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An algorithm for estimation of vehicle yaw rate and side slip angle using steering wheel angle, wheel speed, and lateral acceleration sensors is proposed. It is intended for application in vehicle stability enhancement systems, which use controlled brakes or steering. The algorithm first generates two initial estimates of yaw rate from wheel speeds and from lateral acceleration. A new estimate is subsequently calculated as a weighted average of the two initial ones, with the weights proportional to confidence levels in each estimate. This preliminary estimate is fed into a closed loop nonlinear observer, which generates the final estimate of yaw rate along with estimates of lateral velocity and side slip angle. Parameters of the observer depend on the estimated surface coefficient of adhesion, thus providing adaptation to changes in road surface coefficient of adhesion.

In this paper a simple yet insightful model to predict vehicle propensity to rollover is proposed, which includes the effects of suspension and tire compliance. The model uses only a few parameters, usually known at the design stage. The lateral accelerations at the rollover threshold predicted by the model are compared to the results of simulations, in which vehicles with the same static stability factor, but different suspension characteristics and payloads are subjected to roll-inducing handling maneuvers. The results of simulations correlate well with the predictions based on the proposed model. Design recommendations for passive suspensions, which would increase rollover stability are discussed.