Design of an Experimental Setup for Generating Electric Vehicle Charging Data Sets

S Rinaldi, M Pasetti, A Musatti… - 2024 IEEE 14th …, 2024 - ieeexplore.ieee.org
2024 IEEE 14th International Workshop on Applied Measurements for …, 2024ieeexplore.ieee.org
The increasing adoption of Electric Vehicles (EVs) requires the creation of efficient, robust,
and interconnected charging infrastructures. Currently, Electric Vehicle Supply Equipment
(EVSE) provide all of the power that EVs require. However, the exponential growth in the
number of EVs and associated EVSE systems necessitates the development of charging
systems capable of modulating energy supply in response to distribution network demands.
To design such systems, it is necessary to understand the typical charging behavior of …
The increasing adoption of Electric Vehicles (EVs) requires the creation of efficient, robust, and interconnected charging infrastructures. Currently, Electric Vehicle Supply Equipment (EVSE) provide all of the power that EVs require. However, the exponential growth in the number of EVs and associated EVSE systems necessitates the development of charging systems capable of modulating energy supply in response to distribution network demands. To design such systems, it is necessary to understand the typical charging behavior of various types of EVs. This paper describes the design and implementation of an experimental setup for collecting detailed EV charging datasets. The experimental setup was designed to cover a wide range of charging scenarios, including variables such as charging power levels, EV types, battery capacity, State of Charge (SoC) dynamics, and the environmental factors that influence them. The setup includes meters capable of acquiring various electrical parameters, including power quality, with a thirty-second sampling interval. Initial results from preliminary experiments with the proposed setup and a sample of 16 different EVs reveal key trends and anomalies in EV charging behavior, providing valuable insights into charging infrastructure optimization.
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