Issue |
E3S Web of Conf.
Volume 402, 2023
International Scientific Siberian Transport Forum - TransSiberia 2023
|
|
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Article Number | 04001 | |
Number of page(s) | 9 | |
Section | Automotive Engineering, Engines, Clean Fuels, and E-Mobility | |
DOI | https://doi.org/10.1051/e3sconf/202340204001 | |
Published online | 19 July 2023 |
Development of vehicle driving cycles based on the real traffic dataset
Bauman Moscow State Technical University, 105005 Moscow, Russia
* Corresponding author: potashnikov@bmstu.ru
The paper describes methods for generating (modeling) representative driving cycles of the vehicle used to solve engineering problems in the design of electric vehicles, such as resource calculations, determination of the required capacity of traction batteries and evaluation of power reserve, etc. The general approaches used in the processing of real traffic data and algorithms for modeling driving cycles using deterministic and probabilistic approaches are described. This paper presents driving cycles that ensure convergence with parameters corresponding to the real conditions of vehicle movement. The developed driving cycles can be used in the design of electric vehicle transmission components and allow for the analysis of operational properties.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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