiments were set up as shown in table 1. In each group, a single working condition variation factor was constant, while the other factors were changed and randomly combined.…”

Section: Proposed Modelmentioning

confidence: 99%

“…Han et al [45] employed the fully-connected multilayer perceptron (MLP) to train the general forward model, achieving characterizing the nonlinear features of MRD damping characteristics taking advantage of MLP's strong nonlinear mapping capability. Li et al [46] proposed a nested long short-term memory-convolutional neural network-efficient channel attention modelling method based on a dual-flow neural network architecture, to achieve accurate predictions of MRD damping characteristics under variable working conditions. Although these neural network models reveal good predictive performance on MRD damping characteristics; nevertheless, their reliance on a large number of experimental samples and high dependency on experimental data limit their applicability.…”

Section: Introductionmentioning

confidence: 99%

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Multi-condition adaptive detail characterization model of magnetorheological dampers and experimental verification

Lei,

Li,

et al. 2024

Phys. Scr.

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The theoretical model for predicting the damping characteristics of magnetorheological dampers (MRDs) is significant for enhancing the design efficiency of the control algorithm. However, some existing theoretical models face limitations in characterizing MRD damping characteristics simultaneously in terms of nonlinear detail characterization and adaptability to variable working conditions. Therefore, this paper proposed the Composite Double-Boltzmann (CDB) model combining the Double-Boltzmann (DB) function widely used in the field of biology and chemistry for its strong nonlinear characterization capability. Utilizing this model to fit the sinusoidal vibration testing data of the MRD prototype under variable combination working conditions, obtaining quantitative relationships between the undetermined parameters in the CDB model and the excitation current, vibration frequency, and amplitude to enable the model to address both the nonlinear details characterization of MRDs and adaptability to variable working conditions. Subsequently, the validity of the quantitative relationships were verified by comparing the calculated parameter values using the quantitative relationships with the original accurate parameter values. In order to verify the validity of the CDB model, extensive unknown working condition vibration tests were conducted on the MRD prototype under variable excitation currents, vibration frequencies, amplitudes and random excitation working conditions, employing the CDB and Tanh models to predict the damping characteristics, to compare to demonstrate the CDB model’s capability of adapting to variable working conditions while accurately characterizing the nonlinear details of MRD damping characteristics.

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Section: Proposed Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%