Research On Coordinated Control Of Steering And Braking With Automotive Emergency Avoidance Collision

In view of the emergency conditions that there is a sudden brake of the vehicle ahead or sudden o bstacles appear in front of the vehicle,and the driver cannot take measures timely to avoid a collision while driving on the highway.In this paper,combined with Changzhou science and technology plan a pplication basic research project“Research on coordinated control system of automobile emergency c ollision avoidance active steering and braking”,the key state parameter estimation of the automobile e mergency collision avoidance control system was carried out.The grey neural network was used to st udy the control algorithm for coordinating braking and steering.The active avoidance system that aut omatically taking over the vehicle was realized to complete the emergency avoidance control.Simulat ion experiments,hardware-in-the-loop experiments,and vehicle road test were also carried out under multi working conditions and multi road conditions.Vehicle dynamics models for researching automotive emergency collision avoidance control system were built in this paper including seven degrees of freedom vehicle model,linear two degrees of freedom vehicle model,nonlinear tire model,et al.The models were validated by the co-platform of Carsim and Simulink.The results showed that the models can meet the requirements of emergency collision avoidance control under different driving conditions.In order to estimate the key parameters of vehicle collision avoidance stability control,using the least-squares method,the coefficient of surface adhesion is estimated,a state estimation adaptive filtering algorithm based on Ant Colony Optimization for UKF was proposed.By applying Ant Colony Optimization function,the optimal operation of the covariance matrix of process noise and observation noise was optimized by choosing the objective function.The self-adaptivity,robustness and accuracy of the algorithm were improved.The simulation results suggested that the proposed algorithm was effective enough to meet the requirement of the vehicle stability control.In view of the complex multi vehicles working conditions on the highway,based on the traditional safety distance model,an emergency longitudinal collision avoidance safety distance model and a lateral collision avoidance Lane planning model were established for the complex conditions with two-lane and multi-vehicle.Under the braking condition for collision avoidance,the longitudinal collision avoidance safe distance model was deduced.The five order polynomial was used to carry out the path planning under the steering condition for collision avoidance,and select the path which met the stability requirements as the better path for collision avoidance.Aiming at the optimal collision avoidance mode for emergency,a decision-making method of vehicle collision avoidance mode based on grey theory was proposed.The decision-making method was used to solve the selection problem of collision avoidance mode,which mainly aimed at the coordination avoidance mode of braking and steering.The BP neural network upper controller was developed to coordinate the vehicle braking and steering simultaneously.Through the longitudinal safety distance model and lateral lane changing path,the braking deceleration curve and lateral acceleration curve were obtained.The braking pressure change curve and the front wheel angle change curve were obtained by inverse dynamics modeling,and the PID lower controller was established to perform braking and steering operation.The simulation results showed that,the algorithm has a good control performance that can avoid collision under the emergency condition when meeting the vehicle stability.Aiming at the optimization problem of neural network controller,a genetic algorithm was proposed to optimize the initial weights and threshold of the neural network controller.The yaw rate and sideslip angle of the vehicle were minimized under the premise of successful collision avoidance.The comfort of the vehicle was improved.With the influence of the objective existence of the external environment disturbance that affects the process of collision avoidance,in the process of lane changing,the main factors that affect the vehicle steering were the uncertainty produced by the lateral wind noise.The vehicle was simplified to single input single output model.A H_inf controller was built to suppress the interference factors for its ability to minimize the disturbance affects,which has a strong robustness of making the vehicle track the desired trajectory precisely.At last,based on the former simulations,the hardware-in-the-loop experimental platform of vehicle emergency collision avoidance control system through the co-platform of Labview and Matlab/Simulink was developed.It included a steering motor with a driver,a computer,a monitor,wireless communication module,DP512 core controller,hydraulic brake mechanism and so on.The experimental results show that the controller can identify the real-time vehicle emergency condition and output control voltage.The braking system can quickly and accurately output the brake forces.The braking system and active front wheel steering system can realize a real-time response,the actuators can timely action.The stability index of the horizontal pendulum angular velocity and centroid side-slip angle were in a safe range.The proposed control algorithm had good robustness to obviate the disturbances.