A Sticky Sampling and Markov State Transition Matrix Based Driving Cycle Construction Method for EV
نویسندگان
چکیده
Driving cycle (DC) plays an important role in designing and evaluating EVs, many Markov chain-based DC construction methods describe driving profiles of unfixed-line vehicles with state transition probability. However, for fixed-line electric vehicles, the time-sequence microtrips brings huge influences on their brake, drive, battery management systems. Simply describing topography, traffic, location, features, environment a stochastic manner cannot reflect continuity characteristics hidden fixed route. Thus, this paper, we propose sticky sampling matrix based algorithm to both randomness route, which data structure named “driving pulse chain” was constructed sequence scenarios several matrices were random distribution velocity acceleration same scenarios. Simulation experimental analysis show that sliding window chain, proposed can location. At time, nature be preserved.
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ژورنال
عنوان ژورنال: Energies
سال: 2022
ISSN: ['1996-1073']
DOI: https://doi.org/10.3390/en15031057