Vehicle Stability Control Based On Identification Of Stability Boundary Under Extreme Conditions

Recently,with the increasing number of vehicles,the problem of safe travel has become serious.Frequent road accidents have become a principal threat of human life and possessions’ security.As a significant research and evolution orientation of the field of automobiles,automotive active safety technology plays a significant role in improving vehicle driving stability and decreasing traffic accidents.Especially in extreme conditions,it is likely to induce unpredictable consequences due to the decline of maneuverability and stability.Relevant researches have shown that almost half of traffic accidents are related to vehicle tail drift when the vehicle travels at medium and high speed.The proportion of accidents caused by sideslip increases with the increase of vehicle speed and the decrease of road adhesion coefficient.Compared with tail drift,the rollover of the vehicle has always been a more dangerous situation in the field of transportation,and the damage degree of the rollover problem is second only to the car collision problem.Thence,to enhance the vehicle safety and stability during high-speed turning on low-adhesion and high-adhesion roads,the hub-driven electric vehicle in this paper is regarded as the study object to research the stability control of the vehicle under extreme conditions.First,a stable boundary identification method combining the current vehicle driving state and road information is raised.A vehicle model including the lateral,longitudinal and vertical properties of the vehicle and the Fiala nonlinear tire model are built,and the effect of the vertical load on the tire cornering characteristics is taken into account simultaneously.The complex nonlinear vehicle model is linearized by the Taylor expansion and local linearization method,and the judgment conditions for vehicle stability and controllability are acquired.Then the stability boundary about the vehicle state is obtained.The influence of changes in parameters such as vehicle state and road condition on the identified stable region is explored.Then,a vehicle lateral stability control strategy based on dynamic constraints is proposed to improve the vehicle driving stability during high-speed driving or steering on low-adhesion roads.A dynamics model is built to describe the vehicle lateral and yaw motion,then a lateral stability controller based on the model to predict future dynamics is designed to track the expected response signal of the vehicle lateral motion.The identified stable boundaries and regions are used as dynamic state constraints to optimize the additional yaw moment.The effects of fixed state constraints,phase plane constraints and dynamic constraints on vehicle lateral stability control are compared.Finally,a rollover prevention controller based on dynamic weights is designed to prevent the vehicle from rolling over when turning at high speed on high-adhesion roads.A linear switching tire model is established,a dynamic model that can describe the lateral,yaw,roll motion and wheel rotation of the vehicle is established.The control area is divided into a stable,critically stable and unstable area based on the roll index related to the actual vehicle state and the identified stability boundary.Through the realtime changes of weight coefficients and constraint values,various control requirements in different regions can be dynamically adjusted.The interior-point method on account of C language is applied to deal with the optimization problem again.The proposed approach can effectively reduce the risk of vehicle roll or even rollover under extreme working conditions by the hardware-in-the-loop experiment,ensuring vehicle stability.