Journal of Jilin University(Engineering and Technology Edition) ›› 2019, Vol. 49 ›› Issue (4): 1017-1025.doi: 10.13229/j.cnki.jdxbgxb20180517

   

Neural network sliding mode control of commercial vehicle ABS based on longitudinal vehicle speed estimation

Jing LI(),Qiu⁃jun SHI,Peng LIU,Ya⁃wei HU   

  1. State Key Laboratory of Automotive Simulation and Control，Jilin University，Changchun 130022，China
  • Received:2018-05-17 Online:2019-07-01 Published:2019-07-16

RICH HTML

 23   

PDF (PC)

292

Abstract:

It is difficult to directly obtain the longitudinal vehicle speed of commercial vehicle in the anti-lock braking system (ABS). In order to estimate the longitudinal speed in the braking process, a strong tracking-cubature Kalman filter algorithm was proposed. Then, according to the ABS control requirements, a commercial vehicle ABS neural network sliding control algorithm was established. It uses the sliding mode algorithm to control the slip rate of ABS, and uses the neural network to adjust the parameters of the sliding control algorithm. Through Matlab/Simulink and TruckSim co-simulation, simulations tests were conducted on high, medium, low, and off-road surfaces, respectively. The simulation results show that the strong tracking cubature Kalman filter algorithm is accurate in estimating the longitudinal speed, and the neural network sliding control algorithm of ABS has good effect.

Key words: vehicle engineering, braking antilock braking system, strong tracking cubature Kalman filtering(STCKF), neural network, sliding mode control

CLC Number: 

  • U461.1

Fig.1

Schematic diagram of vehicle dynamics model"

Fig.2

Control structure"

Fig.3

Neural network structure"

Table 1

Main simulation parameters of vehicle"

车辆主要参数 数值 单位
整车质量 6360 kg
轴距 4490 mm
质心到前轴距离 3105 mm
质心高度 1200 mm
车轮滚动半径 510 mm
车轮转到惯量 14 kg·m2

Fig.4

STCKF and CKF estimate longitudinal speed and error（μ=0.8）"

Fig.5

Estimated speed and four wheel speeds（μ=0.8）"

Fig.6

Slip of four wheels（μ=0.8）"

Fig.7

STCKF and CKF estimate longitudinal speed and error（μ=0.5）"

Fig.8

Estimated speed and four wheel speeds（μ=0.5）"

Fig.9

Slip of four wheels（μ=0.5）"

Fig.10

STCKF and CKF estimate longitudinal speed and error（μ=0.3）"

Fig .11

Estimated speed and four wheel speeds（μ=0.3）"

Fig.12

Slip of four wheels（μ=0.3）"

Fig.13

STCKF and CKF estimate longitudinal speed and error（bisectional road）"

Fig.14

Estimated speed and four wheel speeds （bisectional road）"

Fig.15

Slip of four wheels（bisectional road）"

1 Hashemi E , Kasaiezadeh A , Khosravani S , et al . Estimation of longitudinal speed robust to road conditions for ground vehicles[J]. Vehicle System Dynamics, 2016, 54(8): 1120⁃1146.
2 Antonov S , Fehn A , Kugi A . Unscented Kalman filter for vehicle state estimation[J].Vehicle System Dynamics, 2011, 49(9): 1497⁃1520.
3 Reif K , Renner K , Saeger M . Using the unscented kalman filter and a non⁃linear two⁃track model for vehicle state estimation[J]. IFAC Proceedings Volumes, 2008, 17(1):8570⁃8575.
4 金贤建, 殷国栋, 陈南,等 . 分布式驱动电动汽车的平方根容积卡尔曼滤波状态观测[J].东南大学学报: 自然科学版, 2016, 46(5): 992⁃996.
Jin Xian⁃jian , Yin Guo⁃dong , Chen Nan , et al . State observation of distributed drive electric vehicle using square root cubature Kalman filter[J]. Journal of Southeast University（Natural Science Edition）, 2016, 46(5): 992⁃996.
5 Li Jing , Zhang Jia⁃xu . Vehicle Sideslip Angle estimation based on hybrid kalman filter[J]. Mathematical Problems in Engineering, 2016(3): 1⁃10.
6 Sun Ren⁃Yun , Wang Bo , Zhan Yong⁃Fu . Fuzzy control of automobile ECBS on varying pavement[J]. Advanced Materials Research, 2012(383⁃390): 7338⁃7344.
7 Drakunov S , Ozguner U , Dix P , et al . ABS control using optimum search via sliding modes[J]. IEEE Transactions on Control Systems Technology, 2002, 3(1):79⁃85.
8 何祥坤, 季学武, 杨恺明, 等 . 基于集成式线控液压制动系统的轮胎滑移率控制[J]. 吉林大学学报: 工学版, 2018, 48(2): 364⁃372.
He Xiang⁃kun , Ji Xue⁃wu , Yang Kai⁃ming , et al . Tire slip control based on integrated⁃electro⁃hydraulic braking system[J]. Journal of Jinlin University(Engineering and Technology Edition), 2018, 48(2): 364⁃372.
9 张炳超 . 商用车气制动ABS鲁棒控制方法研究[D]. 重庆：重庆大学机械工程学院, 2011.Zhang Bing⁃chao. A study of robust control method for pneumatic brake ABS on commercial vehicles[D]. Chongqing: College of Mechanical Engineering, Chongqing University,2011.
10 戴彦 . 汽车ABS滑移率的模糊滑模控制研究[J]. 机械设计与制造, 2015(6): 80⁃82.
Dai Yan . Study on fuzzy sliding mode control of anti⁃skid⁃brake system based on slip ratio[J]. Machinery Design & Manufacture, 2015(6): 80⁃82.
11 Li Qiu⁃rong , Sun Feng . Strong tracking cubature Kalman filter algorithm for GPS/INS Integrated Navigation System[C]∥IEEE International Conference on Mechatronics and Automation. IEEE, 2013:1113⁃1117.
12 Xia Bi⁃zhong , Wang Hai⁃qing , Wang Ming⁃wang , et al . A new method for state of charge estimation of lithium⁃ion battery based on strong tracking cubature kalman filter[J]. Energies, 2015, 8(12): 13458⁃13472.
13 朱为文 . 某客车复合制动系统控制策略研究[D]. 长春: 吉林大学汽车工程学院, 2017.Zhu Wei⁃wen. Study on control of composite braking system for a bus[D]. Changchun: College of Automotive Engineering, Jilin University, 2017.
14 Dugoff H , Fancher P S , Segel L . An analysis of tire traction properties and their influence on vehicle dynamic performance[C]∥SAE Papers, 700377.
15 李秋荣 . 改进容积卡尔曼滤波算法及其导航应用研究[D]. 哈尔滨: 哈尔滨工程大学自动化学院, 2015.Li Qiu⁃rong. Research on improved cubatrue Kalman filter and its application in navigation[D]. Harbin: College of Automation, Harbin Engineering University, 2015.
16 王建敏, 董小萌, 吴云洁 . 高超声速飞行器RBF神经网络滑模变结构控制[J]. 电机与控制学报, 2016, 20(5):103⁃110.
Wang Jian⁃min , Dong Xiao⁃meng , Wu Yun⁃jie . Hypersonic flight vehicle of sliding mode variable structure control based on RBF neural network[J]. Electric Machines and Control, 2016, 20(5): 103⁃110.
[1] Lei CHEN,Jiang⁃feng WANG,Yuan⁃li GU,Xue⁃dong YAN. Multi⁃source traffic data fusion algorithm based onmind evolutionary algorithm optimization [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(3): 705-713.
[2] Dan⁃tong OUYANG,Jun XIAO,Yu⁃xin YE. Distant supervision for relation extraction with weakconstraints of entity pairs [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(3): 912-919.
[3] CHANG Cheng,SONG Chuan-xue,ZHANG Ya-ge,SHAO Yu-long,ZHOU Fang. Minimizing inverter capacity of doubly-fed machine driving electric vehicles [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1629-1635.
[4] XI Li-he,ZHANG Xin,SUN Chuan-yang,WANG Ze-xing,JIANG Tao. Adaptive energy management strategy for extended range electric vehicle [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1636-1644.
[5] HE Ren,YANG Liu,HU Dong-hai. Design and analysis of refrigeration system supplied by solar auxiliary power of refrigerator car [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1645-1652.
[6] NA Jing-xin,MU Wen-long,FAN Yi-sa,TAN Wei,YANG Jia-zhou. Effect of hygrothermal aging on steel-aluminum adhesive joints for automotive applications [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1653-1660.
[7] LIU Yu-mei,LIU Li,CAO Xiao-ning,XIONG Ming-ye,ZHUANG Jiao-jiao. Construction on collision avoidance model of bogie dynamic simulation test bench [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1661-1668.
[8] JIANG Tao,LIN Xue-dong,LI De-gang,YANG Miao,TANG Xue-lin. Effect of control parameters on heat release rate with ANN method [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1747-1754.
[9] XU Yan,SUN Mei-shuang. Enhancing underwater image based on convolutional neural networks [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1895-1903.
[10] ZHAO Wei-qiang, GAO Ke, WANG Wen-bin. Prevention of instability control of commercial vehicle based on electric-hydraulic coupling steering system [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1305-1312.
[11] SONG Da-feng, WU Xi-tao, ZENG Xiao-hua, YANG Nan-nan, LI Wen-yuan. Life cycle cost analysis of mild hybrid heavy truck based on theoretical fuel consumption model [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1313-1323.
[12] ZHU Jian-feng, ZHANG Jun-yuan, CHEN Xiao-kai, HONG Guang-hui, SONG Zheng-chao, CAO Jie. Design modification for automotive body structure based on seat pull safety performance [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1324-1330.
[13] NA Jing-xin, PU Lei-xin, FAN Yi-sa, SHEN Chuan-liang. Effect of temperature and humidity on the failure strength of Sikaflex-265 aluminum adhesive joints [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1331-1338.
[14] WANG Yan, GAO Qing, WANG Guo-hua, ZHANG Tian-shi, YUAN Meng. Simulation of mixed inner air-flow integrated thermal management with temperature uniformity of Li-ion battery [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1339-1348.
[15] JIN Li-sheng, XIE Xian-yi, GAO Lin-lin, GUO Bai-cang. Distributed electric vehicle stability control based on quadratic programming [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1349-1359.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd