Roll state estimator for rollover mitigation control

Abstract This paper describes a new methodology for designing model-based estimators for detecting impending vehicle rollover. Vehicle roll motions are induced by manoeuvring and road disturbances. An estimator is designed on the basis of a three-degree-of-freedom vehicle manoeuvring model and a four-degree-of-freedom half-car suspension model to obtain good estimates of the vehicle roll angle and roll rate in driving situations in which both manoeuvring and road disturbances affect the vehicle roll motions. The estimator uses existing sensors, such as the steering wheel angle sensor, lateral acceleration sensor, and yaw rate sensor, on a vehicle equipped with an electronic stability control system. Since road disturbance is unknown or very expensive to measure, disturbance-decoupled-observer design technique is used in the design of the estimator. The parameter adaptation algorithm can be used for vehicle mass to improve the accuracy of estimator. The performance of the estimator is evaluated through computer simulations using a validated vehicle simulator. It is shown that, with only the sensor measurements already available, good estimates of the roll angle and roll rate can be obtained using the proposed estimator in driving situations in which both manoeuvring and road disturbances affect the vehicle roll motions. A rollover index that indicates rollover danger has been computed using the measured lateral acceleration and yaw rate, and the estimated roll angle and roll rate. The rollover index computed using the estimated states is shown to be a good measure for the danger of vehicle rollover.