Estimation of road profile variability from measured vehicle responses. Issue 5 (3rd May 2016)

• Record Type: Journal Article
• Authors: Fauriat, W.; Mattrand, C.; Gayton, N.; Beakou, A.; Cembrzynski, T.
• Is Part Of: Vehicle system dynamics. Volume 54:Issue 5(2016:May)
• Page Start: 585
• Page End: 605
• Publication Date: 2016-05-03
• Subjects: Road roughness -- inverse problems -- Kalman filtering -- load variability -- durability; Motor vehicles -- Dynamics -- Periodicals; Electronic journals; 629.231
• DOI: 10.1080/00423114.2016.1145243
• Languages: English
• ISSNs: 0042-3114

Abstract

ABSTRACT: When assessing the statistical variability of fatigue loads acting throughout the life of a vehicle, the question of the variability of road roughness naturally arises, as both quantities are strongly related. For car manufacturers, gathering information on the environment in which vehicles evolve is a long and costly but necessary process to adapt their products to durability requirements. In the present paper, a data processing algorithm is proposed in order to estimate the road profiles covered by a given vehicle, from the dynamic responses measured on this vehicle. The algorithm based on Kalman filtering theory aims at solving a so-called inverse problem, in a stochastic framework. It is validated using experimental data obtained from simulations and real measurements. The proposed method is subsequently applied to extract valuable statistical information on road roughness from an existing load characterisation campaign carried out by Renault within one of its markets.