This paper focuses on a novel solution, Dynamic Wireless Charging, which is investigated to enhance the accessibility of electric vehicle charging. The study centres around a specific case, the "Arena of the Future" project, in which an experimental campaign is conducted, simulating various driving scenarios to assess the performance and efficiency of Dynamic Wireless Charging. The tests reveal insights into energy charged, state of charge variations, and the impact of driving styles on charging efficiency. To complement the empirical findings, a scalable model is developed, incorporating forces acting on the electric vehicle for estimating consumptions and recharged energy. The model is validated through a comprehensive comparison with experimental results. The percentage error between model predictions and experimental data varied from 9% to 38%. Results and discussions underscore the model's tendency to overestimate energy recharged, providing valuable insights into the recharging efficiency concerning different speed profiles and driving styles.

Electric Vehicle Modelling Applied to Dynamic Wireless Charging: Case Study

Saldarini A.;Longo M.;Brenna M.;Zaninelli D.;
2024-01-01

Abstract

This paper focuses on a novel solution, Dynamic Wireless Charging, which is investigated to enhance the accessibility of electric vehicle charging. The study centres around a specific case, the "Arena of the Future" project, in which an experimental campaign is conducted, simulating various driving scenarios to assess the performance and efficiency of Dynamic Wireless Charging. The tests reveal insights into energy charged, state of charge variations, and the impact of driving styles on charging efficiency. To complement the empirical findings, a scalable model is developed, incorporating forces acting on the electric vehicle for estimating consumptions and recharged energy. The model is validated through a comprehensive comparison with experimental results. The percentage error between model predictions and experimental data varied from 9% to 38%. Results and discussions underscore the model's tendency to overestimate energy recharged, providing valuable insights into the recharging efficiency concerning different speed profiles and driving styles.
2024
IFAC-PapersOnLine
Dynamic Wireless Charging
Electric Mobility
Electric Vehicle
Modelling
Smart Green Road
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1277893
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