期刊
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
卷 17, 期 5, 页码 389-397出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trd.2012.03.003
关键词
Real-world driving cycles; Vehicle specific power; Scooter emissions
资金
- Oxford Martin School
This paper develops a robust, data-driven Markov Chain method to capture real-world behaviour in a driving cycle without deconstructing the raw velocity-time sequence. The accuracy of the driving cycles developed using this method was assessed on nine metrics as a function of the number of velocity states, driving cycle length and number of Markov repetitions. The road grade was introduced using vehicle specific power and a velocity penalty. The method was demonstrated on a corpus of 1180 km from a trial of electric scooters. The accuracies of the candidate driving cycles depended most strongly on the number of Markov repetitions. The best driving cycle used 135 velocity modes, was 500 s and captured the corpus behaviour to within 5% after 1,000,000 Markov repetitions. In general, the best driving cycle reproduced the corpus behaviour better when road grade was included. (C) 2012 Elsevier Ltd. All rights reserved.
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