Road profile identification using estimation techniques: comparison between independent component analysis and Kalman filter

Abstract

This paper focuses on the identification of the road profile disturbance acting on vehicles. Vehicles are subjected to many kinds of excitation sources such as road profile irregularities which constitute a major area of interest when designing suspension systems. Indeed, the determination of the road profile is important for passive suspension design on the one hand and for determining an appropriate control law for active suspensions on the other. Direct measurements techniques of the road profile are expensive so solutions based on estimation theory are needed. The objective of this study is to characterize the road excitation using the Independent Component Analysis (ICA). This proposed method can reconstruct original excitation sources by using physically measurable signals of the system under study. Here, road disturbances estimation is considered as output sources and are identified from the dynamic responses of the vehicle. These responses can be measured via sensors or numerically computed. In our case they are numerically simulated using Newmark and considering different types of road profiles. The obtained results are validated using a comparison with Kalman filtering and the robustness of the ICA is confirmed via a parametric study.