Research On Vehicle Longitudinal Control Strategy Based On Integrated Braking System

The development of braking system has never stopped in the history of automobile for hundreds of years.With the continuous intelligence of the automobile,the reliability and safety of the braking system are becoming increasingly strict,and the highly integrated braking system has become a new development trend.Compared with the traditional vacuum booster,the integrated braking system has a faster pressure build-up speed,and realizes the complete decoupling of the driver’s pedal force and brake pressure,which can meet the functions of active braking,compound braking.The integrated braking system supports various driving assistance functions such as adaptive cruise control and automatic emergency braking,which are inseparable from the longitudinal control of the vehicles.Based on the integrated braking system,designing a reasonable longitudinal control strategy will better meet the needs of driving assistance functions and improve the safety of vehicle driving.Based on the university-enterprise cooperation project "IBC Integrated Braking Control Algorithm Development",this paper studies the integrated braking system and pressure control strategy,and researches the layered longitudinal control strategy based on the integrated braking system,including the upper longitudinal vehicle following control and the lower longitudinal motion control.The main research contents of this paper are as follows:(1)Integrated braking system modeling and active pressure control.Firstly,the structure and working principle of three 1-Box schemes of the integrated braking system are analyzed and compared.Combined with the actual situation of the research group,the configuration scheme of the integrated braking system selected in this paper is determined.Then,the integrated braking system is mathematically modeled,including permanent magnet synchronous motor modeling,deceleration transmission mechanism modeling and hydraulic system modeling,and the established model is verified by simulation.Finally,an active pressure control strategy including pressure loop control and servo three closed-loop control is designed,in which the pressure loop adopts the structure of P-V characteristic feedforward and PI feedback,and the servo three closed-loop includes position loop,speed loop and current loop.The active pressure control strategy is verified by experiment.(2)Longitudinal vehicle following control strategy based on model predictive control.Firstly,aiming at the safe distance of following vehicles,a variable headway strategy considering the movement trend of the preceding vehicle is proposed,and its convergence is proved.Secondly,according to the relative motion states of the front and rear vehicles,a longitudinal kinematic model considering the acceleration disturbance of the front vehicle is designed.Then,based on the model predictive control theory,a longitudinal control algorithm is designed that considers multiple optimization objectives such as safety,vehicle following,comfort and economy.By designing an objective function and introducing an exponential decay function as a reference trajectory,it is converted into a quadratic optimization problem to solve to obtain the expected acceleration in the following state.Finally,based on the fuzzy control theory,a weight coefficient adjustment strategy is designed to adjust the weight coefficients of the objective function such as vehicle distance,vehicle speed difference and acceleration in real time to adapt to more complex traffic scenarios.(3)Vehicle longitudinal motion control strategy based on parameter estimation.Firstly,the longitudinal dynamics of the vehicle is modeled,and the effects of rolling resistance,air resistance,slope resistance and acceleration resistance on vehicle running are analyzed.Secondly,based on the longitudinal dynamics of the vehicle,the recursive least square method was used to fit the acceleration.Based on the fitting results,the benchmark acceleration curve was further obtained.The transition region was set on the benchmark acceleration curve,and the driving brake switching strategy was designed.Then,in order to realize the expected acceleration to the expected longitudinal force conversion,a feedforward and feedback control structure is designed.The feedforward control is based on vehicle dynamics,and the road slope is estimated in real time by extended Kalman filter algorithm.The feedback control part adopts incremental PID control structure.Finally,the inverse dynamics model of driving and braking is established to convert the desired longitudinal force into the target drive torque or brake pressure.(4)Longitudinal control integrated simulation and experimental verification.First,this chapter builds a simulation platform based on MATLAB/Simulink and CarSim,and conducts integrated simulation verification of the longitudinal control strategy under different working conditions.The results show that the algorithm not only has good car following and safety,but also has certain economy and comfort.Then,based on the dSPACE rapid prototyping tool and real-time simulation tool,a hardware-in-the-loop experimental platform including the integrated braking system is built,and the underlying longitudinal motion control algorithm is experimentally verified.The results show that the algorithm has a good control effect.Finally,the real vehicle platform is modified based on the integrated braking system,and the longitudinal motion control algorithm is experimentally verified on the real vehicle platform,which further verifies the effectiveness of the algorithm.