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.

Analysis of an Electric Vehicle Charging System Along a Highway

Gribaudo M.;
2022-01-01

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.
2022
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
978-3-031-16335-7
978-3-031-16336-4
Battery charge decision policy
Charging infrastructure
Electric Vehicle
Fluid Stochastic Petri Nets
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1233962
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