摘要
为建立典型城市机动车驾驶模式并量化其尾气排放,研究选取成都市内26辆满足国Ⅴ排放标准(GB 18352.5—2013《轻型汽车污染物排放限值及测量方法(中国第五阶段)》)的轻型汽油车,利用便携式尾气测量系统测量其现实条件下的行驶工况及尾气排放,并根据实际情况结合分类回归树方法构建本地化的驾驶模式并分析各模式的尾气排放。结果表明:划分的加速、减速、匀速、怠速、停走5种驾驶模式,可以反映车辆行驶过程中尾气排放和油耗特征。不同驾驶模式间的尾气排放有显著差异。通常情况下,以加速最大,其次为匀速、停走、减速,以怠速最小。根据污染物不同,不同模式间的尾气排放差异可达到12倍。此外,现实条件下车辆尾气超标排放的情况严重,且存在间歇性高排放的现象。这说明构建典型城市驾驶模式并分析其模式排放特征有助于估算小尺度的机动车尾气排放清单,并为交通管理和尾气排放控制提供数据参考。
The objective of this work was to develop driving modes for a typical city in China and quantify its corresponding emissions. Using Chengdu as an example, twenty-six light-duty gasoline vehicles in compliance with the Phase V national emission standards(GB 18352.5—2013) were selected in this study. A portable emission measurement system(PEMS) was used for driving cycle and real-world emission measurements. The classification and regression tree(CART) was used to develop driving modes for emission modeling. Five driving modes, including acceleration, deceleration, cruise, idle, and stop and go(SNG) were defined and demonstrated to be able to characterize the real-world emissions and fuel consumption. In general, emissions and fuel consumption differ by driving modes with acceleration being the highest, followed by cruise, SNG, deceleration and idling. Depending on pollutant, the ratio of emissions between two different driving modes could be as high as a factor of 12. Furthermore, vehicle emissions from a majority of selected vehicles in this study exceeded its compliance emission standards and were episodic. This indicated that the developed driving modes could be used to characterize vehicle emissions at a high temporal resolution, and develop emission inventory for traffic management and emission control.
作者
殷子渊
张凯山
YIN Zi-yuan;ZHANG Kai-shan(College of Architecture&Environment,Sichuan University,Chengdu 610065,China)
出处
《环境工程》
CAS
CSCD
北大核心
2021年第4期64-71,共8页
Environmental Engineering
基金
国家自然科学基金项目“轻型机动车尾气排放劣化率模型构建及应用研究”(41877395)。
关键词
便携式尾气排放测量系统
轻型汽油车
分类回归树
驾驶模式
排放特征
portable emission measurement system(PEMS)
light-duty gasoline vehicles
classification and regression tree(CART)
driving modes
emission characterization