中文摘要：

目前通常用聚类的方法构建行驶工况，虽然聚类法有很高的精度，但是构建汽车行驶工况的数据含有波动性、不规则性的部分。为了进一步提高构建精度，首先用FCM聚类方法对行驶工况数据进行聚类，然后采用小波变换对构建好的工况进行压缩重构。理论分析及试验结果表明，与用传统方法构建的行驶工况相比，小波变换得到的行驶工况能有效提高所构建行驶工况的精度。

英文摘要：

At present, Clustering Algorithm has been widely used in the construction of the urban vehicle driving cycle. Though Clustering Algorithm has high accuracy, driving cycle data contains fluctuant and irregular parts. In order to further improve the building accuracy, the paper first used Fuzzy C Means （FCM） Algorithm to cluster, and then employed wavelet transformation to compress and reconstruct the urban vehicle driving cycle. The theoretical analysis and experimental results indicate that the driving cycle obtained from wavelet transformation can fully improve the building accuracy in comparison with the traditional method.