交通路网中重型柴油车油耗和排放多层次分析

交通运输系统工程与信息 ›› 2010, Vol. 10 ›› Issue (5): 123-129 .

交通路网中重型柴油车油耗和排放多层次分析

郝艳召¹;邵春福^*1;于雷^1,2;宋国华¹;胥耀方¹

1.北京交通大学城市交通复杂系统理论与技术教育部重点实验室，北京 100044； 2.德克萨斯南方大学，美国休斯敦 77004

收稿日期:2009-07-17 修回日期:2009-10-27 出版日期:2010-10-25 发布日期:2010-10-25
通讯作者: 邵春福
作者简介:郝艳召（1981-），男，河北人；博士生.
基金资助:
国家自然科学基金(50878017)；教育部博士点基金(T06C10020).

Multi-Level Analysis of Fuel Consumption and Emissions of Heavy-Duty Diesel Vehicles in Road Network

HAO Yan-zhao¹; SHAO Chun-fu¹; YU Lei ^1,2;SONG Guo-hua¹;XU Yao-fang¹

1.MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China; 2.Texas Southern University, Houston, Texas 77004, U.S.A.

Received:2009-07-17 Revised:2009-10-27 Online:2010-10-25 Published:2010-10-25
Contact: SHAO Chun-fu

摘要/Abstract

摘要： 利用车载尾气检测系统（PEMS）进行北京市交通路网中重型柴油车实时油耗、排放和行驶数据收集，并从微观、中观和宏观三个层次对动态交通网络中的油耗和排放规律及其影响因素进行深入分析. 行驶特征分析表明：重型柴油车在低、中速状态下行驶时间最长；在中速状态下行驶里程最长；同时匀速工况下的行驶时间和里程所占比例最高. 油耗和排放分析表明：重型柴油车（国III）平均油耗水平为18.6L／100km，NOx和PM污染水平分别为4.63g／km和0.087g／km. 其中在微观层次，高速和高加速是引起车辆瞬时高油耗和排放的主要原因；在中观层次，怠速和低速行驶是造成单位距离高油耗和排放的主要原因；在宏观层次，行驶里程是总油耗和排放评估的一个重要影响参数.

关键词: 公路运输, 交通环境污染, 重型柴油车, 油耗和排放规律, 行驶特征, 车载尾气检测

Abstract: Real-world fuel consumption, emission, and driving activity data from heavy-duty diesel vehicles (HDDVs) were collected using the portable emission measurement system (PEMS) in the road network of Beijing. Then, the fuel consumption and emission characteristics were analyzed at microscopic, mesoscopic as well as macroscopic levels. The analysis results on driving behaviors showed that the driving time was mainly distributed in low and middle-speed bins, 〖JP2〗the driving mileage was mainly located in middle-speed bins, and the driving time and mileage under cruise mode accounted for the highest proportion. The analysis results on fuel consumption and emission characteristics showed that the average level of fuel consumption was 18.6 L/100 km, the average emission factors of NOx and PM were 4.63 g/km and 0.087 g/km for HDDVs that met the Euro III standard. At the microscopic level, driving at high-speed and acceleration is associated with the instantaneous high fuel consumption and emission rates. At the mesoscopic level, idling or driving at low-speed was the main reason of high fuel consumption and emission factors. At the macroscopic level, driving mileage was a significant influencing factor for total fuel consumption and emissions.

Key words: highway transportation, traffic environmental pollution, heavy-duty diesel vehicle, fuel consumption and emissions, driving behavior, portable emission measurement system

中图分类号:

U491

郝艳召,邵春福,于雷,宋国华,胥耀方. 交通路网中重型柴油车油耗和排放多层次分析[J]. 交通运输系统工程与信息, 2010, 10(5): 123-129 .

HAO Yan-zhao, SHAO Chun-fu, YU Lei,SONG Guo-hua,XU Yao-fang. Multi-Level Analysis of Fuel Consumption and Emissions of Heavy-Duty Diesel Vehicles in Road Network[J]. Journal of Transportation Systems Engineering and Information Technology, 2010, 10(5): 123-129 .

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链接本文: http://www.tseit.org.cn/CN/abstract/abstract18046.shtml

http://www.tseit.org.cn/CN/Y2010/V10/I5/123

参考文献

［1］北京汽车研究所有限公司. 北京柴油车颗粒物排放治理技术指南［R］. 北京: 北京市环保局, 2007. ［Beijing Automotive Research Institute Co., Ltd. Technical guide of particulate emissions control for diesel vehicles in Beijing［R］. Beijing: Beijing Municipal Environmental Protection Bureau, 2007.］
［2］Tao Huai, Sandip D, Shah, Wayne Miller J, et al. Analysis of heavy-duty diesel truck activity and emissions data［J］. Atmospheric Environment, 2006, 40(13): 2333-2344. 
［3］GB 17691-2005, 车用压燃式、气体燃料点燃式发动机与汽车排气污染物排放限值及测量方法（中国III、IV、V阶段）［S］. 北京: 中国环境科学出版社, 2005.［GB 17691-2005, Limits and measurement methods for exhaust pollutants from compression ignition and gas fuelled positive ignition engines of vehicles (III, IV, and V)［S］. Beijing: China Environmental Science Press, 2005.］
［4］李孟良, 刘伏萍, 陈燕涛, 等. 基于PEMS的混合动力客车排放和油耗性能评价［J］. 江苏大学学报（自然科学版）, 2006, 27(1): 27-30.［LI M L, LIU F P, CHEN Y T, et al. Study on emission and fuel consumption of hybrid-power bus based on portable emission measurement system［J］. Journal of Jiangsu University (Natural Science Edition), 2006, 27(1): 27-30.］
［5］刘娟, 于雷. 北京市实时尾气数据收集的探索与实践［J］. 交通环保, 2004, 25(6): 13-15.［LIU J, YU L. Exploratory application of real-time vehicle emission data collection in Beijing［J］. Traffic Environmental Protection, 2004, 25(6): 13-15.］
［6］裴文文, 于雷, 杨方, 等. 北京市机动车行驶周期建立方法研究［J］. 交通环保, 2004, 25(3): 20-23.［PEI W W, YU L, YANG F, et al. Development of vehicle driving cycles for Beijing［J］. Traffic Environmental Protection, 2004, 25(3): 20-23.］
［7］Sandip D, Shah, Kent C. Johnson, Wayne Miller J, et al. Emission rates of regulated pollutants from on-road heavy-duty diesel vehicles［J］. Atmospheric Environment, 2006, 40(1): 147-153. 
［8］张雪莲. 大城市路网运行状态分层次评价模型［D］. 北京: 北京交通大学, 2008.［ZHANG X L. Multi-level models to measure road network operational conditions for megapolises［D］. Beijing: Beijing Jiaotong University, 2008.］

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