On the public citation graph

Data-driven assessment of effective service capacity and high-power retrofits for heterogeneous EV charging topologies at expressway service areas

https://doi.org/10.2139/ssrn.7454632
0 signed · 13 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.apenergy.2023.122278openalex-snapshot
A two-level charging scheduling method for public electric vehicle charging stations considering heterogeneous demand and nonlinear charging profile
inferredcites →https://doi.org/10.1016/j.apenergy.2024.124623openalex-snapshot
Effectiveness of high-power chargers at a quick-Charging Station for electric vehicles
inferredcites →https://doi.org/10.1016/j.est.2021.103099openalex-snapshot
A comprehensive review on system architecture and international standards for electric vehicle charging stations
inferredcites →https://doi.org/10.1016/j.jclepro.2018.12.188openalex-snapshot
Optimal locations of U.S. fast charging stations for long-distance trip completion by battery electric vehicles
inferredcites →https://doi.org/10.1016/j.trb.2020.03.001openalex-snapshot
Optimal deployment of charging stations considering path deviation and nonlinear elastic demand
inferredcites →https://doi.org/10.1016/j.trc.2019.03.013openalex-snapshot
Designing locations and capacities for charging stations to support intercity travel of electric vehicles: An expanded network approach
inferredcites →https://doi.org/10.1016/j.trd.2019.11.008openalex-snapshot
Electric vehicle charging station locations: Elastic demand, station congestion, and network equilibrium
inferredcites →https://doi.org/10.1016/j.tre.2024.103568openalex-snapshot
Planning of electric vehicle charging stations: An integrated deep learning and queueing theory approach
inferredcites →https://doi.org/10.1109/access.2021.3112189openalex-snapshot
A Comprehensive Review on Structural Topologies, Power Levels, Energy Storage Systems, and Standards for Electric Vehicle Charging Stations and Their Impacts on Grid
inferredcites →https://doi.org/10.1109/ojpel.2024.3466936openalex-snapshot
A Comprehensive Review on DC Fast Charging Stations for Electric Vehicles: Standards, Power Conversion Technologies, Architectures, Energy Management, and Cybersecurity
inferredcites →https://doi.org/10.1109/tte.2019.2897088openalex-snapshot
Modeling and Analysis of a Fast Charging Station and Evaluation of Service Quality for Electric Vehicles
inferredcites →https://doi.org/10.1109/tte.2023.3245332openalex-snapshot
The Impact of Considering State-of-Charge-Dependent Maximum Charging Powers on the Optimal Electric Vehicle Charging Scheduling
inferredcites →https://doi.org/10.3390/wevj17070337openalex-snapshot
Cost-Aware Topology and Gun-to-Module Ratio Design for Modular Multi-Gun DC Fast Chargers
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.