Atmosphere (Apr 2022)
Development of Vehicle Emission Model Based on Real-Road Test and Driving Conditions in Tianjin, China
Abstract
Based on the demand of vehicle emission research and control, this paper presents the development of a portable vehicle measurement system (PEMS) based on SEMTECH-DS and ELPI+, the vehicle emission tests carried out on actual roads, and the data obtained for the establishment and validation of a vehicle emission model. Based on the results of the vehicle emission test, it was found that vehicle driving conditions (speed, acceleration, vehicle specific power (VSP), etc.) had a significant impact on the pollutant emission rate. In addition, local driving cycles were generated and the frequency distribution of VSP-bin under different cycles was analyzed. Then, through the establishment of an emission rate database, calculation of emission factors and validation of the emission model, a vehicle emission model based on actual road driving conditions was developed by taking VSP as the “surrogate variables”. It showed that the emission factor model established in this study could better reflect the vehicle transient emissions on the actual road with high accuracy and local adaptability. Through this study, it could be found that due to the great differences in traffic development modes and vehicle driving conditions in different cities in China, the emission model based on driving conditions was a better choice to carry out the research on vehicle emission in Chinese cities. Compared with directly applying international models or quoting the recommended values of relevant macroscopic guidelines, the emission factor model established in this study, using actual driving conditions, could better reflect the vehicle transient emissions on the actual road with high accuracy and local adaptability. In addition, due to the rapid development of China’s urban traffic and the rapid change of driving conditions, it was of great significance to regularly update China’s urban conditions to improve the accuracy of the model, no matter which model was chosen.
Keywords