吉林大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (4): 1008-1015.doi: 10.13229/j.cnki.jdxbgxb20170301

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Analysis of state transition characteristics for typical vehicle driving cycles

ZHANG Man, SHI Shu-ming   

  1. College of Transportation, Jilin University, Changchun 130022, China
  • Received:2017-03-23 Online:2018-07-01 Published:2018-07-01

Abstract: In current research of vehicle driving cycles only some parameters are selected as characteristics of the driving cycles, which lacks the analysis of the characteristics of driving cycle state transition. To solve this problem, based on the characteristic parameters extracted from typical driving cycles, this paper adopts the principal component analysis and K-means clustering to obtain three kinds of typical driving cycles, which represent the vehicle driving characteristics under different traffic conditions. The state, transition probability and eigenvalues of the state Transition Probability Matrixes (TPM) under the typical driving cycles are analyzed, and the analysis results are consistent with that of the characteristic parameter analysis under three kinds of typical driving cycles. It is shown that the eigenvalues essentially influences the efficiency of cycle generation of highway, suburb and city roads, revealing the reasonability of construction two-parameter TPM in designing driving cycles.

Key words: vehicle engineering, state transition probability matrix, principal component analysis, K-means clustering, typical driving cycles

CLC Number: 

  • U461.1
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