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Research On Control Strategy Of Vehicle Emergency Braking System

Posted on:2022-04-07Degree:MasterType:Thesis
Country:ChinaCandidate:T K RongFull Text:PDF
GTID:2492306338478044Subject:Vehicle Engineering
Abstract/Summary:PDF Full Text Request
In recent years,with the rapid development of active safety technology,the safety performance of the vehicle has been greatly improved.As an important part of the active safety technology of the vehicle,AEB(automatic braking)system can alert the driver when the vehicle encounters obstacles in front.When the collision risk is further upgraded and the driver fails to take the braking measures in time,the AEB system will control the vehicle to conduct emergency braking,so as to ensure the safety of the driver and the passenger.Based on the knowledge of vehicle system dynamics,this paper studies the control strategy of automatic emergency braking system by using fuzzy control theory,finite state machine control theory and PID control theory.The control strategy is verified by the combination simulation of CarSim/Simulink.The main research work of this paper is as follows:(1)The overall design of automatic emergency braking system.Based on the control requirements of automatic emergency automatic system,the overall design of AEB system is carried out,including the overall scheme design,the overall structure design and the overall logic design.(2)The vehicle system dynamics model is built,including the vehicle longitudinal dynamics model and the vehicle longitudinal dynamics reverse model.The vehicle dynamics system parameters are configured by CarSim software and the vehicle longitudinal dynamic model is established;the braking pressure model is established based on the vehicle dynamics theory,and the mathematical relationship between the expected acceleration and the braking pressure is obtained.The vehicle longitudinal dynamic reverse model is established in MATLAB/Simulink,and the vehicle system dynamics simulation model is completed.(3)The research on the control strategy of automatic emergency braking system.This chapter analyzes the safety model requirements that AEB system needs to meet when triggering,analyzes the common safety model structure of AEB system,and proposes the control strategy of automatic emergency braking system based on the combination of safe distance time model by layered control.Firstly,according to the lane change of vehicles in the adjacent lane under straight road condition,a danger target discrimination controller is designed based on fuzzy control theory and safety time model,and the determination of dangerous target in front of AEB system is realized.Then,based on the finite state machine control theory,the upper controller of the automatic emergency braking system is designed,which combines the safe distance and the safety time model.The expected acceleration of the vehicle is obtained according to the relative position and speed of the vehicle and the target vehicle.The lower controller of automatic emergency braking system based on PID control is constructed.The expected acceleration obtained by the upper controller is converted into the brake master cylinder pressure of the vehicle,and the real-time follow-up adjustment of the acceleration to the expected acceleration is realized.(4)Based on the typical test conditions of C-NCAP,the control strategy of the automatic emergency braking system designed in this paper is verified by the joint simulation of CarSim and MATLAB/Simulink.The simulation results show that the control strategy can better judge the lane change behavior of vehicles in front of adjacent lanes,and the judgment of dangerous target vehicles is consistent with the expected results;the early warning /classification braking control function can be better realized,and the phase to distance between the two vehicles before and after the brake stops is kept within the specified range,and the effective follow-up of the expected acceleration is realized.
Keywords/Search Tags:automatic emergency braking system, hierarchical control, dangerous target judgment, fuzzy control, safe distance time model, Co-simulation
PDF Full Text Request
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