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为了构建乘用车微观排放模型,采用便携式车载排放测量仪(OEM-2100)搭建了车载排放测试试验平台,并选取由长春4条主干路组成的环路为试验路段进行了实车道路试验。通过试验获取试验车质量排放数据与对应的行驶状态参数,分析车辆行驶过程中的排放影响因素,建立了车辆瞬时排放率基于速度的一元回归模型和基于速度-比功率的二元回归模型。对比分析2种模型对试验车排放特性预测误差,基于速度-比功率的二元回归模型的准确性高于速度一元回归模型,整体误差小于15%,可有效预测不同交通状态下乘用车的排放特性。
In order to build a micro-emission model for passenger cars, a portable vehicle-mounted emission meter (OEM-2100) was used to build an on-board emission test platform and a loop consisting of four main roads in Changchun was selected as the test road to carry out real-vehicle road tests. Through the experiment, the vehicle emission data and the corresponding driving state parameters were obtained. The influencing factors of vehicle emissions were analyzed. A speed-based univariate regression model of vehicle instantaneous emission rate and a binary regression model based on speed-specific power were established. Comparing the prediction errors of the two models on the emission characteristics of the test vehicle, the accuracy of the binary regression model based on the speed-specific power is higher than that of the speed one-component regression model, the overall error is less than 15%, which can effectively predict the passenger vehicle emissions under different traffic conditions Emissions characteristics.