Journal
INTERNATIONAL WORKSHOP ON AUTOMOBILE, POWER AND ENERGY ENGINEERING
Volume 16, Issue -, Pages -Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.proeng.2011.08.1055
Keywords
Driving cycle; Markov; Maximum likelihood estimation; Random number
Ask authors/readers for more resources
Thinking about the traffic process of vehicle, the change of speech over time is an uncertain variable, the driving cycle of vehicle is studied by the Markov theory in random process, By analysis and calculating a number of experimental data, the transition probability matrix of original data was obtained by maximum likelihood estimation to determine the statistical characteristics of the experimental data then according the constraints of the transfer matrix, a large number of model events were selected from experimental datas randomly to develop a driving cycle. On the theoretical basis of the above, the actual application analysis was carried out with a example of typical roads driving cycles in Hefei, and define 12 characteristic parameters to evaluate the constructed cycle. The results showed that this method is more representative than the traditional method. (C) 2010 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Society for Automobile, Power and Energy Engineering
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available