Abstract
To reduce carbon emission, the transportation sector evolves toward replacing internal combustion vehicles by electric vehicles (EV). However, the limited driving ranges of EVs, their long recharge duration and the need of appropriate charging infrastructures require smart strategies to optimize the charging stops during a long trip. These challenges have generated a new area of studies that were mainly directed to extend the classical Vehicle Routing Problem (VRP) to a fleet of commercial EVs. In this paper, we propose a different point of view, by considering the interaction of private EVs with the related infrastructure, focusing on a highway trip. We consider a highway where charging stations are scattered along the road, and are equipped with multiple chargers. Using Fluid Stochastic Petri Nets (FSPN), the paper compares different decision policies when to stop and recharge the battery to maximize the probability of a car to reach its destination and minimize the trip completion time.
Keywords
Research partially supported by CNIT (Consorzio Nazionale Interuniversitario per le Telecomunicazioni).
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Appendix
Appendix
In Table 2 the location of the service stations along A14 Bologna to Taranto is shown. In particular: the name of the service stations (column 2), the length of the segments (column 3) together with the progressive distances from the start (column 4) and to the end (column 5).
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Cerotti, D., Mancini, S., Gribaudo, M., Bobbio, A. (2022). Analysis of an Electric Vehicle Charging System Along a Highway. In: Ábrahám, E., Paolieri, M. (eds) Quantitative Evaluation of Systems. QEST 2022. Lecture Notes in Computer Science, vol 13479. Springer, Cham. https://doi.org/10.1007/978-3-031-16336-4_15
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