Critical Stability Control And Adaptive Dynamic Programming Of Vehicle Drift Dynamics

Drifting is a kind of side-sliding movement of a vehicle when the rear wheels are saturated.It usually appears in some rally fields or in car stunts.The current vehicle dynamics control strategy is to suppress the rear wheel as much as possible to avoid drifting,because it is regarded as an unstable state.When extreme conditions such as vehicle collision or sudden reduction in road friction coefficient occur,the vehicle has already slipped.Using drift stability to control the vehicle can stabilize the vehicle more quickly than strategies to suppress it,and also it is more helpful to avoid loss of control or danger due to secondary collision.Actually,The study and control of the drift stability dynamics has great significance for improving the stability boundary of the vehicle,which can stabilize the vehicle in more scenarios and improve safety.This article relies on the National Natural Science Foundation’s Major Project "Integrated Coordinated Control of Automobile Movements under Extreme Conditions"(No.61790564).The balance point of the vehicle’s drift dynamic was analyzed,and the joint controller which consisted of a sliding mode controller and an adaptive dynamic programming controller was designed.The main contents are as follows:1.A 2DOF nonlinear vehicle model and a pure slip steady-state Uni Tire model were established,and the parameters in the tire force formula were identified based on the slip test data.2.The equilibrium point based on the 2DOF vehicle was calculated,and phase-plane on the state space composed of sideslip angle and yaw rate was analyzed to find the stable equilibrium points and unstable equilibrium points,and according to the characteristics of the drifting,identified the drift equilibrium points as the unstable equilibrium points.3.A sliding mode controller was designed,which takes the calculated drift balance point as the controlling target.And the stability of the controller was proved.The simulation in MATLAB / Simulink realized the entire process from the initial straight driving situation to a given drift equilibrium.after that,a step disturbance was applied,and the states of vehicle remained stable.4.Based on the adaptive dynamic programming method,the Q-value iterative algorithm with a parameter approximator was used to calculate the optimal control strategy function of vehicle drift dynamics.A joint switching controller is designed which is combined with a the sliding mode controller and an ADP controller.In the joint controller,the sliding mode controller will be adopted when the state of vehicle is significantly different from the drift equilibrium state,and it will be switched to the adaptive dynamic programming optimal controller when the vehicle state approaches the drift equilibrium point nearly.The simulation results show that the convergence time of the joint controller is shorter than that of the single sliding mode controller,and after the disturbance is applied,the ADP controller can make the vehicle to the near drift equilibrium point.The controller also has an ability to adapt to changes in friction coefficient,which means that it can provide vehicle safety when road conditions suddenly change.