Research on Intelligent Charging Management of New Energy Vehicles Based on Big Data
Pages 148 - 152
Abstract
Aiming at the problem that the low level of intelligent charging management of new energy vehicles leads to poor charging scheduling effect, an intelligent charging management method of new energy vehicles based on big data analysis is proposed. The dynamic charging service algorithm (DCSA) based on Lyapunov was used to perform the charging scheduling on NETs, and charging suggestions were given according to demand. The simulation results show that in terms of passenger demand latency, the latency of DCSA is 19.65%, 22.54% and 16.15% lower than that of NCM, RCM and WPAC algorithms, respectively, thus the proposed algorithm can obtain passenger demand faster. In conclusion, the DCSA scheduling algorithm based on passenger demand performs well in charging management and has certain feasibility.
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Published In
April 2023
296 pages
ISBN:9798400707544
DOI:10.1145/3616901
Copyright © 2023 ACM.
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Association for Computing Machinery
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Publication History
Published: 05 March 2024
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- Research-article
- Research
- Refereed limited
Funding Sources
- Scientific Research Project of Hunan Provincial Department of Education
Conference
FAIML 2023
FAIML 2023: 2023 International Conference on Frontiers of Artificial Intelligence and Machine Learning
April 14 - 16, 2023
Beijing, China
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