Research On Construction Of Urban Bus Driving Cycle And Prediction Of Emission Inventory In Haikou City

With the rapid development of urban transportation,energy and environmental issues are becoming more and more significant.As an important part of public transportation,city buses emission inventory and emission trend based on big data of bus driving cycle,which can provide important data basis for medium and long-term pollutant control in urban vehicles,and provide important reference for the formulation of energy conservation and emission reduction policies.The city buses of Haikou City were selected as the research object,and the original data was processed by statistical methods to construct the driving cycle of Haikou City.Based on the IVE model,a city bus emission inventory was established,and the calibration of the emission inventory was completed by portable emission measurement system.Based on this,the emission trends of various types of emissions under the three scenarios are predicted separately,and the following contents are included in the study:(1)Bus driving data was collected by vehicle data recorder,and kinematic segments containing a series of characteristic parameters were extracted.Four different driving conditions cycles were constructed based on four different clustering algorithms.After correlation verification,two-step clustering,K-means clustering,particle swarm optimization clustering,and SOM clustering algorithm can well reflect the actual driving cycle of Haikou bus,and the driving cycle constructed by the SOM clustering algorithm are closest to the experimental data.It can be seen from the driving cycle that the speed of Haikou bus is significantly higher than that of first class cities,with a uniform rate of 25.8%,which is higher than other cities;the idle speed is 17.2%lower than other cities.(2)Based on the data of bus driving cycle in Haikou City,other input parameters such as the technical level distribution,oil parameters and environmental parameters required for the calculation of the emission inventory are obtained by investigation,and the 2017 Haikou bus emission inventory was established by the localized model.The emission inventory was verified and calibrated by the portable emission measurement system,and annual emissions of VOCs,NOx,CO and PM in Haikou buses are 1252t,1071t,33404t and 26t respectively.(3)Emissions trend prediction set three different scenarios:baseline scenarios,improved emission standards scenarios and improved emission standards and replacement by electric vehicle scenario.The grey model was used to calculate the amount of various types of vehicles under the three scenarios,and the emission trends under different scenarios were predicted.The results show that the improved emission standards scenarios is expected to reduce VOCs,NOx,CO and PM emissions by 36.6%,34.8%,36.7%,and 64.4%,respectively,in 2025 compared to the baseline scenario.Improved emission standards and replacement by electric vehicle scenario compared to the baseline scenario,VOCs,NOx,CO and PM emissions reduced by 38.0%,40.4%,37.4%,and 73.3%,respectively.