Comparison and Analysis of Real Driving Emissions with Different Processing Methods and Driving Behaviors from a Light-Duty Gasoline Vehicle 2022-01-0573

Real driving emission (RDE) tests are influenced by factors such as data processing methods, driving behaviors, and environmental conditions. Therefore, being able to effectively identify test influence factors is particularly important for RDE emissions-based calibrations. In order to investigate the correlation between data processing methods, driving behaviors and vehicle emissions, the moving average window (MAW) method and cumulative averaging (CA) method were used to compare and analyze the RDE tests data of a light-duty gasoline vehicle under different driving modes in this study. The results showed that in MAW method, carbon monoxide (CO) emissions of urban and total trips calculated by using the front to back window division order were slightly lower compared to the back to front window division order, with an average reduction of 4.68% and 6.33%, respectively. For carbon dioxide (CO₂) emissions, the order of window division had the opposite effect as for CO emissions. For nitrogen oxides (NO_X) and particle number (PN) emissions, the window division order was stochastic for them. In normal driving mode, the NO_X, CO and PN emissions of urban trip calculated by the CA method were higher than those calculated by the MAW method, while the opposite was true in aggressive driving mode. In addition, for the same RDE trip, the NO_X, CO, CO₂ and PN emissions of total trip calculated by the CA method were on average 7.40%, 21.13%, 2.14% and 19.79% higher than those calculated by the MAW method for both normal and aggressive driving modes, respectively. In the China VI RDE emission certification, it was easier to make NO_X and PN emissions meet the regulatory requirements by using the normal driving mode. In Euro VI RDE emission certification, the choice of driving mode had a random effect on whether vehicles passed the emission certification or not.