Development of an analytical multi-variable steady-state vehicle stability model for heavy road vehicles

Vihar Malviya, Rakesh Mishra

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


Road vehicles tend to be more vulnerable to accidents especially at motorway speeds. Commercial vehicles in particular are more prone to overturning accidents due to adverse conditions like cross winds and abrupt acceleration/braking conditions. Thus, it is essential to investigate vehicle stability under various conditions of manoeuvring, cross winds and on inclined ground planes. This work presents a methodology of determining rollover stability of road vehicles. A wide range of destabilising factors have been investigated. These include the longitudinal and lateral inclination of the ground plane, road surface curvature; acceleration and braking effects; centrifugal cornering effects as well as the aerodynamic effects of cross winds at various wind speeds and angles of attack. These destabilising factors have been described in detail, with a description of associated variables that influence vehicle stability. A four-equation model has been proposed to evaluate the vertical ground reaction forces at each wheel, based on the force-moment system created by the above-mentioned destabilising factors. A parametric study is carried out to investigate the influence of various parameters on the overall stability of the vehicle. It is noted that higher magnitude of wind velocities cause a reduction in the maximum safe vehicle speeds. Moreover, for high magnitude of wind speeds, it is also seen that for some vehicles wind angles as low as 5° can cause overturning accidents, even at low vehicles speeds of 15. m/s (33.5. mile/h, 54. km/h). Additionally, the influence of acceleration, braking, turning and road surface curvature has been investigated. An increase in vehicle mass is seen to be beneficial as it increases the maximum safe vehicle speeds for a given set of wind conditions, thus making the vehicle more stable. The proposed vehicle stability model can predict stability characteristics of a wide range of vehicle types.

Original languageEnglish
Pages (from-to)4756-4777
Number of pages22
JournalApplied Mathematical Modelling
Issue number19-20
Early online date1 Apr 2014
Publication statusPublished - 1 Oct 2014


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