State-of-the-art of terrain profile characterisation models

In the automotive industry, proper mathematical models of terrain profiles provide a compact representation of excitations to vehicle simulations. Vehicle design is aided by accurately representing the excitation and thereby improving the accuracy of the resulting suspension loading conditions, vehicle response and fatigue life predictions. Terrain data acquisition methods are reviewed to provide a framework for the scope of applicability of these models. Several roughness indices are reviewed that identify and classify the type and general severity of terrain, including their measurement procedures, algorithms, applicability and limitations are discussed and compared. The statistical properties of the terrain and various modelling methods are reviewed, including Power Spectral Density (PSD), Markov Chains, Autoregressive Models, Wavelets and Hilbert-Huang Transformation (HHT). The advantages and disadvantages of these models are discussed based on the model's capability to capture the stochastic nature of terrain profiles. As a result of this review, the implications of the selection of a particular terrain model can be evaluated with respect to particular applications.