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Towards sustainable cities : a KPI-based method to compare cities’ performance and encourage the spread of electric cars
ID
Menendez Agudin, Alvaro
(
Author
),
ID
Caballini, Claudia
(
Author
),
ID
Deflorio, Francesco Paolo
(
Author
),
ID
Fernandez Aznar, Gregorio
(
Author
),
ID
Herman, Leopold
(
Author
),
ID
Knez, Klemen
(
Author
)
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MD5: A15ED047AFE29D12221A9FBA0A92F9B4
URL - Source URL, Visit
https://www.mdpi.com/2071-1050/17/7/3052
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Abstract
European cities have adopted different solutions to address the challenges of charging infrastructure for electric vehicles, depending on their specific characteristics and needs. The widespread adoption of effective solutions could accelerate the transition towards more sustainable urban mobility. However, as cities differ in socio-economic, infrastructural, and environmental aspects, a one-size-fits-all approach may not be suitable. Currently, there is a lack of studies in the literature that identify similarities among cities to support the development of shared strategies for sustainable electric mobility. This paper contributes to filling this gap by proposing a methodology based on Key Performance Indicators (KPIs) to classify and compare cities according to their electric vehicle infrastructure. Using quantitative data from 80 European cities across civil, social, and transport-related factors, as well as electric vehicle charging characteristics, we identified five reference city clusters. A sensitivity analysis, conducted across 30 scenarios, validated the robustness of the KPI framework. This approach provides a tool for policymakers to monitor the evolution of charging infrastructure, supporting data-driven decision-making for sustainable urban mobility. By promoting efficient and adaptable electric vehicle policies, this study aligns with the objectives of the 2030 Agenda for Sustainable Development, particularly in fostering sustainable cities and clean energy adoption.
Language:
English
Keywords:
urban sustainable mobility
,
electric cars
,
charging infrastructures
,
KPIs
,
clusters
,
robustness
,
K-Means clustering method
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
FE - Faculty of Electrical Engineering
Publication status:
Published
Publication version:
Version of Record
Year:
2025
Number of pages:
27 str.
Numbering:
Vol. 17, iss. 7, art. 3052
PID:
20.500.12556/RUL-168387
UDC:
629.331-83
ISSN on article:
2071-1050
DOI:
10.3390/su17073052
COBISS.SI-ID:
232223235
Publication date in RUL:
11.04.2025
Views:
1898
Downloads:
125
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Record is a part of a journal
Title:
Sustainability
Shortened title:
Sustainability
Publisher:
MDPI
ISSN:
2071-1050
COBISS.SI-ID:
5324897
Licences
License:
CC BY 4.0, Creative Commons Attribution 4.0 International
Link:
http://creativecommons.org/licenses/by/4.0/
Description:
This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Secondary language
Language:
Slovenian
Keywords:
urbana trajnostna mobilnost
,
električna vozila
,
polnilna infrastruktura
,
kazalniki
,
gručenje
,
robustnost
,
metoda k-voditeljev
Projects
Funder:
EC - European Commission
Project number:
875683
Name:
Large demonstratIoN of user CentrIc urban and long-range charging solutions to boosT an engaging deployment of Electric Vehicles in Europe
Acronym:
INCIT-EV
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