This research is an investigation into the identification of vehicle suspension systems from measured operational data. Methods of identifying unknown parameter values in dynamic models, from experimental data, are of considerable interest in practice. Much of the focus has been on the identification of mechanical systems when both force and response data are obtainable. In recent years a number of researchers have turned their focus to the identification of mechanical systems in the absence of a measured input force. This work presents a combined time and frequency domain approach to the identification of vehicle suspension parameters using operational measurements. An end– to–end approach is taken to the problem which involves a combination of focused experimental design, well established force–response testing methods and vehicle suspension experimental testing and simulation. A quarter car suspension test rig is designed and built to facilitate experimental suspension system testing. A novel shock absorber force measurement set–up is developed allowing the measurement of shock absorber force under both isolated and operational testing conditions. The quarter car rig is first disassembled and its major components identified in isolation using traditional force–response testing methods. This forms the basis for the development of an accurate nonlinear simulation of the quarter car test rig. A comprehensive understanding of the quarter car experimental test rig dynamics is obtained before operational identification is implemented. This provides a means of validating the suspension parameters obtained using operational testing methods. A new approach to the operational identification of suspension system parameters is developed. The approach is first developed under controlled simulated conditions before being applied to the operational identification of the quarter car experimental test rig. A combination of time and frequency domain methods are used to extract sprung mass, linear stiffness and nonlinear damping model parameters from the quarter car experimental test rig. Component parameters identified under operational conditions show excellent agreement with those identified under isolated laboratory conditions.