基于大样本的上海市乘用车行驶工况构建

Large sample based Car driving Cycle in Shanghai City

摘要:

进行了10辆车12个月连续道路行驶数据采集，获得7 137 017条有效行驶数据，从中提取13 789个实际道路行驶运动学片段，通过主成分分析和聚类分析将运动学片段特征值进行降维和分类处理，利用相关系数提取代表性行驶工况，构建了基于大样本、符合上海市交通特征、长度为1 163 s的上海市乘用车行驶工况.结果表明：上海市乘用车行驶工况具有平均速度低、怠速比例高、匀速比例低等特点，与新欧洲测试循环(NEDC)存在较大差异，采用NEDC工况开展的污染物测试不能完全反映上海市的实际交通状况，应建立反映上海市交通特点的乘用车行驶工况.

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.