@inproceedings{2c556501d44d45dba15c478e070dccad,
title = "Charging Strategy of Electric Vehicle Based on Multi-dimensional Characteristics",
abstract = "This paper proposes an charging strategy research for electric vehicles based on multi-dimensional characteristics, which is an orderly charging strategy based on multi-dimensional characteristics such as electric vehicle charging and charging facility operation. Considering the load of grid system and the safe driving of electric vehicles, the vehicle dynamic operation data, vehicle static data and vehicle charging data are matched with the static parameters of the charging pile of the charging station, and the dynamic operation data are based on the time, space, and energy supply and demand relationship, and the charging station is sorted by the aggregation recommended algorithm considering the charging time consumption and the economic benefits of the charging station operator, According to the results, guide the user to find the most suitable charging station.",
keywords = "Charging guidance, Dynamic aggregation, Electric vehicle",
author = "Peng Liu and Boyuan Cao and Yang, {Xin Gang} and Zhenpo Wang and Encheng Zhou",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 7th International Conference on Computing, Control and Industrial Engineering, CCIE 2023 ; Conference date: 25-02-2023 Through 26-02-2023",
year = "2023",
doi = "10.1007/978-981-99-2730-2_22",
language = "English",
isbn = "9789819927296",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "221--232",
editor = "{S. Shmaliy}, Yuriy and Anand Nayyar",
booktitle = "7th International Conference on Computing, Control and Industrial Engineering, CCIE 2023 - Advances in Computing, Control and Industrial Engineering VII",
address = "Germany",
}