Research on Vehicle Collaborative Algorithm for Optimizing Intelligent Charging Pile of Electric Vehicles in the Internet of Vehicles Environment

This paper proposes a collaborative optimization algorithm for intelligent charging piles of electric vehicles based on the Internet of Vehicles environment. The algorithm combines the real-time information interaction between vehicles to establish a charging demand prediction model, and designs an intelligent allocation strategy based on multi-objective optimization to improve the utilization efficiency of charging resources. Various influencing factors are considered, including the distribution density of charging piles, the driving trajectory of electric vehicles, and the spatiotemporal distribution of charging demand. In addition, the model simulation is carried out based on MATLAB, and the algorithm performance is analyzed through experimental data to verify the effectiveness of the proposed algorithm in optimizing the utilization rate of charging piles and shortening user waiting time. The simulation results show that compared with the traditional charging pile allocation method, the algorithm can significantly reduce the average waiting time (by about 25%) and improve the overall charging efficiency (by about 15%). Therefore, this study provides strong support for the optimization of charging resources for electric vehicles in the Internet of Vehicles environment, which is conducive to promoting the popularization of electric vehicles and the integrated application of Internet of Vehicles technology.

Authors

Publication Details

Published
2025-01-10
DOI
https://doi.org/10.1109/citsc64390.2025.00117
Citations
1
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.73
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Research on Vehicle Collaborative Algorithm for Optimizing Intelligent Charging Pile of Electric Vehicles in the Internet of Vehicles Environment

Fengyue Chen, Xiaorong Zhang, Jinsheng Wang, Rui Zheng et al.
1 citations
Electric Vehicles and Infrastructure
0.73
article

Research on Vehicle Collaborative Algorithm for Optimizing Intelligent Charging Pile of Electric Vehicles in the Internet of Vehicles Environment

Fengyue Chen, Xiaorong Zhang, Jinsheng Wang, Rui Zheng, Yuanyuan Lv, Jiaxin Dai
article en
1 citations

Abstract

This paper proposes a collaborative optimization algorithm for intelligent charging piles of electric vehicles based on the Internet of Vehicles environment. The algorithm combines the real-time information interaction between vehicles to establish a charging demand prediction model, and designs an intelligent allocation strategy based on multi-objective optimization to improve the utilization efficiency of charging resources. Various influencing factors are considered, including the distribution density of charging piles, the driving trajectory of electric vehicles, and the spatiotemporal distribution of charging demand. In addition, the model simulation is carried out based on MATLAB, and the algorithm performance is analyzed through experimental data to verify the effectiveness of the proposed algorithm in optimizing the utilization rate of charging piles and shortening user waiting time. The simulation results show that compared with the traditional charging pile allocation method, the algorithm can significantly reduce the average waiting time (by about 25%) and improve the overall charging efficiency (by about 15%). Therefore, this study provides strong support for the optimization of charging resources for electric vehicles in the Internet of Vehicles environment, which is conducive to promoting the popularization of electric vehicles and the integrated application of Internet of Vehicles technology.

Openalex Percentile: Top 30%
Electric Vehicles and Infrastructure
0.73
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