福州地区汽车行驶工况构建与研究

Construction and Research of Vehicle Driving Cycle in Fuzhou Area

为了构建汽车行驶工况模型和汽车运动特征评估体系,连续采集了三周福州地区的行驶数据进行处理,将处理后的数据进行运动学片段的划分。采用K-均值聚类分析法对降维的主成分特征值进行聚类,根据距离最小原则挑选出运动学片段来合成反映不同交通状况的汽车行驶工况曲线。并对汽车行驶工况曲线进行分析评价,由此论证了该方法构建汽车行驶工况曲线的合理性。

In order to construct a vehicle driving cycle model and a vehicle motion characteristic evaluation system,continuously collected driving data for three weeks in Fuzhou area for processing,divided the processed data into kinematic segments.Then,the K-means clustering analysis is used to cluster the dimensionality-reduced principal component feature values,and the kinematics segments are selected according to the principle of minimum distance to synthesize the driving cycle curves reflecting different traffic conditions.The analysis and evaluation of the vehicle driving cycle curve are performed,and the rationality of the method to construct the vehicle driving cycle curve is demonstrated.