Citation

Steve Clovis MN, Claude Valery NA, Jean Chills A, Jean-Maurice NY. Int. J. Transp. Sci. Technol. 2023; 12(4): 907-924.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.ijtst.2022.09.003

PMID

unavailable

Abstract

This paper supports the implementation of a braking efficiency estimator of urban vehicle on rural roads, based on analytical and numerical approach. A statistical study is defined by the Association Road Managers and Partners (AGEPAR) estimates the rate of unpaved roads in Africa around 72%, which approximately 90% of passengers and goods transport that generally doesn't respect loading standards. This is a major reason for increase traffic accidents in these countries. Hence the need to define vehicle speed limitations that takes in vehicle parameters and irregularities road. This can be done by defining a predicting model of dynamic behaviour for small vehicles, which constitute the majority of African vehicle fleet. To achieve this, we numerically solve the longitudinal dynamic equations of a vehicle body combine with front and rear axles on a road which has irregularities, opposed to existing models and Field data that are defined on surface roads which have little or no irregularities. The input parameters of the model are the initial vehicle speed, the road profile, inclination angle of road, peak wheel cylinder, wheelbase, centre of gravity height, rising time, brake pads contact area, final drive gear ratio, gearbox gear ratio, moment of inertia of engine, slip ratio, vehicle weight, moment of inertia at on axle and dynamic tyre radius which are assumed similarly and the braking system which is a disc braking system. The suspension is assumed identical and rigid since our study focuses on longitudinal and not vertical dynamics. The results produced by our modelling on paved and unpaved roads are compared with those obtained experimentally by J. R. Choa and the unpaved road data we obtained. The relative differences in braking times are respectively 6.5% and 3.1%. For the stopping distance, these relative differences are 11.5% and 11.9%.

Language: en

Keywords

Braking distance; Braking time; Random profile; Rolling resistance; Unpaved road