基于轮胎状态刚度预测的极限工况路径跟踪控制研究

王国栋; 刘洋; 李绍松; 卢晓晖; 张邦成

doi:10.16383/j.aas.c190349

基于轮胎状态刚度预测的极限工况路径跟踪控制研究

doi: 10.16383/j.aas.c190349

1.
长春工业大学机电工程学院长春 130012
2.
长春孔辉汽车科技股份有限公司长春 130012

基金项目: 国家重点研发计划(2017YFB0103602), 国家自然科学基金(51905045, 61603060)资助

详细信息

作者简介:
王国栋：长春工业大学机电工程学院硕士研究生. 主要研究方向为车辆动力学控制与智能车辆控制. E-mail: wangguodong99@outlook.com

刘洋：长春孔辉汽车科技股份有限公司中级工程师. 主要研究方向为汽车智能底盘、电控悬架系统及控制算法. E-mail: liuyang@khat.com.cn

李绍松：长春工业大学机电工程学院讲师. 2013年获得吉林大学博士学位. 主要研究方向为车辆动力学控制. 本文通信作者. E-mail: lishaosong@ccut.edu.cn

卢晓晖：长春工业大学机电工程学院副教授. 2013年获得吉林大学博士学位. 主要研究方向为汽车动力传动系统控制技术, 压电驱动与控制技术, 微能源俘获技术. E-mail: luxh13@ccut.edu.cn

张邦成：长春工业大学机电工程学院教授. 2011年获得吉林大学博士学位. 主要研究方向为机械电子测量技术与故障诊断. E-mail: zhangbangcheng@ccut.edu.cn

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出版历程
- 收稿日期: 2019-05-09
- 录用日期: 2019-09-09
- 网络出版日期: 2022-04-24
- 刊出日期: 2022-06-02

Research on Path Tracking Control Under Limit Conditions Based on Tire State Stiffness Prediction

1.
School of Mechatronic Engineering, Changchun University of Technology, Changchun 130012
2.
KH Automotive Technologies (Changchun) Co., Ltd., Changchun 130012

Funds: Supported by National Key Research and Development Program of China (2017YFB0103602) and National Natural Science Foundation of China (51905045, 61603060)

More Information

Author Bio:
WANG Guo-Dong　Master student at the School of Mechanical and Electrical Engineering, Changchun University of Technology. His research interest covers vehicle dynamics and intelligent vehicle control

LIU Yang　Intermediate engineer at KH Automotive Technologies (Changchun) Co., Ltd.. His research interest covers automotive intelligent chassis, electronically controlled suspension systems, and control algorithms

LI Shao-Song　Lecturer at the School of Mechanical and Electrical Engineering, Changchun University of Technology. He received his Ph.D. degree from Jilin University in 2013. His research interest covers vehicle dynamics control. Corresponding author of this paper

LU Xiao-Hui　Associate professor at the School of Mechanical and Electrical Engineering, Changchun University of Technology. She received her Ph.D. degree from Jilin University in 2013. Her research interest covers automotive powertrain control technology, piezoelectric drive and control technology, and microenergy capture technology

ZHANG Bang-Cheng　Professor at the School of Mechanical and Electrical Engineering, Changchun University of Technology. He received his Ph.D. degree from Jilin University in 2011. His research interest covers mechatronic measurement technology and fault diagnosis

摘要

摘要: 为解决高速极限工况下自动驾驶车辆紧急避撞时传统路径跟踪控制方法因轮胎力表达不精确导致的路径跟踪失败问题, 提出一种基于轮胎状态刚度预测的模型预测路径跟踪控制方法. 首先, 基于非线性UniTire轮胎模型求解的轮胎状态刚度对非线性轮胎力进行线性化处理. 其次, 基于期望路径信息提出状态刚度预测方法, 实现预测时域内轮胎力的预测和线性化. 最后, MATLAB和CarSim联合仿真实验表明: 所提出的方法能够明显改善高速极限工况下的避撞控制效果.
- 自动驾驶车辆 /
- 路径跟踪 /
- 转向避撞 /
- 模型预测控制 /
- 状态刚度预测
Abstract: To solve the problem of path tracking failure caused by the imprecise expression of tire force in conventional path tracking control system during the emergency collision avoidance of autonomous vehicles under high-speed limit condition, a model predictive path tracking control method based on tire state stiffness prediction is proposed. Firstly, the nonlinear tire force is linearized based on the tire state stiffness calculated by the nonlinear UniTire tire model. Secondly, based on the reference path information, the state stiffness prediction method is proposed to predict and linearize the tire force in the predicted horizon. Finally, MATLAB and CarSim joint simulation experiments show that the proposed method can improve the collision avoidance control effect under high-speed limit conditions obviously.
- Autonomous vehicle /
- path tracking /
- steering collision avoidance /
- model predictive control /
- state stiffness prediction

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图 1 车辆模型

Fig. 1 Vehicle model

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图 2 控制器整体结构

Fig. 2 Overall structure of the proposed controller

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图 3 基于Sigmoid函数的路径规划

Fig. 3 Path planning based on sigmoid function

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图 4 轮胎侧偏状态刚度

Fig. 4 Lateral tire state stiffness

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图 5 预测时域内的轮胎力

Fig. 5 Tire force over prediction horizon

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图 6 轮胎状态刚度对比曲线

Fig. 6 Comparison of tire state stiffness

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图 7 侧向位移

Fig. 7 Lateral displacement

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图 8 横摆角

Fig. 8 Yaw angle

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图 9 前轮转角

Fig. 9 Front steering angle

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图 10 车辆侧偏角

Fig. 10 Vehicle sideslip angle

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图 11 前轮轮胎侧向力

Fig. 11 Lateral force at front tire

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图 12 后轮轮胎侧向力

Fig. 12 Lateral force at rear tire

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图 13 侧向位移

Fig. 13 Lateral displacement

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图 14 横摆角

Fig. 14 Yaw angle

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图 15 前轮转角

Fig. 15 Front steering angle

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图 16 车辆侧偏角

Fig. 16 Vehicle sideslip angle

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图 17 前轮轮胎侧向力

Fig. 17 Lateral force at front tire

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图 18 后轮轮胎侧向力

Fig. 18 Lateral force at rear tire

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表 1 车辆参数

Table 1 Vehicle parameters

参数	符号	值
质心到前轴的距离	l_f	1.04 m
质心到后轴的距离	l_r	1.56 m
整车质量	m	1 240 kg
横摆转动惯量	I_z	2 031.4 kgm²

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表 2 控制器参数

Table 2 MPC controller parameters

参数	LTI-MPC	LTV-MPC
T_s	0.01	0.01
P	40	40
M	1	1
${Y_{\max }}$(°)	5	5
${\varphi _{\max }}$(°)	15	15
${\delta _f}_{\max }$(°)	10	10
${\Delta{\delta_f}_{\max }}$(°)	0.17	0.17
${\tau _{\varphi ,80}}$	550	550
${\tau _{y ,80}}$	260	260
${\tau _{u ,80}}$	1 900	1 900
${\tau _{\varphi ,100}}$	550	550
${\tau _{y ,100}}$	260	260
${\tau _{u ,100}}$	3 500	3 500

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