The transition to Electric Vehicles (EVs) represents a significant change in the mobility sector, promising greater environmental sustainability, safety and efficiency. Despite these benefits, EVs adoption is hampered by range anxiety. This study presents a predictive model designed to estimate the number of charging sessions needed for an EV under various usage scenarios. The model simulates the behaviour of the electric vehicle through a network of Charging Stations (CSs) and evaluates its performance by comparing the simulated results with real data. To validate the model, an experimental test is conducted on the Bergamo-Paris route. The vehicle required three charging sessions, consistent with the model's predictions. This model is critical for optimizing energy management strategies, potentially alleviating range anxiety and driving EVs adoption.
Predictive Modelling of Electric Vehicle Charging Sessions: An Empirical Validation of an Italy - France Route
Borgosano S.;Saldarini A.;Longo M.;Zaninelli D.;
2024-01-01
Abstract
The transition to Electric Vehicles (EVs) represents a significant change in the mobility sector, promising greater environmental sustainability, safety and efficiency. Despite these benefits, EVs adoption is hampered by range anxiety. This study presents a predictive model designed to estimate the number of charging sessions needed for an EV under various usage scenarios. The model simulates the behaviour of the electric vehicle through a network of Charging Stations (CSs) and evaluates its performance by comparing the simulated results with real data. To validate the model, an experimental test is conducted on the Bergamo-Paris route. The vehicle required three charging sessions, consistent with the model's predictions. This model is critical for optimizing energy management strategies, potentially alleviating range anxiety and driving EVs adoption.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
