With the development of intelligent driving technology,the research on active safety of intelligent vehicles has become an important research direction in vehicle engineering.Intelligent vehicles achieve tracking of the desired path through automatic steering,but the vehicle will experience roll motion during the steering process.If the roll amplitude is too large,it will cause roll behavior.Ensuring the accuracy of trajectory tracking and ensuring the vehicle has a certain anti roll ability is currently a problem that needs to be solved.By effectively improving the vehicle’s anti roll performance and roll limit through anti roll methods,intelligent vehicles can travel along the expected path,and can adjust the vehicle’s roll amplitude in real-time based on the trajectory tracking of the front wheel angle,thus completing the task of safe,efficient,and stable driving of the vehicle.The control of vehicle roll mainly focuses on active roll devices and control algorithms,such as differential braking,active steering,active lateral stabilizer bars,active suspension,and integrated control methods.The suspension system alleviates the impact load caused by road undulation on the entire system by transferring the interaction force between the tires and the vehicle body,while the main function of the active lateral stabilizer bar system is to improve the vehicle’s anti roll ability and prevent the vehicle from rolling over during the steering process.This article is based on the active lateral stabilizer bar anti roll control strategy,and designs a vehicle roll stability control strategy for intelligent vehicles during trajectory tracking.Firstly,a three degree of freedom vehicle dynamics model with a passive stabilizer bar is established,and a double vane swing hydraulic motor is used as the actuator,and a mathematical model is built in Simulink software.In order to ensure the accuracy of the three degree of freedom vehicle dynamics mathematical model,this chapter uses Carsim software to verify the model,so as to ensure the accuracy of the three degree of freedom vehicle model.Secondly,because it is difficult to measure the body roll angle,the unscented Kalman filter(UKF)state observer is used to estimate the body roll angle in real time,and the state parameters are input into the active stabilizer bar.The active stabilizer bar is designed with a sliding mode variable structure controller.The actuator uses a three closed-loop proportional integral differential(PID)controller.Particle swarm optimization(PSO)algorithm is used to optimize the sliding mode variable structure controller and the three closed-loop PID controller parameters,Simulation verification shows that the control algorithm has strong adaptability and stability,can effectively follow the target value,reduce the vehicle roll angle,achieve the goal of antiroll,and improve the driving performance of the vehicle.Then,a trajectory tracking controller based on model predictive control(MPC)is designed,and joint simulation is conducted in the Simulink environment to analyze the accuracy and stability of MPC trajectory tracking control under dual lane changing and serpentine conditions at different vehicle speeds.Finally,the intelligent vehicle trajectory tracking is integrated with the active lateral stabilizer system for control.The target roll angle and target yaw rate are obtained based on the vehicle roll angle reference model and a two degree of freedom model,and a PID controller is designed to control the distribution coefficient.The front and rear torque distribution is changed in real-time based on the vehicle’s driving status,and the fractional order particle swarm optimization algorithm(FO-PSO)is used to optimize the control parameters as a whole,the impact of this control method on vehicle roll was studied under serpentine and double lane changing conditions.Simulation results show that the integrated control algorithm can effectively reduce roll angle and suppress vehicle roll motion. |