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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.

The development and preliminary testing of an algorithm that detects impending rollover is described. The algorithm is intended for use in conjunction with active chassis systems to prevent some types of rollovers. Several methods of estimating roll angle and roll rate from physical principles using available sensors are presented. Advantages and drawbacks of each method and their ranges of reliable operations are discussed. An approach using a closed-loop adaptive observer for estimating roll angle and roll rate of vehicle body with respect to the road is proposed. Performance and robustness of the estimator are evaluated through numerical simulations and vehicle testing, using various scenarios, including maneuver induced and road induced body roll. The estimates are shown to be consistently superior to those obtained from other methods. A roll index is proposed, which uses the estimated roll angle and other signals to indicate rollover danger.

The purpose of this paper is to evaluate through simulations the effects of active chassis systems on vehicle propensity to rollover caused by aggressive handling maneuvers. A 16 degree-of-freedom computer model of a full vehicle is used for this purpose. It includes models of active chassis systems and the associated control algorithms, and allows for simulation of vehicle dynamic behavior under large roll angles. The controllable chassis systems considered in this investigation are active rear steer, brake based vehicle stability enhancement system and active anti-roll bar. The maneuvers used in simulation are the double lane change and the fishhook maneuvers with increasing steering amplitudes. The vehicle represents a midsize SUV with a marginal static stability factor of 1.09 and aggressive tires. The results of simulations demonstrate that the uncontrolled vehicle rolls over in both maneuvers when the steering angle is sufficiently large.

In dynamic rollover tests many vehicles experience sustained body roll oscillations during a portion of road edge recovery maneuver, in which constant steering angle is maintained. In this paper, qualitative explanation of this phenomenon is given and it is analyzed using simplified models. It is found that the primary root cause of these oscillations is coupling occurring between the vehicle roll, heave and subsequently yaw modes resulting from suspension jacking forces. These forces cause vertical (heave) motions of vehicle body, which in turn affect tire normal and subsequently lateral forces, influencing yaw response of vehicle. As a result, sustained roll, heave and yaw oscillations occur during essentially a steady-state portion of maneuver. Analysis and simulations are used to assess the influence of several chassis characteristics on the self-excited oscillations. The results provide important insights, which may influence suspension design.

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.

Undesirable low frequency vibrations experienced on vehicles equipped with semi-active suspension are observed: when road inputs have significant repetitive component, when there are large control gains in the suspension control algorithm, and when the velocities of the body are estimated by filtering the measured suspension deflections. Stability analysis performed on simple vehicle models demonstrates that interaction between the dynamics of the vehicle and the estimation filter is the root cause of the problem. A vehicle with an active suspension becomes unstable while a vehicle with a semi-active suspension exhibits limit cycles when the above mentioned conditions are present. A solution is proposed in which the control gains are adaptively changed depending on the frequency content of the road spectrum.

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.