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.
This study assesses the dynamic performance of the semi-active quarter car vehicle under random road conditions through a new approach. The monotube MR damper is modelled using non-parametric method based on the dynamic characteristics obtained from the experiments. This model is used as the variable damper in a semi-active suspension. In order to control the vibration caused under random road excitation, an optimal sliding mode controller (SMC) is utilised. Particle swarm optimisation (PSO) is coupled to identify the parameters of the SMC. Three optimal criteria are used for determining the best sliding mode controller parameters which are later used in estimating the ride comfort and road handling of a semi-active suspension system. A comparison between the SMC, Skyhook, Ground hook and PID controller suggests that the optimal parameters with SMC have better controllability than the PID controller. SMC has also provided better controllability than the PID controller at higher road roughness.
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