Please use this identifier to cite or link to this item: https://idr.nitk.ac.in/jspui/handle/123456789/12812
Title: Performance analysis of a semi-active suspension system using coupled CFD-FEA based non-parametric modeling of low capacity shear mode monotube MR damper
Authors: Tharehalli, Mata, G.
Kumar, H.
Mahalingam, A.
Issue Date: 2019
Citation: Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2019, Vol.233, 5, pp.1214-1231
Abstract: In this work, an approach for formulation of a non-parametric-based polynomial representative model of magnetorheological damper through coupled computational fluid dynamics and finite element analysis is presented. Using this, the performance of a quarter car suspension subjected to random road excitation is estimated. Initially, prepared MR fluid is characterized to obtain a relationship between the field-dependent shear stress and magnetic flux density. The amount of magnetic flux induced in the shear gap of magnetorheological damper is computed using finite element analysis. The computed magnetic field is used in the computational fluid dynamic analysis to calculate the maximum force induced under specified frequency, displacement and applied current using ANSYS CFX software. Experiments have been conducted to verify the credibility of the results obtained from computational analysis, and a comparative study has been made. From the comparison, it was found that a good agreement exists between experimental and computed results. Furthermore, the influence of fluid flow gap length and frequency on the induced force of the damper is investigated using the computational methods (finite element analysis and computational fluid dynamic) for various values. This proposed approach would serve in the preliminary design for estimation of magnetorheological damper dynamic performance in semi-active suspensions computationally prior to experimental analysis. IMechE 2018.
URI: http://idr.nitk.ac.in/jspui/handle/123456789/12812
Appears in Collections:1. Journal Articles

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