Comparative analysis of light-duty vehicle emission model
Using OEM-2100 to build light-duty vehicle testing platform and test on actual road, vehicle emission factors were analyzed by regression and neural network method, the emission model between speed, acceleration and mass emission rate was established, and the emissions data error based on actual road emissions was calculated. The results indicate that the establishment of emission model can predict the actual instantaneous mass emission rate, the total error of speed regression model, and the binary regression model and the neural network model can predict vehicle emissions with the error less than 17%, while the second based error is about 30%, and the emission model can merge with traffic simulation model to evaluate traffic control measures under different operating conditions in motor vehicle emissions.
国家科技期刊平台
NSTL
万方数据
维普
