摘要
为量化重型货车车重与比功率分布关系,提高排放测算精度和效率,本文根据有限的本地车辆轨迹数据构建了基于实际车重的重型货车比功率分布及排放模型。首先,基于北京市不同车重的货车轨迹数据构建实际比功率分布。然后,利用高斯函数拟合比功率分布,基于多项式函数量化车重和高斯函数参数的关系,从而构建本文模型。最后,计算NOx排放因子以验证模型排放测算及预测精度,并与既有排放模型MOVES对比阐述车重对货车排放测算的影响。结果表明:本文构建的模型满足一定的排放测算精度,快速路和非快速路的排放测算误差分别为4.7%和7.0%;模型通过输入唯一变量车重即可实现排放预测,降低了不同车重货车轨迹数据采集成本,简化了传统排放计算流程,车重为6.7 t货车的排放预测误差为5.3%;与基于默认固定行驶周期和固定车重的MOVES相比,模型可降低16.7%的排放测算误差。
To quantify the relationship between vehicle weight of Heavy-Duty Trucks(HDT)and Scaled Tractive Power(STP)distribution,and thus improve the accuracy and efficiency of emission estimation,this study develops a model of STP distribution and emission for HDT based on vehicle weight.First,the actual STP distributions are developed based on trajectory data of HDTs with different vehicle weights in Beijing.Then,the STP distributions are fitted by the Gaussian functions,and the relationships between vehicle weight and the parameters of the Gaussian functions are quantified by the polynomial functions to develop the model.Finally,the NOx emission factors are calculated to verify the emission estimation and prediction accuracy of the model,and the impact of vehicle weight on the emission estimation for HDT is elaborated in comparison with the existing emission model MOVES.The results are as follows:(1)The emission estimation accuracy of the model is satisfied.The emission estimation errors of restricted and unrestricted access roads are 4.7%and 7.0%,respectively.(2)The emission can be predicted by the only variable vehicle weight,which reduces the cost of collecting data on the trajectory of HDTs with different vehicle weights and simplifies the traditional emission calculation process,and the emission prediction error of the HDT weighing 6.7 t is 5.3%.(3)Compared with MOVES based on default fixed driving cycles and fixed vehicle weights,the emission error drops by 16.7%according to the developed model.
作者
黄意然
宋国华
彭飞
HUANG Yi-ran;SONG Guo-hua;PENG Fei(Key Laboratory of Big Data Application Technologies for Comprehensive Transport of Transport Industry,Beijing Jiaotong University,Beijing 100044,China)
出处
《交通运输系统工程与信息》
EI
CSCD
北大核心
2023年第2期326-334,共9页
Journal of Transportation Systems Engineering and Information Technology
基金
国家自然科学基金(71871015,71901018)
国家重点研发计划(2018YFB1600701)。
关键词
交通工程
比功率分布
高斯函数
重型货车
车辆重量
排放测算
traffic engineering
STP distribution
Gaussian function
heavy-duty truck
vehicle weight
emission estimation