A method for modeling Electro-Rheological (ER) dampers is proposed. It consists in two sequential steps: Characterization and Customization. Both steps are. This study presents nondimensional analysis of an Eyring constitutive model to describe the field-dependent behavior of an electrorheological. This paper presents the design, analysis, testing and modeling of an electrorheological (ER) fluid damper developed for vibration and seismic.
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This is result of the actuation and manipulation signals used in that experiment, because the DSFS signal captures best the dynamical behavior of the damper in its whole range of operation while electrorhfological RP only explores a limited zone. This model predicts the nonlinear behavior of the ER damper in the preyield and postyield zones but depends on physical properties of the damper and it is sensitive to the initial conditions, [ 10 ].
The ER damper force can be represented by two components: Figure 12 presents a comparison of the density plots of experiment. This combination, at high frequencies, introduces high variability in the camper variability induces more hysteresis in the measured force.
Finally, the customized model, Figure 12 dgenerates a similar density of experimental data for extension forces and slightly larger compression forces. Abstract Funding Institution Comments.
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However, this model was unable to describe the stick-slip phenomenon, Figures 8 a and 9 ain the FV diagrams; they are the force peaks around 0. View at Google Scholar R. The experimental setup, Figure 2 aconsists of three modules: The performance indexes for all the experiments customized and full models are shown in Table 3.
The RP smooth highway is the most common road for commercial vehicles. Furthermore, the yield stress is field dependent; it increases as the electric field does.
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The ER damper models are also qualitatively compared using density plots in order to identify if these models predict correctly the distribution of the experimental data. The DoE consists of a combination of displacement and actuation sequences i. In contrast with the experimental data, in the Eyring-plastic model the higher density appears with large forces and exhibits a saturation, Figure 12 g ; hence the Eyring-plastic model produces smaller forces with large dqmper than the real epectrorheological.
In the experimental FV diagram, Figure 12 athe higher density of data appears with small compression forces while in the Choi model, Figure 12 bthe higher density appears with larger forces; hence, this model represents a stiffer damping force than the real damper at low velocities. After long inactive periods settling of the suspension occurs which results to loss of the fluid ER activity. The results were quantitatively compared with two well-known Electrorheplogical damper models: View at Google Scholar S.
Table 3 shows that the performance indices of the customized model are very similar to the full model; for both models the ESR indices are low.
A series of displacement sequences and actuation signals were used to capture the static and dynamic relations between velocity, displacement, actuation signal, and the damper force [ 14 ].
The ER fluid, when exposed to the electric field, behaves as a viscoelastic material, known as a Bingham plastic. The Choi parametric model, Figures 11 a and 11 bdoes not estimate correctly the hysteresis and nonlinearities of the damping force, but the levels of force caused by the changes in the manipulation signal are notorious. Name University of Notre Dame. This change on the damper needs to be controlled, to achieve the desired objectives. A model with the same shape and density distribution to the experimental data is required in order to compute a right manipulation to achieve a desired force.
Characteristic diagrams of the ER damper passive behavior. The characterization procedure was applied to the damper, using experimentTable 2. Then the general model is customized. Also, when compared with well-known models, the results have better performance, an average of Afterwards the SA diagram, Figure 5 cis analyzed using 1.
In the postyield region the force is almost independent of the piston velocity, but in the preyield zone the force is velocity dependent. This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The electrorheolotical model, Figures 11 e and 11 fshows the best modeling performance since the nonlinearities added by the manipulation signal are well described and the low and high damping forces are correctly identified. The authors declare that electeorheological is no conflict of interests regarding the publication of this paper. For the PWM duty cycle, the Stepped inCrements SC signal, Figure 3 ais used to study the effect of the actuation signal under different displacements sequences.
The resulting model is light enough to be implemented in an embedded system. The SA damper force, Figure 7presents a sigmoid behavior without significant hysteresis. The advantage of this model is the few number of constants but it does not seem to be very accurate; also it needs a set of constants for every field manipulation interval.
There are many mathematical models to reproduce the characteristic behavior of the ER damper. The method was experimentally validated with a commercial damper. Most of the models are dependent on internal physical properties of the damper, ER fluid, and its design; this makes the implementation of these models very restricted i. In these equations, the use of the tanh function is replaced with the so-called squash function: In order to analyze the effectiveness of the customized model, a comparative analysis with other two well-known models was carried out: Increased clock period signal ICPSFigure 3 band pseudorandom electrorheologicla signal PRBSFigure 3 csequences are used to analyze the damper transient response under actuation signal variations.