基于多源数据的公交车能耗碳排放测算模型

交通运输系统工程与信息 ›› 2020, Vol. 20 ›› Issue (3): 174-181.

基于多源数据的公交车能耗碳排放测算模型

徐龙^{1, 2}，王力^*1，刘莹²，宋国华³，李晨旭⁴，翟志强⁵

1. 北方工业大学城市道路交通智能控制技术北京重点实验室，北京 100144；2. 北京交通发展研究院，北京 100073；3. 北京交通大学交通运输学院，北京100044；4. 中国民航大学机场学院，天津 300300； 5. 北京公共交通控股(集团)有限公司，北京 100081

收稿日期:2020-02-12 修回日期:2020-03-03 出版日期:2020-06-25 发布日期:2020-06-28
作者简介:徐龙(1988-)，男，江西广丰人，高级工程师，博士生.
基金资助:
国家重点研发计划/National Key Research and Development Program of China (2017YFB0504000)；北京市长城学者培养计划/Beijing GreatWall Scholar(CIT&TCD20190304)；河北省自然科学基金重点项目/Natural Science Foundation of Hebei Province, China(F2016203496).

Calculation Model of Bus Energy Consumption and CO2 Emission Based on Multi-source Data

XU Long^1,2,WANG li¹, LIU Ying², SONG Guo-hua³, LI Chen-xu⁴, ZHAI Zhi-qiang⁵

1. Beijing Key Lab of Urban Intelligent Traffic Control Technology, North China University of Technology, Beijing 100144, China; 2. Beijing Transport Institute, Beijing 100073, China; 3. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China; 4. Airport College of Civil Aviation University of China, Tianjin 300300, China; 5. Beijing Public Transport Corporation, Beijing 100081, China

Received:2020-02-12 Revised:2020-03-03 Online:2020-06-25 Published:2020-06-28

摘要/Abstract

摘要：

公交车能耗碳排放强度与车辆、线路和驾驶员有显著相关关系，为精准刻画其能耗碳排放强度特征，整合OBD监测数据、加油(气)数据、运营排班数据等多源数据资源. OBD监测数据和加油(气)数据呈显著的线性关系，证明修正后的OBD监测数据可满足分析要求. 搭建“速度—能耗碳排放强度曲线”测算模型，幂函数关系的拟合优度R2 =0.972 6 为最高. 实证研究发现，平均速度在10~60 km/h 变化时，液化天然气(LNG)车比柴油车能耗碳排放强度高 3.3%~33.7%，双层车比铰接车高2.4%~13.3%；LNG铰接车在不同线路、相同速度下的强度相差9.6%；不同驾驶员在相同线路的能耗碳排放强度可相差24.2%. 模型为各城市基于多源数据开展公交能耗碳排放目标设定提供数据支撑.

关键词: 城市交通, 速度&mdash, 能耗碳排放强度曲线, 数据融合, 公交车, 驾驶员

Abstract:

The intensity of energy consumption and CO2 emission of buses are closely related to the vehicle type, bus routes and bus drivers. To accurately describe the characteristics of the intensity of energy consumption and CO2 emission, this study integrated multiple data resources for the analysis, which include the on-board diagnostic (OBD) monitoring data, diesel or liquefied natural gas (LNG) refueling data, and driver scheduling data. The strong linear relationship between the OBD monitoring data and the diesel or LNG refueling data indicated that the revised OBD monitoring data is able to meet the evaluation purposes. The Average Speed- Energy and CO2 Intensity Curve Model was developed, having a power function relationship with the goodness of fit ( R2 ) at 0.972 6. The empirical study in Beijing, China provides the following findings: when the average speed of the bus changes from 10 kilometers per hour to 60 kilometers per hour, the intensity of energy consumption and CO2 emission of LNG bus is 3.3% to 33.7% higher than that of the diesel bus, and the intensity of energy consumption and CO2 emission of double-decker bus are 2.4% to 13.3% higher than that of the articulated bus. When the same type of bus was used for different bus routes operating at the same average speed, the intensity of energy consumption can vary by 9.6%. The intensity can vary by 24.2% by different drivers on the same bus route. This study provides references for cities to set up the carbon emission target of bus energy consumption and CO2 emission with multiple data resources.

Key words: urban traffic, average speed-energy and CO2 emission intensity curve, data fusion, bus, bus driver

中图分类号:

U268.6

徐龙，王力，刘莹，宋国华，李晨旭，翟志强. 基于多源数据的公交车能耗碳排放测算模型[J]. 交通运输系统工程与信息, 2020, 20(3): 174-181.

XU Long,WANG li, LIU Ying, SONG Guo-hua, LI Chen-xu, ZHAI Zhi-qiang. Calculation Model of Bus Energy Consumption and CO2 Emission Based on Multi-source Data[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(3): 174-181.

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链接本文: http://www.tseit.org.cn/CN/abstract/abstract20063.shtml

http://www.tseit.org.cn/CN/Y2020/V20/I3/174

参考文献

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