Large sample based Car driving Cycle in Shanghai City

Abstract:

An on road driving data collection test lasted for 12 months was conducted on 10 taxies in Shanghai. Over 7 137 017 valid driving data were collected and then 13 789 kinematics sequences were extracted from test data, and dimension reduction and sorting treatment of kinematics sequences’ characteristic parameters were performed by principal component analysis and cluster analysis. Then according to the correlation coefficients theory, typical driving cycle fragments were selected and finally a car driving cycle of 1 163 s about the real traffic condition of Shanghai was established based on large sample statistics. The results show that the car driving cycle of Shanghai is characterized by the low average speed, high idling proportion and low cruise proportion, which shows large differences from that of new european driving cycle (NEDC). So the emission test results based on NEDC cannot exactly reflect the real traffic condition in Shanghai, and a car driving cycle based on the traffic characteristics of Shanghai should be developed.