Title: A general model for inferring terrain surface roughness as a root-mean-square to predict vehicle off-road ride quality

Authors: Phillip J. Durst; Alex Baylot; Burney McKinley; George L. Mason

Addresses: US Army Engineer Research and Development Center, 3909 Halls Ferry Road, Vicksburg, MS 39180, USA ' US Army Engineer Research and Development Center, 3909 Halls Ferry Road, Vicksburg, MS 39180, USA ' US Army Engineer Research and Development Center, 3909 Halls Ferry Road, Vicksburg, MS 39180, USA ' US Army Engineer Research and Development Center, 3909 Halls Ferry Road, Vicksburg, MS 39180, USA

Abstract: Vehicle maximum speed for off-road operations is limited by the absorbed power via vertical acceleration to the driver for a given terrain Root-Mean-Square surface roughness (RMS). RMS calculation requires centimetre-scale terrain elevation data; however, previous work by the authors has shown that RMS can be modelled using a 5-metre terrain profile's Fractal Dimension (FD) and Power Spectral Density (PSD) DC offset. Presented is a study of the effects of surface elevation data resolution on the model. Forty-nine ride courses were down-sampled from 30 centimetre to 0.91, 1.83, 2.74, 3.66, 4.57, 5.49, 6.40, 7.32, and 8.23 metre spacings, and an RMS model at each spacing was generated using linear regression techniques. The effects of data resolution on the RMS model were studied, and a continuous model for RMS as a function of FD and DC offset across elevation data resolutions for up to 7 metre sample spacing was developed. Results of the model's use in predicting off road military vehicle mobility are presented.

Keywords: surface roughness; RMS; root-mean-square; fractal dimension; PSD; power spectral density; off-road performance; ride performance; military vehicles; terrain modelling; terrain characterisation; terrain roughness; off-road vehicles; ride quality; vehicle speed; vehicle mobility.

DOI: 10.1504/IJVD.2014.058481

International Journal of Vehicle Design, 2014 Vol.64 No.2/3/4, pp.137 - 152

Received: 25 Feb 2011
Accepted: 28 Oct 2011

Published online: 31 Dec 2013 *

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