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Emission Factors Determination of Euro III 1,200- to 1,400-cc Petrol Passenger Cars with a PLS Multivariate Regression Model

机译:用PLS多元回归模型确定欧III 1200至1400 cc汽油乘用车的排放因子

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摘要

This paper presents emission factors of a class of passenger cars obtained by applying a statistical model developed to evaluate average emission factors based on driving cycle emission measurements. A multivariate regression method based on principal components, namely, the partial least squares (PLS) method, is applied to calculate the model. The method was applied to emission data from a sample of petrol Euro III 1,200- to 1,400-cc passenger cars taken from the ARTEMIS database. A vehicle effect analysis showed that vehicle effect is considerable, in some cases comparable to or greater than the driving cycle effect. Determination of emission factors is obviously affected by these aspects. Thus, the CO2 PLS model fit results are good, CO, HC and NOX more or less sufficient. PLS-predicted quantities were compared with corresponding quantities estimated by a multiple regression model (GLM) based on a quadratic polynomial equation of sub-cycle overall mean speed. GLM goodness of fit was poorer than PLS ones. A validation effort of models is in progress, which is considering the ARTEMIS database extended with tests performed within other national or international projects. In this way, an extended population of combinations of vehicles and driving cycles will provide a better calculation of models and emission factors.
机译:本文介绍了通过应用统计模型获得的一类乘用车的排放因子,该统计模型是根据驾驶循环排放测量结果评估平均排放因子而得出的。应用基于主成分的多元回归方法,即偏最小二乘(PLS)方法来计算模型。该方法已应用于从ARTEMIS数据库中获得的欧III 1200至1400 cc汽油乘用车样本的排放数据。车辆效果分析表明,车辆效果相当好,在某些情况下可媲美或大于驾驶循环效果。排放因子的确定显然受这些方面的影响。因此,CO2 PLS模型拟合结果良好,CO,HC和NOX或多或少都足够。基于子循环总体平均速度的二次多项式方程,将PLS预测的量与通过多元回归模型(GLM)估算的对应量进行比较。 GLM拟合优度比PLS差。模型的验证工作正在进行中,正在考虑将ARTEMIS数据库扩展为在其他国家或国际项目中进行的测试。这样,车辆和驾驶循环组合的扩展人群将提供对模型和排放因子的更好计算。

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