TY - GEN
T1 - Analysis of an Electric Vehicle Charging System Along a Highway
AU - Cerotti, Davide
AU - Mancini, Simona
AU - Gribaudo, Marco
AU - Bobbio, Andrea
N1 - Publisher Copyright:
© 2022, Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - Battery charge decision policy
KW - Charging infrastructure
KW - Electric Vehicle
KW - Fluid Stochastic Petri Nets
UR - https://www.scopus.com/pages/publications/85139083668
U2 - 10.1007/978-3-031-16336-4_15
DO - 10.1007/978-3-031-16336-4_15
M3 - Conference contribution
AN - SCOPUS:85139083668
SN - 9783031163357
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 298
EP - 316
BT - Quantitative Evaluation of Systems - 19th International Conference, QEST 2022, Proceedings
A2 - Ábrahám, Erika
A2 - Paolieri, Marco
PB - Springer Science and Business Media Deutschland GmbH
T2 - 19th International Conference on Quantitative Evaluation of Systems, QEST 2022
Y2 - 12 September 2022 through 16 September 2022
ER -