低附着路况条件下人车共享转向系统稳定控制

doi:10.13229/j.cnki.jdxbgxb20221416

Abstract

Abstract:

Aiming at the problem that the vehicle is more prone to instability in ice and snow weather， the stable tracking of the vehicle to the reference path is studied under the condition of low adhesion and asymmetric road surface. At the same time， considering the cooperative sharing between the driver and the intelligent controller， the sharing mode and driving right allocation is discussed， so as to improve the tracking accuracy and steering stability of the vehicle under the complex road conditions of ice and snow road and ensure the driving experience of the driver. A vehicle model with asymmetric left and right wheels for snow and ice road surface is established. And the vehicle steering stability constraint under ice and snow pavement is determined as a part of the subsequent model predictive control solution. The human-vehicle sharing structure based on model prediction and fuzzy weight allocation strategy is established and the shared steering controller is designed. Simulink/ CarSim co-simulation verifies that the designed control system can effectively improve vehicle tracking accuracy and driving stability.

Key words: vehicle engineering, trajectory tracking control, model predictive control, shared steering control, driving authority allocation

CLC Number:

U461.6

Bo XIE,Rong GAO,Fu-qiang XU,Yan-tao TIAN. Stability control of human⁃vehicle shared steering system under low adhesion road conditions[J].Journal of Jilin University(Engineering and Technology Edition), 2023, 53(3): 713-725.

Figures/Tables 21

Fig.1

Fig.2

Fig.3

Table 1

Fuzzy rules"

$S θ E$	$L 0$	$L 1$	$L 2$	$L 3$	$L 4$
$E 0$	$S$	$S$	$S$	$S$	$M S$
$E 1$	$S$	$S$	$S$	$M S$	$M$
$E 2$	$S$	$S$	$M S$	$M$	$M B$
$E 3$	$S$	$M S$	$M$	$M B$	$B$
$E 4$	$M S$	$M S$	$M$	$M B$	$B$

Table 1

Fig.4

Fig.5

Fig.6

Fig.7

Table 2

Parameters for the vehicle and controller"

参数	数值
整车质量 $m$ /kg	1 380
质心到前轴的距离 $l f$ /m	1.015
横摆转动惯量/（kg·m²）	1 536.7
车轮半径 $R w$ /m	0.325
前轮侧倾刚度 $K ? f$ /（N·m^-1）	46 560.5
前轮侧倾阻尼 $C ? f$ /（N·m·s^-1）	2 386
车身宽度 $D$ /m	1.616
质心距地面高度 $h$ /m	0.87
采样周期 $T$ /s	0.001
预测时域 $N p$	50
最大横向误差 $Δ y m a x$ /m	1
簧上质量 $m s$ /kg	1 270
质心到后轴的距离 $l r$ /m	1.895
车轮转动惯量 $I w$ /（kg·m²）	1
车轮轴距 $t w$ /m	1.55
后轮侧倾刚度 $K ? r$ /（N·m^-1）	24 955.5
后轮侧倾阻尼 $C ? r$ /（N·m·s^-1）	2386
道路宽度 $W r$ /m	3.75
重力加速度 $g$ /（m·s^-2）	9.8
转向系传动比 $i$	15
控制时域 $N c$	25
转角最大差 $δ h - δ a m a x$ /rad	0.45

Table 2

Fig.8

Fig.9

Fig.10

Table 3

Table 4

Table 5

Fig.11

Fig.12

Table 6

Fig.13

Table 7

Table 8

References 18

1	宗长富, 代昌华, 张东. 智能汽车的人机共驾技术研究现状和发展趋势[J]. 中国公路学报, 2021, 34(6): 214-237.
	Zong Chang-fu, Dai Chang-hua, Zhang Dong. Human-machine interaction technology of intelligent vehicles: current development trends and future directions[J]. China Journal of Highway and Transport, 2021, 34(6): 214-237.
2	赵又群, 李宇昊, 邓汇凡, 等. 基于Popov超稳定性的分布式电动汽车稳定性控制[J]. 吉林大学学报: 工学版, 2022, 52(10): 2225-2233.
	Zhao You-qun, Li Yu-hao, Deng Hui-fan, et al. Stability control of distributed electric vehicle based on popov hyperstability[J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(10): 2225-2233.
3	Marcano M, Díaz S, Pérez J, et al. A review of shared control for automated vehicles: theory and applications[J]. IEEE Transactions on Human-Machine Systems, 2020, 50(6): 475-491.
4	Wang W, Na X, Cao D, et al. Decision-making in driver-automation shared control: a review and perspectives[J]. IEEE/CAA Journal of Automatica Sinica, 2020, 7(5): 1289-1307.
5	胡云峰, 曲婷, 刘俊, 等. 智能汽车人机协同控制的研究现状与展望[J]. 自动化学报, 2019, 45(7): 1261-1280.
	Hu Yun-feng, Qu Ting, Liu Jun, et al. Human-machine cooperative control of intelligent vehicle: recent developments and future perspectives[J]. Acta Automatica Sinica, 2019,45(7): 1261-1280.
6	何仁, 赵晓聪, 杨奕彬, 等. 基于驾驶人风险响应机制的人机共驾模型[J]. 吉林大学学报:工学版, 2021, 51(3): 799-809.
	He Ren, Zhao Xiao-cong, Yang Yi-bin, et al. Man⁃machine shared driving model using risk⁃response mechanism of human driver[J]. Journal of Jilin University (Engineering and Technology Edition), 2021, 51(3): 799-809.
7	Xie J, Xu X, Wang F, et al. Modeling adaptive preview time of driver model for intelligent vehicles based on deep learning[J]. Journal of Systems and Control Engineering, 2022, 236(2): 355-369.
8	Lazcano A M R, Niu T, Akutain X C, et al. MPC-based haptic shared steering system: a driver modeling approach for symbiotic driving[J]. IEEE/ASME Transactions on Mechatronics, 2021, 26(3): 1201-1211.
9	田涛涛, 侯忠生, 刘世达, 等. 基于无模型自适应控制的无人驾驶汽车横向控制方法[J]. 自动化学报, 2017, 43(11): 1931-1940.
	Tian Tao-tao, Hou Zhong-sheng, Liu Shi-da, et al. Model-free adaptive control based lateral control of self-driving car[J]. Acta Automatica Sinica, 2017, 43(11): 1931-1940.
10	Li L, Lu Y, Wang R, et al. A three-dimensional dynamics control framework of vehicle lateral stability and rollover prevention via active braking with MPC[J]. IEEE Transactions on Industrial Electronics, 2016, 64(4): 3389-3401.
11	Chouki S, Anh-Tu N, Amir B M, et al. Driver-automation cooperation oriented approach for shared control of lane keeping assist systems[J]. IEEE Transactions on Control Systems Technology, 2019, 27(5): 1962-1978.
12	刘俊. 智能车辆人机协同转向控制策略研究[D]. 长春: 吉林大学通信工程学院, 2020.
	Liu Jun. Research on driver-automation cooperative steering control strategy of intelligent vehicle[D]. Changchun: College of Communication Engineering, Jilin University, 2020.
13	Tian Y, Zhao Y, Shi Y, et al. The indirect shared steering control under double loop structure of driver and automation[J]. IEEE/CAA Journal of Automatica Sinica, 2020, 7(5): 1403-1416.
14	葛召浩. 一种极限工况下人-车-路闭环系统纵横向协同控制方法[D]. 南京: 南京航空航天大学能源与动力学院, 2020.
	Ge Zhao-hao. A longitudinal-lateral cooperative control method for human-vehicle-road closed loop system under extreme conditions[D]. Nanjing: College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, 2020.
15	Wang P, Liu H, Guo L, et al. Design and experimental verification of real-time nonlinear predictive controller for improving the stability of production vehicles[J]. IEEE Transactions on Control Systems Technology, 2020, 29(5): 2206-2213.
16	张雷, 赵宪华, 王震坡. 四轮轮毂电机独立驱动电动汽车轨迹跟踪与横摆稳定性协调控制研究[J]. 汽车工程, 2020, 42(11): 1513-1521.
	Zhang Lei, Zhao Xian-hua, Wang Zhen-po. Study on coordinated control of trajectory tracking and yaw stability for autonomous four-wheel-independent-driving electric vehicles[J]. Automotive Engineering, 2020, 42(11): 1513-1521.
17	司振立. 基于模型预测的分布式驱动智能车轨迹跟踪研究[D]. 长春: 吉林大学汽车工程学院, 2020.
	Si Zhen-li. Research on trajectory tracking of distributed driving intelligent vehicle based on model predictive control[D]. Changchun: College of Automotive Engineering, Jilin University, 2020.
18	谭运生. 电动轮汽车转向的动态稳定控制及人车闭环仿真研究[D]. 南京: 南京航空航天大学能源与动力学院, 2015.
	Tan Yun-sheng. Study of dynamic stability control and driver-vehicle closed loop system for in-wheel motor electric vehicles steering[D]. Nanjing: College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, 2015.

Related Articles 15

[1]	Yan-tao TIAN,Fu-qiang XU,Kai-ge WANG,Zi-xu HAO. Expected trajectory prediction of vehicle considering surrounding vehicle information [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(3): 674-681.
[2]	De-jun WANG,Kai-ran ZHANG,Peng XU,Tian-biao GU,Wen-ya YU. Speed planning and control under complex road conditions based on vehicle executive capability [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(3): 643-652.
[3]	Ke HE,Hai-tao DING,Xuan-qi LAI,Nan XU,Kong-hui GUO. Wheel odometry error prediction model based on transformer [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(3): 653-662.
[4]	Yan-tao TIAN,Yan-shi JI,Huan CHANG,Bo XIE. Deep reinforcement learning augmented decision⁃making model for intelligent driving vehicles [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(3): 682-692.
[5]	Ke HE,Hai-tao DING,Nan XU,Kong-hui GUO. Enhanced localization system based on camera and lane markings [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(3): 663-673.
[6]	Bing ZHU,Tian-xin FAN,Jian ZHAO,Pei-xing ZHANG,Yu-hang SUN. Accelerate test method of automated driving system based on hazardous boundary search [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(3): 704-712.
[7]	Deng-feng WANG,Hong-li CHEN,Jing-xin NA,Xin CHEN. Failure comparison of single and double lap joints after high temperature aging [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(2): 346-354.
[8]	Pei ZHANG,Zhi-wei WANG,Chang-qing DU,Fu-wu YAN,Chi-hua LU. Oxygen excess ratio control method of proton exchange membrane fuel cell air system for vehicle [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(9): 1996-2003.
[9]	Yun-feng HU,Tong YU,Hui-ce YANG,Yao SUN. Optimal control method of fuel cell start⁃up in low temperature environment [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(9): 2034-2043.
[10]	Hai-lin KUI,Ze-zhao WANG,Jia-zhen ZHANG,Yang LIU. Transmission ratio and energy management strategy of fuel cell vehicle based on AVL⁃Cruise [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(9): 2119-2129.
[11]	Yan LIU,Tian-wei DING,Yu-peng WANG,Jing DU,Hong-hui ZHAO. Thermal management strategy of fuel cell engine based on adaptive control strategy [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(9): 2168-2174.
[12]	Cheng LI,Hao JING,Guang-di HU,Xiao-dong LIU,Biao FENG. High⁃order sliding mode observer for proton exchange membrane fuel cell system [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(9): 2203-2212.
[13]	Ke-yong WANG,Da-tong BAO,Su ZHOU. Data-driven online adaptive diagnosis algorithm towards vehicle fuel cell fault diagnosis [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(9): 2107-2118.
[14]	Qi-ming CAO,Hai-tao MIN,Wei-yi SUN,Yuan-bin YU,Jun-yu JIANG. Hydrothermal characteristics of proton exchange membrane fuel cell start⁃up at low temperature [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(9): 2139-2146.
[15]	Feng-xiang CHEN,Qi WU,Yuan-song LI,Tian-de MO,Yu LI,Li-ping HUANG,Jian-hong SU,Wei-dong ZHANG. Matching，simulation and optimization for 2.5 ton fuel cell/battery hybrid forklift [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(9): 2044-2054.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Comments

Recommended 0

No Suggested Reading articles found!

车辆参数	CarSim驾驶员控制	固定权重控制	本文共享控制
方向盘转角最大值/（°）	27.24	20.42	14.36
方向盘转角标准值/（°）	13.35	10.04	7.49
侧向误差最大值/m	0.6997	0.3973	0.1553
侧向误差最大值占比（同carsim控制比较）/%	100.00	56.78	22.19
侧向误差均方根值/m	0.2468	0.1976	0.0781
侧向加速度最大值/ （9.8 m·s^-2）	0.2831	0.1692	0.1463
侧向加速度标准差/ （9.8 m·s^-2）	0.1361	0.1037	0.0775

车辆参数	CarSim驾驶员控制	固定权重控制	本文共享控制
方向盘转角最大值/（°）	19.16	18.73	17.08
方向盘转角标准值/（°）	8.817	8.223	7.041
侧向误差最大值/m	0.2424	0.1781	0.1021
侧向误差最大值占比（同CarSim控制比较）/%	100.00	73.47	42.12
侧向误差均方根值/m	0.1126	0.0869	0.0497
侧向加速度最大值/ （9.8 m·s^-2）	0.1988	0.1788	0.1369
侧向加速度标准差/ （9.8 m·s^-2）	0.0906	0.0838	0.0723

车辆参数	CarSim驾驶员控制	本文共享控制
方向盘转角最大值/（°）	50.29	41.98
方向盘转角标准差/（°）	18.84	15.61
侧向误差最大值/m	0.5471	0.5089
侧向误差均方根值/m	0.1974	0.1891
侧向误差最大值占比（与CarSim控制比较）/%	100	95.79
侧向加速度最大值/ （9.8 m·s^-2）	0.9343	0.7552
侧向加速度标准差/ （9.8 m·s^-2）	0.3686	0.2959
横摆角速度最大值/（rad·s^-1）	0.4456	0.3711

车辆参数	CarSim驾驶员控制	本文共享控制
方向盘转角最大值/（°）	151.80	44.34
方向盘转角标准差/（°）	59.47	16.73
侧向误差最大值/m	0.9260	0.5779
侧向误差均方根差/m	0.4849	0.2002
侧向误差最大值占比（与CarSim控制比较）/%	100.00	41.29
侧向加速度最大值/ （9.8 m·s^-2）	0.6616	0.6445
侧向加速度标准差/ （9.8 m·s^-2）	0.3309	0.2569
横摆角速度最大值/ （rad·s^-1）	0.7524	0.4816

车辆参数	生疏驾驶员控制	MPC控制	本文共享控制
方向盘转角最大值/（°）	52.8	32.37	31.89
方向盘转角标准差/（°）	36.23	22.26	20.63
侧向误差最大值/m	3.8797	-	0.2159
侧向误差均方根值/m	1.0591	-	0.1782

Stability control of human⁃vehicle shared steering system under low adhesion road conditions

RICH HTML

PDF (PC)