Journal of Jilin University(Engineering and Technology Edition) ›› 2021, Vol. 51 ›› Issue (5): 1700-1707.doi: 10.13229/j.cnki.jdxbgxb20200540

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Driving cycle construction of heavy semi⁃trailers carrying hazardous cargos

Hong-xue LI1(),Shi-wu LI1(),Wen-cai SUN1,Wei LI1,Meng-zhu GUO1,2   

  1. 1.College of Transportation,Jilin University,Changchun 130022,China
    2.State Key Laboratory of Automotive Simulation and Control,Jilin University,Changchun 130022,China
  • Received:2020-07-17 Online:2021-09-01 Published:2021-09-16
  • Contact: Shi-wu LI E-mail:lhx18@mails.jlu.edu.cn;lshiwu@163.com

Abstract:

The self-developed Nicigo driving-recorder was used to collect the driving data of 50 heavy semi-trailers carrying hazardous cargos in Ningbo city according to the 24-hour free running route method. 3006 kinematic fragments were obtained through data segmentation technology. Principal component analysis and K-means clustering technology were used to classify the kinematic segments. Various representative segments were selected according to the distance between the kinematic segments and the clustering center, and the driving cycle of heavy semi-trailers carrying hazardous cargos in Ningbo city were finally fitted. By comparing with the representative driving cycles at home and abroad, it is found that the average speed, acceleration and deceleration ratio of the constructed cycle are very close to the FTP-75 cycle, and the uniform speed ratio is the least different from that of heavy trucks in Beijing, and the idle speed ratio is greatly different from that of various cycles.

Key words: vehicle operation engineering, semi-trailers, driving cycles, principal component analysis, K-means clustering

CLC Number: 

  • U469.5

Fig.1

Data collection equipment and flow"

Fig.2

Flow chart of data processing"

Table 1

Characteristic parameters and definition"

特征参数定义
Vda/(km·h-1平均行驶速度
aam/(m·s-2最大加速度
adm/(m·s-2最大减速度
aaa/(m·s-2加速度段平均加速度
ada/(m·s-2减速度段平均减速度
t/s持续时间
Pa/%加速比例
Pd/%减速比例
Pi/%怠速比例
va/(km·h-1平均速度
vm/(km·h-1最大速度
vd/(km·h-1速度标准差
ad/(m·s-2加速度标准差

Table 2

Characteristic parameters of kinematic segments"

片段VdaaamadmaaaadaPaPdPivatvmvdad
155-42.40-3.000.220.170.571.962262.552.00
24.66-63.50-3.500.110.110.740.731872.052.09
338.56-71.40-1.500.250.220.5234.083334714.891.19
??????????????
15545.26-44.50-2.250.280.160.550.524971.621.21
155538.17-41.35-1.380.280.290.4136.203226619.261.16
155647.97-61.32-1.710.380.330.2947.101756114.501.49
??????????????
300531.78-72.18-2.180.280.450.2528.201005015.602.20
300631.75-61.93-2.480.330.330.0026.90794515.502.00

Fig.3

Characteristic values and total contribution of principal component"

Table 3

Principal component load matrix"

特征

参数

第一

主成分

第二

主成分

第三

主成分

第四

主成分

Vda0.914-0.2480.233-0.054
aam0.4480.2700.4840.375
adm-0.500-0.169-0.5500.255
aa-0.4670.5690.4850.134
ada0.359-0.530-0.4860.424
va0.7000.439-0.426-0.165
vm0.5560.610-0.3910.342
Pa-0.679-0.5610.441-0.084
Pd0.910-0.2460.1980.050
Pi0.391-0.3900.4110.496
t0.936-0.2130.176-0.115
vd0.800-0.041-0.012-0.436
ad0.0620.9280.2360.061

Fig.4

K-means clustering result"

Table 4

Each micro-trip cluster center and category"

片段类别中心
12类3.29
22类3.42
31类12.41
42类4.95
53类20.43
???
14582类3.62
14591类7.62
???
30051类5.32
30061类2.96

Fig.5

Frequency distribution of maximum speed"

Fig.6

Representative driving cycle"

Table 5

Characteristic parameters of typical cycles"

工况类型平均速度 /(km·h-1加速比例/%减速比例/%匀速比例/%怠速比例/%
ECE-1517.8217.5617.5629.2735.61
NEDC33.6023.8117.6334.7523.81
FTP-7534.1028.8525.6026.4519.09
JAPAN10-1517.7025.9026.4022.2025.40
沈阳乘用车29.7425.0021.9423.6729.39
哈尔滨公交车14.4934.3834.458.8622.30
北京市重型客车25.7325.3021.3728.6524.68
北京市重型卡车35.3727.5921.6536.7614.00
宁波重型危险品半挂车34.1828.1123.9647.920.01
1 Peng Y H, Zhuang Y, Yang H B. Development of a representative driving cycle for urban buses based on the K-means cluster method[J]. Cluster Computing, 2018, 22(2): 1-10.
2 Shen P, Zhao Z, Li J. Development of a typical driving cycle for an intra-city hybrid electric bus with a fixed route[J]. Transportation Research Part D: Transport Environment, 2018, 59: 346-360.
3 罗玉涛, 胡红斐, 沈继军. 混合动力电动汽车行驶工况分析与识别[J]. 华南理工大学学报: 自然科学版, 2007, 35(6): 12-17.
Luo Yu-tao, Hu Hong-fei, Shen Ji-jun. Numerical simulation of pyrogenation regeneration process in particulate filter of vehicle diesel[J]. Journal of South China University of Technology(Natural Science Edition), 2007, 35(6): 12-17.
4 Chauhan B P, Joshi G J, Parida P. Driving cycle analysis to identify intersection influence zone for urban intersections under heterogeneous traffic condition[J]. Sustainable Cities and Society, 2018, 41: 180-185.
5 Zhao X, Ma J, Wang S, et al. Developing an electric vehicle urban driving cycle to study differences in energy consumption[J]. Environmental Science and Pollution Research, 2019, 26(14): 13839-13853.
6 Kim W G, Kim C K, Lee J T, et al. Characteristics of nanoparticle emission from a light-duty diesel vehicle during test cycles simulating urban rush-hour driving patterns[J]. Journal of Nanoparticle Research, 2018, 20(4): 1-94.
7 Rady J, O'Mahony M. Development of a driving cycle to evaluate the energy economy of electric vehicles in urban areas[J]. Applied Energy, 2016, 177(9): 165-178.
8 Zc A, Rui X, Cw C, et al. An on-line predictive energy management strategy for plugin hybrid electric vehicles to counter the uncertain prediction of the driving cycle[J]. Applied Energy, 2017, 185(2): 1663-1672.
9 He H W, Guo J Q, Peng J K, et al. Real-time global driving cycle construction and the application to economy driving pro system in plug-in hybrid electric vehicles[J]. Energy, 2018, 152(6): 95-107.
10 Abas M A, Rajoo S, Abidin S F Z. Development of Malaysian urban drive cycle using vehicle and engine parameters[J]. Transportation Research Part D: Transport and Environment, 2018, 63(8): 388-403.
11 胡志远, 秦艳, 谭丕强, 等. 基于大样本的上海市乘用车行驶工况构建[J]. 同济大学学报: 自然科学版, 2015, 43(10): 1523-1527.
Hu Zhi-yuan, Qin Yan, Tan Pi-qiang, et al. Large-sample-based car-driving cycle in shanghai city[J]. Journal of Tongji University(Natural Science), 2015, 43(10): 1523-1527.
12 郑殿宇, 吴晓刚, 陈汉, 等. 哈尔滨城区乘用车行驶工况的构建[J]. 公路交通科技, 2017, 34(4): 101-107.
Zheng Dian-yu, Wu Xiao-gang, Chen Han, et al. Construction of driving conditions of Harbin urban passenger cars[J]. Journal of Highway and Transportation Research and Development, 2017, 34(4): 101-107.
13 张宏, 姚延钢, 杨晓勤. 城市道路轻型汽车行驶工况构建 [J]. 西南交通大学学报, 2019, 54(6): 1139-1154.
Zhang Hong, Yao Yan-gang, Yang Xiao-qin. Light-duty vehicles driving cycle construction based on urban roads[J]. Journal of Southwest Jiaotong University, 2019, 54(6): 1139-1154.
14 孙强, 白书战, 韩尔樑, 等. 基于试验测量的瞬时行驶工况构建[J].吉林大学学报: 工学版, 2015, 45(2): 364-370.
Sun Qiang, Bai Shu-zhan, Han Er-liang, et al. Instantaneous driving cycle construction based on experimental measurement[J]. Journal of Jilin University(Engineering and Technology Edition), 2015, 45(2): 364-370.
15 石琴, 仇多洋, 吴靖. 基于主成分分析和 FCM 聚类的行驶工况研究[J]. 环境科学研究, 2012, 25(1): 70-76.
Shi Qin, Qiu Duo-yang, Wu Jing. Study on driving cycles based on principal component analysis and fuzzy c-means clustering[J]. Research of Environmental Sciences, 2012, 25(1): 70-76.
16 曹骞, 李君, 刘宇, 等. 基于马尔科夫链的长春市乘用车行驶工况构建[J]. 吉林大学学报: 工学版, 2018, 48(5): 1366-1373.
Cao Qian, Li Jun, Liu Yu, et al. Construction of driving cycle based on Markov chain for passenger car in Changchun City[J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1366-1373.
17 Gong H, Zou Y, Yang Q, et al. Generation of a driving cycle for battery electric vehicles: a case study of Beijing[J]. Energy, 2018, 150: 901-912.
18 秦大同, 詹森, 漆正刚, 等. 基于K-均值聚类算法的行驶工况构建方法[J]. 吉林大学学报: 工学版, 2016, 46(2): 383-389.
Qin Da-tong, Zhan Sen, Qi Zheng-gang, et al. Driving cycle construction using k-means clustering method[J]. Journal of Jilin University(Engineering and Technology Edition), 2016, 46(2): 383-389.
19 Esteves-Booth A, Muneer T, Kubie J, et al. A review of vehicular emission models and driving cycles[J]. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2002, 216(8): 777-797.
20 曹骞, 李君, 刘宇, 等. 基于大数据和马尔科夫链的行驶工况构建[J]. 东北大学学报: 自然科学版, 2019, 40(1): 80-84.
Cao Qian, Li Jun, Liu Yu, et al. Construction of driving cycle based on big data and Markov chain[J]. Journal of Northeastern University(Natural Science), 2019, 40(1): 80-84.
21 胡宸, 吴晓刚, 李晓军, 等. 哈尔滨城市公交工况的构建[J]. 哈尔滨理工大学学报, 2014, 19(1): 85-89.
Hu Chen, Wu Xiao-gang, Li Xiao-jun, et al. Construction of Harbin city driving cycle[J]. Journal of Harbin University of Science and Technology, 2014, 19(1): 85-89.
22 杨小娟, 王建. 北京市重型客车行驶工况的构建与研究[J]. 环境工程技术学报, 2015, 5(6): 455-463.
Yang Xiao-juan, Wang Jian. Construction and research of heavy-coach's driving cycle in Beijing city[J]. Journal of Environmental Engineering Technology, 2015, 5(6): 455-463.
23 王军方, 丁焰, 王爱娟, 等. 北京市机动车行驶工况研究[J]. 环境工程技术学报, 2012, 2(3): 240-246.
Wang Jun-fang, Ding Yan, Wang Ai-juan, et al. Study of vehicle driving cycle modes on road in Beijing[J]. Journal of Environmental Engineering Technology, 2012, 2(3): 240-246.
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