Automobile Emission Distribution Based on the Quadratic Kalman Filter Correction

It is extremely urgent to monitor vehicle exhaust emissions and formulate scientific emission reduction measures. How to respond to changes in emissions distribution caused by changes in traffic demands is the core issue in establishing a distribution model for exhaust emissions. According to the idea of "transfer of traffic demand-determination of vehicle specific power parameters-traffic emissions", the vehicle's specific power parameters were used to calibrate quantitative relationship between traffic demands and the exhaust gas emission. Based on the traffic demand data, the traffic flow state data and traffic distribution data were corrected by the quadratic Kalman filter (QKF), and the real-time vehicle operating condition parameters were obtained through dynamic traffic assignment, which matches the typical vehicle operating condition curve to determine the vehicle specific power at different speeds. The interval distribution, and then the vehicle driving characteristic parameters were substituted into the international vehicle emission (IVE) model to determine the emission factor, and the vehicle exhaust emissions in the area were calculated. Results show that the average relative error of traffic demand is estimated by 8.89% using the QKF for 15 minutes, and the simulation with IVE tail gas model has better reliability. The prediction results show that it is feasible to realize the traffic pollution distribution model constructed based on the driving conditions of dynamic traffic demand, and the QKF correction provides the guarantee of accuracy. The deductive data can be used to analyze the distribution of exhaust gas and evaluate traffic improvement measures. The impact on tail gas emissions provides a basis for developing emission reduction strategies.