Classification Scheme for Random Longitudinal Road Unevenness Considering Road Waviness and Vehicle Response | Zendy

Oldřich Kropáč | Zendy; Peter Múčka | Zendy

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Classification Scheme for Random Longitudinal Road Unevenness Considering Road Waviness and Vehicle Response

Author(s) -

Oldřich Kropáč,

Peter Múčka

Publication year - 2009

Publication title -

shock and vibration

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.418

H-Index - 45

eISSN - 1875-9203

pISSN - 1070-9622

DOI - 10.1155/2009/935858

Subject(s) - waviness , truck , interval (graph theory) , vibration , spectral density , transformation (genetics) , standard deviation , engineering , structural engineering , computer science , mathematics , automotive engineering , statistics , acoustics , mechanical engineering , biochemistry , physics , chemistry , combinatorics , gene

A novel approach to the road unevenness classification based on the power spectral density with consideration of vehicle vibration response and broad interval of road waviness (road elevation PSD slope) is presented. This approach enables transformation of two basic parameters of road profile elevation PSD (unevenness index, C , and waviness, w ) into a single-number indicator C w when using a correction factor K w accounting for w . For the road classification proposal two planar vehicle models (passenger car and truck), ten responses (reflecting ride comfort, dynamic load of road and cargo, ride safety) and three different vehicle velocities have been considered. The minimum of ten estimated vibration response ranges sum for a broad waviness interval typical for real road sections ( w = 1.5 to 3.5) has been used for the correction factor estimation. The introduced unevenness indicator, C w , reflects the vehicle vibration response and seems to be a suitable alternative to the other currently used single-number indicators or as an extension of the road classification according to the ISO 8608: 1995, which is based on constant waviness value, w = 2.

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