Application of Multi-Input Uncorrelated Periodic Signals for Identification of Active Suspension System

Abstract

Active suspension system has been widely used to improve ride comfort in passenger cars by adjusting the force between the tyre and the vehicle body such that the effect of the rough road surfaces will be minimally felt by the passengers. Control algorithms for active suspension are frequently designed using the well-known quarter-car model, which is a linear approximation of the system. In this paper, multi-input uncorrelated periodic signals are applied on a laboratory-scale active suspension system. The signals incorporate harmonic suppression allowing more accurate estimation of the frequency response functions and quantification of nonlinearities and noise. The results reveal significant amount of nonlinearities, which should be taken into account during controller design.