Exploiting data acquisition approaches in an electric vehicle charging scheduling module

• Published in: 2024 10th International Conference on Control, Decision and Information Technologies (CoDIT) pp. 2385 - 2388
• Main Authors: Chen, Henry, Lambrinos, Lambros, Grammenos, Ryan, Karagiannis, Konstantinos, Kfoury, Elie
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-07-2024
• Subjects: Accuracy; Data acquisition; electric vehicle; Electric vehicle charging; Information technology; Power system stability; Roads; smart charging; Stability analysis; State of charge; Stress; user drive cycle data
• ISSN: 2576-3555
• DOI: 10.1109/CoDIT62066.2024.10708327

In the last few years there is a significant increase in the use of electric vehicles and this highly welcomed development obviously contributes towards the reduction of emissions. On the other hand, as electric vehicles require considerable power during charging, the electric grid infrastructure is put under stress during periods of high overall demand from households. As such, a smart electric vehicle charging scheduling system is a necessity satisfying the needs of the vehicle owners while ensuring the stability of the grid. One of the most significant inputs to such a system, that should be inherently available, is vehicle and user drive cycle data. To this end, this paper examines three different yet practical electric vehicle data acquisition techniques, which were tested in the real world. Consequently, data acquisition constitutes a primary building block in a newly proposed electric vehicle charging scheduling recommendation module.