Study On Emission Deterioration Model Of Light Duty Vehicles

In recent years,the number of motor vehicles in China is rising,which has caused increasingly serious environmental pollution.Research has shown that 20% of vehicles with deteriorating technical conditions contribute 60% of pollutant emissions.Therefore,the key to emission control lies in the identification and management of high emission vehicles.With the usage of vehicles and the aging of emission control system,emissions will rise continuously,which is recognized as emission deterioration.Exploring the characteristics and factors of emission deterioration and establishing emission deterioration model provides a reliable basis for accurate high emission vehicle identification and vehicle emission prediction in urban area.Based on the annual inspection data of light gasoline vehicles(LGVs)of Nanjing in 2018,this study analyzed the overall technical distribution and emission characteristics of in-use LGVs in Nanjing.According to emission concentration,K-means clustering algorithm was employed to divide the vehicles into three categories: low,medium and high emission vehicles.Comparing the technical distribution of low,medium and high emission vehicles,it was found that high emission vehicles tend to have lower emission standards,higher accumulated mileage,larger vehicle age and smaller engine displacement.Emission level classification model was established by Random Forest Algorithm to predict the emission levels according to technical parameters.A method to quickly identify high emission vehicles was thus proposed.In order to eliminate the influence of other factors on emission concentration and directly reflect its dynamics with accumulated mileage,vehicle model was taken as the classification standard.100 typical vehicle models were selected and their deterioration curves were drawn.Deterioration rate and coefficient were then calculated.The results show that the deterioration curves fit linear or exponential function,and the deterioration of NO is the most significant.Statistical analysis and XGBoost regression model were employed to explore the factors of deterioration.It is found that(1)With the update of emission standards,the deterioration rate declines gradually,while the deterioration coefficient rises;(2)Deterioration coefficient of vehicles with high annual mileage is generally smaller;(3)Deterioration coefficient is negatively correlated with engine displacement and mass,while positively correlated with compression ratio.Based on the investigation of the factors on deterioration,a linear deterioration model was established to reflect the deterioration trend of vehicles with different technical conditions.Taking the average deterioration trend of vehicles under different emission standards as the model benchmark,the effects of engine displacement,compression ratio and annual mileage on deterioration were quantified in the form of correction coefficient.A deterioration model suitable for vehicles with different technical conditions was thus established.Several vehicle models were selected to verify the model,which proved that the accuracy of the model was acceptable and in line with the reality of emission deterioration of LGVs in Nanjing.The model can be applied to predict the trend of vehicle emissions,providing a basis for updating the emission limits.