Charging route selection model of electric vehicles considering user perception

Mei Feng; Liying Wei

doi:10.1117/12.3024667

14 February 2024 Charging route selection model of electric vehicles considering user perception

Mei Feng, Liying Wei

Proceedings Volume 13018, International Conference on Smart Transportation and City Engineering (STCE 2023); 130180S (2024) https://doi.org/10.1117/12.3024667
Event: International Conference on Smart Transportation and City Engineering (STCE 2023), 2023, Chongqing, China

Abstract

In order to provide a reference for EV travelers in charging route planning and charging station selection, a charging route selection model considering the impact of congestion on users' perception is established in this paper. Firstly, using the data obtained from the questionnaire survey, the MNL model is used to obtain the impact of congestion on users' perception of travel time. The results show that when the travel time is 10min, the user's mental travel time is 2.6 minutes longer than the actual travel time when the congestion degree increases by 1 level. Secondly, considering charging fee, parking fee, queuing time at the charging station and mental travel time from the starting point to the charging station and then to the destination, a charging route selection model aiming at minimizing the total charging cost is established. Taking the actual road network in typical areas of Beijing as an example, the charging route selection is carried out based on ant colony algorithm. The results show that the model is feasible and effective.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Mei Feng and Liying Wei "Charging route selection model of electric vehicles considering user perception", Proc. SPIE 13018, International Conference on Smart Transportation and City Engineering (STCE 2023), 130180S (14 February 2024); https://doi.org/10.1117/12.3024667

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