车辆纵向跟车舒适性模型预测控制算法研究  

Research on the model predictive control algorithm of comfortable longitudinal car following

作　　者：徐哲 胡趁义 龙永文 刘豪 XU Zhe;HU Chenyi;LONG Yongwen;LIU Hao(Key Laboratory of Advanced Manufacturing Technology for Automobile Parts,Ministry of Education,Chongqing University of Technology,Chongqing 400054,China)

机构地区：[1]重庆理工大学汽车零部件先进制造技术教育部重点实验室,重庆400054

出　　处：《重庆理工大学学报（自然科学）》2022年第12期9-17,共9页Journal of Chongqing University of Technology：Natural Science

基　　金：重庆市教委科学技术研究项目(KJQN201801101);重庆市自然科学基金项目(cstc2019jcyj-msxmX0119)。

摘　　要：在纵向跟车过程中,由于目标车辆的行驶状态不断变化,使自车也在不断变化,这样会导致自车的乘员出现不舒适的情况。因此,针对纵向跟车舒适性问题,在Matlab/Simulink中基于模型预测控制理论搭建了纵向跟车仿真模型。通过模型预测控制计算目标车辆的期望加速度,然后根据加速度、车辆自身信息计算出车辆4个轮的扭矩,通过CarSim/Simulink联合仿真对模型进行验证。仿真结果表明:两车的车间距误差为零,并且满足安全距离的要求,同时自车能够跟随前车的车速,且相对车速为零,而自车的加速度变化率又较稳定,能较好地实现纵向跟车并且满足舒适性的要求。With the continuous development of science and technology,the adaptive cruise system is widely used in modern cars and has become one of the important systems of intelligent assistant driving.At the same time,it can effectively reduce the driver’s operating intensity and improve safety,comfort and fuel economy.The adaptive cruise control system can not only achieve constant speed cruise,but also track the vehicle in front.It can also relieve the driver’s fatigue in the process of following the car longitudinally,and plays an important role in improving the traffic environment.However,the driving state of the target vehicle is constantly changing during longitudinal following,which causes the driving state of the self-vehicle to change continuously during the tracking process and makes the occupants in the self-vehicle feel uncomfortable.Therefore,aiming at the problem of longitudinal car following comfort,the controller is designed in Matlab/Simulink and the longitudinal car following model is established.The controller adopts the model predictive control principle,establishes the vehicle kinematics differential equation,and selects the distance between two vehicles,relative speed,self-vehicle acceleration,self-vehicle speed and impact as state variables.The expected acceleration of the self-vehicle is then selected as the control quantity.In order to make the simulation closer to the real situation,the acceleration of the front vehicle is considered as the disturbance in the driving process.When designing the model predictive controller,this paper selects trackability,comfort and safety as the performance indicators and system constraints of the controller to achieve multi-objective optimization,and then transforms the optimization objectives into a quadratic programming with constraints.If the optimal solution cannot be obtained within the specified calculation time,a relaxation factor is added to the optimization objectives.The expected longitudinal acceleration of the self-vehicle can be obtained by solvi

关 键 词：模型预测控制 目标车辆 跟车模型 安全距离 舒适性 

分 类 号：U471.15[机械工程—车辆工程]