Hierarchical layout optimisation of distributed charging infrastructures on expressways

Range anxiety has become an obstacle to intercity travel by electric vehicle (EV), which has restricted the promotion of EVs. Balancing the supply of charging infrastructures (CIs) on expressways with intercity travel demand should therefore be paid more attention. In this context, a method for estimating charging demand is proposed at the road scale to analyse the disparities between supply and demand (DSD) of CIs. Based on the charging supply at service areas, the method was applied to future scenarios with varying EV penetration rates. Then, a construction plan and a hierarchical optimised model for distributed CIs on expressways were developed in order to meet the DSD. Finally, planning for expressway CIs in the Beijing–Tianjin–Hebei urban agglomeration was considered. The results showed that only 30–40% of the peak charging demand can be met solely on service areas. The DSD spreads from the urban centre to the periphery as the EV penetration rate gradually increases. Through optimisation of the hierarchical distribution of CIs, the construction of CIs should be at intervals greater than 10 km. The results of this study provide theoretical support for the planning and construction of CIs on expressways, which will help promote the development of EVs and expressway electrification.

Authors

Institutions

Publication Details

Journal
Proceedings of the Institution of Civil Engineers - Transport
Published
2025-12-18
DOI
https://doi.org/10.1680/jtran.24.00006
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Hierarchical layout optimisation of distributed charging infrastructures on expressways

Xian Rong, Hongjun Cui, Minqing Zhu, Yue Su et al.
Proceedings of the Institution of Civil Engineers - Transport
Electric Vehicles and Infrastructure
article

Hierarchical layout optimisation of distributed charging infrastructures on expressways

Xian Rong, Hongjun Cui, Minqing Zhu, Yue Su, Xiushi Dong
article en

Abstract

Range anxiety has become an obstacle to intercity travel by electric vehicle (EV), which has restricted the promotion of EVs. Balancing the supply of charging infrastructures (CIs) on expressways with intercity travel demand should therefore be paid more attention. In this context, a method for estimating charging demand is proposed at the road scale to analyse the disparities between supply and demand (DSD) of CIs. Based on the charging supply at service areas, the method was applied to future scenarios with varying EV penetration rates. Then, a construction plan and a hierarchical optimised model for distributed CIs on expressways were developed in order to meet the DSD. Finally, planning for expressway CIs in the Beijing–Tianjin–Hebei urban agglomeration was considered. The results showed that only 30–40% of the peak charging demand can be met solely on service areas. The DSD spreads from the urban centre to the periphery as the EV penetration rate gradually increases. Through optimisation of the hierarchical distribution of CIs, the construction of CIs should be at intervals greater than 10 km. The results of this study provide theoretical support for the planning and construction of CIs on expressways, which will help promote the development of EVs and expressway electrification.

Proceedings of the Institution of Civil Engineers - Transport
Hebei University of Technology (CN)
Openalex Percentile: Top 59%
Electric Vehicles and Infrastructure
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.