Study On Emission Characteristics Of Normal Transit Exhaust Based On Bus Operation States

Green traffic is an important goal of the development of transportation industry.public transport priority can not only maximum utilization rate of roads,but also play an important role on energy saving and emission reduction.In recent years,new energy bus,such as electric bus and hybrid bus,has been vigorously promoted.It reduces exhaust emissions and plays an important role on the improvement of urban environmental quality.Data processing is the foundation and one of the difficulties of this paper.In the process of data preprocessing,linear interpolation is used to interpolate the data,which makes the GPS data and the emission data more easily integrated.The method for the determination of idle node position,the idea of pattern recognition is adopted,and the idle node identification rate of the hybrid bus line is as high as 90%.After processing the data,the first comparison including liquefied natural gas(LNG)emission of diesel and diesel,the National IV emission and hybrid of different fuel and emission standards,CO,C02,HC and NOX emission characteristics,the results show that the hybrid electric bus exhaust minimum emissions,National IV emission standard buses far more environmentally friendly than China III,and pollution emissions in the gas C02 and HC liquefied natural gas vehicle at the maximum of four vehicles.When the comparison of emission characteristics of different fuel types is finished,oil and gas hybrid buses were selected to predict the emission in real time.After the vehicle specific power(VSP)is discretized,the mass emission rate of various exhaust gases is modeled by the driving state and the idle state.Among them,the rate of exhaust emission status of mass prediction modeling on traffic,using the method of model tree depth of data mining;and the node idle exhaust gas mass emission rate prediction,using the method of the mean.On this basis,the emission mass prediction model is established for a given period of time.Compared to methods in other papers,method in this paper has the highest degree of accuracy not only on mass emission rate prediction,but also on emission mass prediction.This shows the reliability of the method.