Development of China Light-duty Passenger Car Test Cycle

Abstract

Abstract:

This paper presents the China Light- duty Passenger car Test Cycle (CLTC), developed under the "China Automobile Test Cycle Development" project. First, 16 million kilometers of driving data of light- duty passenger cars are collected from 41 cities nationwide in total, and the traffic volume data for each city are also collected to develop weighting factors. Then, the driving data and weighting factors are combined to develop unified speed- acceleration distributions representing the driving behavior in our country. Finally, based on the unified speed- acceleration distributions, the optimal short trip combination is selected by the chi- square test method and the China Light-duty Passenger car Test Cycle (CLTC) is constructed. Through the geo-information system (GIS) weighted results based on real data, the CLTC characteristics are compared with other typical cycles, and the comparison results demonstrate that CLTC conforms better to the reality in China.

Key words: highway transportation, passenger car, weighting factor, unified speed-acceleration distribution, chi-square test

摘要：

依托“中国工况”项目，对我国乘用车行驶工况进行深入研究. 在全国41 个城市采集乘用车共计1 600 万km的行驶数据，收集各城市交通量大数据用于权重因子开发；利用权重因子对采集数据进行加权，获取代表我国驾驶特征的、统一的速度—加速度分布，以其为基准，使用卡方检验选择最优短片段组合作为我国乘用车行驶工况(CLTC). 对比CLTC工况特征与其他典型工况及实测数据GIS加权结果，CLTC工况更符合我国实际.

关键词: 公路运输, 乘用车, 权重因子, 统一的速度&mdash, 加速度分布, 卡方检验

CLC Number:

U491

LIU Yu, WU Zhi-xin, LI Meng-liang, YU Han-zheng-nan,. Development of China Light-duty Passenger Car Test Cycle[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(3): 233-240.

刘昱，吴志新，李孟良，于晗正男，汪洋，贺可勋，安晓盼. 中国乘用车工况构建[J]. 交通运输系统工程与信息, 2020, 20(3): 233-240.

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URL: http://www.tseit.org.cn/EN/abstract/abstract20071.shtml

http://www.tseit.org.cn/EN/Y2020/V20/I3/233

References

[1] TSOKOLIS D, DIMARATOS A, SAMARAS Z, et al. Quantification of the effect of WLTP introduction on passenger cars CO2 emissions[J]. Journal of Earth Sciences and Geotechnical Engineering, 2017, 7(1): 191-214.

[2] 程颖, 陈艳艳, 刘莹, 等. 城市交通排放高分辨率分析方法研究：北京实证[J]. 交通运输系统工程与信息, 2018, 18(2): 236-244. [CHENG Y, CHEN Y Y, LIU Y, et al. A method of high-resolution of urban traffic emission for pollution control: A case study in Beijing [J]. Journal of Transportation Systems Engineering and Information Technology, 2018, 18(2): 236-244.]

[3] 马志雄, 朱西产, 李孟良, 等. 动态聚类法在车辆实际行驶工况开发中的应用[J]. 武汉理工大学学报, 2005, 27(11): 69- 71. [MA Z X, ZHU X C, LI M L, et al. Application of dynamic cluster to the development of vehicle real world driving cycle[J]. Journal of Wuhan University of Technology, 2005, 27(11): 69-71.]

[4] 李友文. 混合交通环境下行驶工况构建方法的研究 [D]. 合肥: 合肥工业大学, 2010. [LI Y W. Research on construction of driving cycle under mixed traffic condition[D]. Hefei: Heifei University of Technology, 2010.]

[5] 杨延相, 蔡晓林, 杜青, 等. 天津市道路汽车行驶工况的研究[J]. 汽车工程, 2002, 24(3): 200-204. [YANG Y X, CAI X L, DU Q, et al. Investigation into vehicle driving mode in Tianjin[J]. Automotive Engineering, 2002, 24(3): 200-204.]

[6] 姜平, 石琴, 陈无畏, 等. 基于小波分析的城市道路行驶工况构建的研究[J]. 汽车工程, 2011, 33 (1): 70-73. [JIANG P, SHI Q, CHEN W W, et al. A research on the construction of city road driving cycle based on wavelet analysis[J]. Automotive Engineering, 2011, 33 (1): 70- 73.]

[7] 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 J F, DING Y, WANG A J, et al. Study of vehicle driving cycle modes on road in Beijing[J]. Journal of Environmental Engineering Technology, 2012, 2(3): 240-246.]

[8] 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 D T, ZHAN S, QI Z G, et al. Driving cycle construction using K-means clustering method[J]. Journal of Jilin University(Engineering and Technology Edition), 2016, 46(2): 383-389.]

[9] PENG Y, ZHUANG Y, YANG H. Development of a representative driving cycle for urban buses based on the K-means cluster method[J]. Cluster Computing, 2019, 22(3): 6871-6880.

[10] 张富兴. 城市车辆行驶工况的研究[D]. 武汉: 武汉理工大学, 2005. [ZHANG F X. Study of driving cycles of city vehicle [D]. Wuhan: Wuhan University of Technology, 2005.]

[11] TUTUIANU M, BONNEL P, CIUFFO B, et al. Development of the World-wide harmonized Light duty Test Cycle (WLTC) and a possible pathway for its introduction in the European legislation[J]. Transportation Research Part D: Transport and Environment, 2015, 40(1): 61-75.

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