Abstract: Fuzzy clustering based on particle swarm optimization method in vehicle driving cycle is tested in this paper.Principal component analysis is used to reduce the characteristics of the whole kinematic segments,which represents road running characteristics.The scores of the first three principal components of the kinematic segments are classified by using fuzzy clustering based on particle swarm optimization method.Programming with Matlab,the above theory is used to construct and analyze the typical roads in Hefei,and the representative driving cycle is obtained by selecting proper segments according to the ratio of time.The representative driving cycle and driving cycle obtained from k-means clustering and fuzzy cmeans clustering method are compared with the experimental data respectively.The research results shaws that fuzzy clustering based on particle swarm optimization method which is used to construct driving cycle can improve construction precision effectively.

Key words: particle swarm, fuzzy clustering, principal component analysis, k-means clustering, driving cycle