Optimised Centralised Charging of Electric Vehicles Along Motorways

Ekaterina Dudkina, Claudio Scarpelli (), Valerio Apicella, Massimo Ceraolo and Emanuele Crisostomi
Additional contact information
Ekaterina Dudkina: Department of Energy, Systems, Territory and Construction Engineering, University of Pisa, 56122 Pisa, Italy
Claudio Scarpelli: Department of Energy, Systems, Territory and Construction Engineering, University of Pisa, 56122 Pisa, Italy
Valerio Apicella: Research & Development and Innovation, Movyon SpA—Gruppo Autostrade per l’Italia, 50123 Firenze, Italy
Massimo Ceraolo: Department of Energy, Systems, Territory and Construction Engineering, University of Pisa, 56122 Pisa, Italy
Emanuele Crisostomi: Department of Energy, Systems, Territory and Construction Engineering, University of Pisa, 56122 Pisa, Italy

Sustainability, 2025, vol. 17, issue 12, 1-15

Abstract: Nowadays, when battery-powered electric vehicles (EVs) travel along motorways, their drivers decide where to recharge their cars’ batteries with no or scarce information on the occupancy status of the next charging stations. While this may still be acceptable in most countries, due to the limited number of EVs on motorways, long queues may build-up in the coming years with increased electric mobility, unless smart allocation strategies are designed and implemented. For instance, as we shall investigate in this manuscript, a centralised coordination of the charging strategies of individual EVs has the potential to significantly reduce the queuing time at charging stations. In particular, in this paper we explain how the charging problem on motorways can be modelled as an optimisation problem, we propose some strategies based on dynamic optimisation to solve it, and we explain how this may be implemented in practice using a centralised charge manager that exchanges information with the EVs and solves the optimisation problems. Finally, we compare in a realistic scenario the current decentralised recharging strategies with a centralised one, and we show that, under simplifying assumptions, queueing times can be reduced by more than 50%. Such a significant reduction allows one to greatly improve vehicular flows and general journey durations without requiring building new infrastructure. Reducing queuing times has a positive impact on traffic congestion and emissions, and the more geographically balanced energy demand of the proposed methodology mitigates energy consumption peaks.

Keywords: electric vehicles; charging algorithms; centralised optimisation algorithms; charging stations balancing; energy demand sustainability (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/17/12/5668/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/12/5668/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:12:p:5668-:d:1683158

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().