Research On Vehicle Adaptive Cruise Control Method Based On Fuzzy MPC

As a new vehicle assistant driving system,adaptive cruise control(ACC)system can not only reduce the driver's burden,reduce the incidence of traffic accidents,but also effectively improve the safety of vehicle driving.In order to further improve the driving comfort and fuel economy of ACC system,this paper mainly studies the following aspects:(1)The whole control structure of ACC system is studied and analyzed.ACC system is divided into upper and lower control modes to solve the problem of system instability caused by direct control.In order to adapt to the complex traffic scene,the traditional variable headway strategy introduces the relative speed of two vehicles,so that the following distance can change with the change of the speed of the vehicle and the speed of the vehicle in front,and its convergence stability is proved by theory.(2)The reverse engine model and the reverse brake model of the vehicle are established,and the driving/braking switch strategy is formulated.Based on the proportional integral differential(PID)control,the feed forward and feedback lower controller is designed.The results show that the lower controller can track the upper desired acceleration quickly and accurately,and the control effect is good.(3)Based on model predictive control theory(MPC),a multi-objective ACC system upper controller is designed.Firstly,a state space model reflecting the longitudinal dynamic characteristics of the two vehicles is established,and the safety,following,driving comfort and fuel economy in the process of vehicle driving are analyzed as the optimization performance index and system constraints of the objective function.Secondly,the feasible solution domain is extended by introducing relaxation vector factor to soften the system constraints In order to adapt to the complex traffic conditions,the fuzzy control strategy is used to design the variable weight coefficient to update the weight coefficient online.Finally,through MATLAB simulation,it is found that the improved MPC algorithm not only ensures its safety and following performance,but also effectively improves the driving comfort and fuel economy in the process of driving compared with the traditional MPC.(4)The longitudinal dynamic model of vehicle is built based on CarSim software.The upper controller and lower controller model of ACC system are built in Matlab/Simulink environment.The CarSim vehicle model is embedded in the form of s function in Matlab/Simulink environment to complete the construction of joint simulation platform.The simulation experiments are carried out in five typical working conditions,and it is found that the vehicle can follow the front vehicle stably in different working conditions,and multiple control objectives such as safety and comfort can be taken into account in the process of vehicle driving,and the state quantity of vehicle driving is within a reasonable range.The results show that the control method can adapt to complex traffic conditions.