基于自适应模型预测的智能网联汽车稳定性控制研究  

Research on Stability Control of Intelligent Connected Vehicles based on Adaptive Model Prediction

作　　者：李然 郭谨玮 董海博 黄哲 Li Ran;Guo Jinwei;Dong Haibo;Huang Zhe(Automotive Data of China Co.,Ltd.,Tianjin 300300;CATARC Intelligent and Connected Technology Co.,Ltd.,Tianjin 300300)

机构地区：[1]中汽数据有限公司,天津300300 [2]中汽智联技术有限公司,天津300300

出　　处：《中国汽车》2024年第8期28-35,共8页China Auto

摘　　要：针对智能网联汽车在急转工况下,高附着路面易发生侧翻事故,低附着路面易发生侧滑事故的车辆稳定性问题,提出了一种基于自适应模型预测的智能网联汽车稳定性控制模型。全面考虑了智能网联车辆运行过程中的横摆、侧滑、侧倾等众多造成车辆不稳定的因素,构建了智能网联汽车整车动力学模型。通过对整车动力学模型进行优化,实现模型时域参数的自适应控制,使得控制器的计算效率和跟踪精度显著提升。为了进一步验证控制器的性能,通过MATLAB/Simulink与Carsim软件,搭建基于车辆动力学模型预测控制器,以FishHook和J-Turn为试验工况,对自适应预测控制模型的有效性进行全面验证。仿真结果表明:本文提出的自适应模型预测控制器能够有效提升模型的计算效率和控制精度,单次平均计算时间缩短约15.76%;相对于传统的侧倾预测方法,本文提出的方法响应速度快,控制精度高,能有效地保证智能网联汽车在时变曲率、侧倾坡度等复杂环境下实现无碰撞安全稳定的运行。An intelligent networked vehicle stability control model based on adaptive model prediction is proposed to address the vehicle stability issues of intelligent networked vehicles under sharp turning conditions,where high-adhesion roads are prone to rollover accidents and low-adhesion roads are prone to side slip accidents.A complete dynamic model of the intelligent connected vehicle is established,taking into account the many factors that can cause instability during operation,such as yaw,side slip,and roll.By optimizing the vehicle dynamics model and enabling adaptive control of model time-domain parameters,the computational efficiency and tracking accuracy of the controller have been significantly improved.To further verify the performance of the controller,an adaptive model predictive controller was built using MATLAB/Simulink,combined with a vehicle dynamics model built using Carsim software.The effectiveness of the adaptive predictive control model was tested using the FishHook and J-Turn test cases.The simulation results show that the adaptive model predictive controller proposed in this paper can effectively improve the computational efficiency and control accuracy of the model compared with traditional model predictive controllers,and the average single computation time has been reduced approximately 15.76%;the method proposed in this paper has a fast response speed,high control accuracy,witch can effectively ensure the safe and stable operation of intelligent connected vehicles without collision in complex environments such as time-varying curvature and roll gradient,compared with traditional roll prediction methods.

关 键 词：智能车辆 轨迹跟踪 模型预测 稳定性控制 

分 类 号：U463.6[机械工程—车辆工程]