Journal of Jilin University(Engineering and Technology Edition) ›› 2019, Vol. 49 ›› Issue (6): 1810-1817.doi: 10.13229/j.cnki.jdxbgxb20181122

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Road roughness identification based on vehicle responses

Jie LI(),Wen-cui GUO,Qi ZHAO,Sheng-feng GU   

  1. State Key Laboratory of Automotive Simulation and Control，Jilin University，Changchun 130022，China
  • Received:2018-11-12 Online:2019-11-01 Published:2019-11-08

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Abstract:

To solve the problem of road roughness identification, a NARX neural network identification method and its applicability are studied based on vehicle responses. A four degree of freedom plane model of vehicle vibration system is established, thus, the vehicle responses and road roughness of wheel can be obtained by simulation. The application selection, input scheme optimization and evaluation index of NARX neural network are studied, and the solutions of vehicle response selection and its combination optimization are put forward. The NARX neural network is used to identify the road roughness at front wheel of a car under the common road grade B and 60 km/h driving speed, for which the correlation coefficient and root mean square error are 96.75% and 0.003 3, respectively. The influences of training sampling points, vehicle response random noise, vehicle speed, and road grade on the NARX neural network are considered, and the adaptability of NARX neural network method for road roughness identification based on vehicle responses is illustrated. The results show that the use of orthogonal test design to determine the optimal input scheme of the NARX neural network and the identification of road roughness based on vehicle responses can achieve satisfactory performance and good applicability.

Key words: vehicle engineering, road roughness identification, vehicle response, NARX neural network

CLC Number: 

  • U461.4

Fig.1

Four degree of freedom plane model of vehicle vibration system"

Fig.2

Typical configuration of NARX neural network"

Table 1

Evaluation indexes of NARX neural network based on orthogonal experimental design"

方案 R/% RMSE 方案 R/% RMSE
1 0.00 0.015 00 17 96.29 0.003 48
2 26.47 0.013 40 18 95.05 0.004 38
3 16.72 0.013 52 19 93.06 0.004 66
4 36.87 0.012 22 20 96.21 0.003 54
5 29.07 0.013 50 21 92.85 0.004 84
6 43.41 0.014 30 22 91.18 0.006 00
7 43.36 0.012 38 23 94.93 0.003 76
8 32.84 0.014 28 24 84.89 0.005 98
9 75.44 0.008 96 25 42.26 0.013 62
10 93.43 0.004 50 26 32.13 0.015 26
11 72.52 0.008 94 27 48.30 0.014 24
12 93.59 0.004 44 28 47.91 0.012 02
13 94.39 0.004 26 29 19.28 0.015 32
14 94.51 0.004 38 30 21.52 0.015 42
15 95.44 0.003 70 31 36.46 0.013 44
16 96.35 0.003 30 32 28.76 0.014 38

Fig.3

Identification results of optimized input scheme for NARX neural network"

Table 2

Evaluation indexes of different trainingsample points"

采样点数 R/% RMSE
216 38.75 0.012 0
240 58.69 0.012 3
270 65.46 0.012 1
310 83.93 0.007 0
360 83.39 0.006 8
432 91.33 0.006 6
540 93.17 0.005 9
720 93.29 0.006 0
1080 93.56 0.005 0

Table 3

Evaluation indexes of different SNRs"

信噪比/dB R/% RMSE
1 68.10 0.013 2
3 77.97 0.008 0
5 84.47 0.007 5
10 87.82 0.006 7
20 92.71 0.004 6

Table 4

Evaluation indexes of different speeds"

车速/(km·h-1) R/% RMSE
40 89.66 0.005 6
50 96.94 0.002 9
60 95.25 0.003 7
70 96.18 0.003 1
80 89.56 0.004 4

Table 5

Evaluation indexes of different road grades"

路面等级 R/% RMSE
A级 92.26 0.005 6
B级 94.70 0.005 0
C级 85.02 0.014 6
D级 62.06 0.036 8
1 段虎明, 石峰, 谢飞, 等 . 路面不平度研究综述[J]. 振动与冲击, 2009, 28(9): 95-101.
1 Duan Hu-ming , Shi Feng , Xie Fei , et al . A survey of road roughness study[J]. Journal of Vibration and Shock, 2009, 28(9): 95-101.
2 Hammond D S , Chapman L , Thornes J E . Roughness length estimation along road transects using airborne LIDAR data[J]. Meteorological Applications, 2012, 19(4): 420-426.
3 Chen W X , Ni Z B , Hu X H . Research on pavement roughness based on the laser triangulation[J]. Photonic Sensors, 2016, 6(2): 177-180.
4 张丽霞, 赵又群, 徐培民, 等 . 路面功率谱密度识别的仿真[J]. 农业机械学报, 2007, 38(5): 15-18.
4 Zhang Li-xia , Zhao You-qun , Xu Pei-min , et al ．Simulation of road surface power spectrum density identif ication[J]. Transactions of the Chinese Society for Agricultural Machinery, 2007, 38(5): 15-18.
5 Yousefzadeh M , Azadi S , Soltani A . Road profile estimation using neural network algorithm[J]. Journal of Mechanical Science and Technology, 2010, 24(3): 743-754.
6 Solhnirzaei A , Azadi S , Kazemi R . Road profile estimation using wavelet neural network and 7-DOF vehicle dynamic systems[J]. Journal of Mechanical Science and Technology, 2012, 26(10): 3029-3036.
7 Ngwangwa H M , Heyns P S , Kululanga Grant K . An overview of the neural network based technique for monitoring of road condition via reconstructed road profiler[C]∥Southern African Transport Conference, Pretoria, Southern African, 2008: 312-329.
8 Ngwangwa H M , Heyns P S , Labuschagne F J J . Reconstruction of road defects and road roughness classification using vehicle responses with artificial neural networks simulation[J]. Journal of Terramechanics, 2010, 47(2): 97-111.
9 Ngwangwa H M , Heyns P S , Breytenbach H G A . Reconstruction of road defects and road roughness classification using artificial neural networks simulation and vehicle dynamic response: application to experimental data[J]. Journal of Terramechanics, 2014, 53(1): 1-18.
10 李杰, 高雄, 王维, 等 . 基于UniTire模型的平顺性和操纵稳定性协同研究[J]. 汽车工程, 2018, 40(2): 127-132.
10 Li Jie , Gao Xiong , Wang Wei , et al . A collaborative study on ride comfort and handling stability based on UniTire models[J]. Automotive Engineering, 2018, 40(2): 127-132.
11 周瑜 . 某轿车车身姿态半主动悬架最优控制研究[D]. 长春: 吉林大学汽车工程学院, 2016.
11 Zhou Yu . Research on the body attitude control of semi-active suspension vehicle using optimal control theory[D]. Changchun: College of Automotive Engineering, Jilin University, 2016.
12 Lei J , Yu W , Zhu X H . A novel vehicle dynamics identification method utilizing MIMU sensors based on support vector machine[C]∥10th International Conference on Sensing Technology, Nanjing, China, 2016:1-8.
13 张金 . 基于ARM的车辆姿态测量系统设计[D]. 北京: 北京交通大学电子信息工程学院, 2008.
13 Zhang Jin . Design and realization of vehicle attitude measurement system based on ARM[D]. Beijing: College of Electronic Information Engineering, Beijing Jiaotong University, 2008.
14 Andersson U , Bortolin G , Backen S , et al . Estimation of sideslip angles of a Volvo A25E articulated all-wheel drive hauler based on GPS/INS measurements[J]. SAE Technical Papers, 2011-01-2156.
15 王朝斌, 吴旭, 熊吉 . 汽车车轮轮心与车身相对位移测量方法的探讨[J]. 汽车科技, 2014(5): 41-44.
15 Wang Chao-bin , Wu Xu , Xiong Ji . Study on test method about measuring the relative displacement of body at wheel center[J]．Automobile Science and Technology, 2014(5): 41-44.
16 王小川, 史峰, 郁磊 . MATLAB神经网络43个案例分析[M]. 北京: 北京航空航天大学出版社, 2013.
17 任露泉 . 试验优化设计与分析[M]. 北京: 高等教育出版社, 2003.
18 张敏, 袁辉 . 关于标准误差应用问题的讨论[J]. 郑州工业大学学报, 1996, 17(3): 95-100.
18 Zhang Min , Yuan Hui . Discussion of application problems about standard error[J]. Journal of Zhengzhou University of Technology, 1996, 17(3): 95-100.
19 杨彦荣, 戴云 . 基于均方根误差和相关系数评价人眼像差对视网膜像质的影响[J]. 光学学报, 2017, 37(3): 389-395.
19 Yang Yan-rong , Dai Yun . Evaluation og the effect on eye aberration on retinal imaging quality based on the root mean sqaure error and correlation coefficient[J]. Acta Optica Sinica, 2017, 37(3): 389-395.
20 余志生 ．汽车理论[M]．北京：机械工业出版社，2009.
21 GB/T 4970—2009．汽车平顺性试验方法[S].
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