The stationary response in terms of the zero-lag covariance of a two Degree of Freedom (DOF) quarter car vehicle model with nonlinear suspension consisting of linear elements and a nonlinear magnetorheological (MR) damper to random road excitation is obtained by the equivalent linearisation method and verified by Monte Carlo simulation. The parameters of the actual fabricated MR damper using an indigenous MR fluid and modelled by the modified Bouc-Wen model are obtained by solution of a multi-objective optimisation problem through a non-dominated sorting genetic algorithm minimising the mean square error between model and experimental results. Copyright © 2008, Inderscience Publishers.

Sujatha Chandramohan

Department of Mechanical Engineering

Ramia Sridaran Prabakar

EQUIVALENT LINEARISATION TECHNIQUE

MODIFIED BOUC-WEN MODEL

Monte Carlo simulation

MULTI-OBJECTIVE OPTIMISATION TECHNIQUE

QUARTER CAR VEHICLE MODEL

TWIN TUBE MR DAMPER

Damping

Image retrieval

Magnetos

Monte Carlo methods

Multiobjective optimization

VEHICLE SUSPENSIONS

Vehicles

Simulators

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

Stationary response of a quarter car vehicle model with magnetorheological damper

International Journal of Vehicle Systems Modelling and Testing

In this paper, control of the stationary response of a half-car model with a magnetorheological (MR) damper moving over a random road is considered. The MR damper is characterized using Bingham and modified Bouc-Wen models whose parameters are determined optimally using a multi-objective optimization technique and nondominated sorting genetic algorithm II. The multi-objective optimization problem is solved by minimizing the difference between the root mean square sprung mass acceleration, the sum of the front and rear suspension strokes and the sum of the front and rear road holding response of the half-car model with the MR damper, and those of an active suspension system based on linear quadratic regulator (LQR) control. The control force of the MR damper suspension is constrained to lie within ±5% of the control force corresponding to the active suspension system based on LQR control. It is observed that the MR damper suspension systems with optimal parameters perform an order of magnitude better than the passive suspension and perform as well as active suspensions with limited state feedback, and closer to the performance of fully active suspensions. In the case of MR damper suspensions, the vehicle response statistics are obtained using the equivalent linearization method and verified by Monte Carlo simulation. © The Author(s) 2014.

JVC/Journal of Vibration and Control

Response of a half-car model with optimal magnetorheological damper parameters

The control of the stationary response of a half car vehicle model moving with a constant velocity over a rough road with magnetorheological (MR) dampers is considered. The MR damper is modelled by the modified Bouc-Wen model. The MR damper parameters adopted in the vehicle model correspond to an actual fabricated damper and are determined so that the MR damper model characteristics match with experimental characteristics. The random road excitation is considered as the output of a first-order linear shaping filter to white noise excitation. The control and response statistics of the nonlinear vehicle model with MR damper are obtained using the equivalent linearization method in an iterative manner and the results are verified by Monte-Carlo simulation. The MR damper performance is sought to be improved by suitable choice of input currents to the levels of performance of an active suspension based on H∞ control without and with preview by a mean square equivalence of respective control forces. The H∞ optimal control with preview minimizes a performance index which is a weighted sum of vehicle performance measures such as sprung mass acceleration, pitch acceleration, front and rear suspension strokes, road holding and control forces with the weights obtained by solving a multi-objective optimization problem using a non-dominated sorting genetic algorithm II (NSGA II). © 2009 Elsevier Ltd. All rights reserved.

Journal of Sound and Vibration

Optimal semi-active preview control response of a half car vehicle model with magnetorheological damper

Volume 32, Number 2, April 2005

Multi-objective Evolutionary Optimisation for Product Design and Manufacturing

Multi-objective Optimisation Using Evolutionary Algorithms: An Introduction

Journal of Vibration and Control

Semi-active Vibration Control Schemes for Suspension Systems Using Magnetorheological Dampers

Smart Materials and Structures

An innovative magnetorheological damper for automotive suspension: from design to experimental characterization

Journal	International Journal of Vehicle Systems Modelling and Testing
ISSN	17456436
Open Access	No