| Adaptive cruise control(ACC)plays an important role in easing the burden of driving and improving the road traffic capacity.The comfortability,economic efficiency and safety can be improved by using ACC significantly.At present,ACC products are mostly developed and tested under good road conditions.However,the size of road adhesion coefficient is influenced by road material,weather and other factors.Then,the use of ACC system is not only limited by road conditions,but also can not automatically adjust the vehicle control strategy according to the change of road environment.As a result,ACC system is limited in application.To ensure reliable operation of vehicle under different road conditions,it is necessary to accurately estimate the road adhesion coefficient and form an ACC system for different road adhesion coefficients.Meanwhile,this thesis is of great significance for many aspects,like: expanding application scenarios of ACC system,improving driving safety and reducing driving burden.Based on ACC hierarchical control architecture,this thesis carried out systematic researches on the real-time estimation of road adhesion coefficient,safe distance model and multi-objective control algorithm,etc.The main contents of this thesis are as follows:(1)Road adhesion coefficient estimation algorithm based on extended Kalman filter.Firstly,a three-degree-freedom vehicle dynamics model and a Dugoff tire model are established for real-time estimation of road adhesion coefficient.Secondly,based on the relationship between road adhesion coefficient and vehicle dynamic parameters,the extended Kalman filter algorithm is used to estimate the road adhesion coefficient in real time.Finally,simulation verification is completed by Car Sim.The validity of the estimation algorithm is verified by comparing the actual value of road adhesion coefficient with the real-time estimation result.(2)Design of ACC system considering the influence of road adhesion coefficient.Aiming at the longitudinal control of vehicle,this thesis intends to establish the upper and lower layers for hierarchical controller.Based on the estimated road adhesion coefficient,a safety distance model considering the influence of road adhesion coefficientis proposed to obtain the expected distance.Then,fixed-speed cruise mode and following cruise mode are distinguished according to driving condition.The expected longitudinal acceleration is calculated by different control algorithms: PID control is used in fixed-speed cruise mode and model predictive control is used in following cruise mode.In following cruise mode,the objective function is designed by considering the influence of multiple performance indexes,such as safety,comfort and fuel economy.The constraint conditions are set based on the vehicle performance and road conditions.In addition,the relaxation factor is introduced to expand the range of feasible solution,and the prediction model is derived.Finally,the longitudinal expected acceleration is obtained by solving the quadratic programming problem.In the lower controller,acceleration/braking control switching strategy is established.Based on feedforward-feedback control strategy,engine torque and pressure of brake master cylinder are calculated to achieve the desired acceleration tracking.(3)Build the co-simulation platform of ACC system.The vehicle models,driving conditions are set in Car Sim.The road adhesion coefficient estimator,upper controller and lower controller are built in Simulink.The multi-condition adaptability simulation verification of the algorithm under different road adhesion coefficients is completed by four working conditions including fixed-speed cruising,steady following on straighttrack,front cut in and front cut out,and the adaptability of proposed algorithm under changing road conditions is verified in the following cruising mode. |
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