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Estimation of vehicle roll angle, lateral velocity and side slip angle for the purpose of crash sensing is considered. Only roll rate sensor and the sensors readily available in vehicles equipped with ESC (Electronic Stability Control) systems are used in the estimation process. The algorithms are based on kinematic relationships, thus avoiding dependence on vehicle and tire models, which minimizes tuning efforts and sensitivity to parameter variations. The estimate of roll angle is obtained by blending two preliminary estimates, each valid in different conditions, in such a manner that the final estimate continuously favors the more accurate one. The roll angle estimate is used to compensate the gravity component in measured lateral acceleration due to vehicle roll or road bank angle. This facilitates estimation of lateral velocity and side slip angle from fundamental kinematic relationships involving the gravity-compensated lateral acceleration, yaw rate and longitudinal velocity.

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.