[HTML][HTML] EV idle time estimation on charging infrastructure, comparing supervised machine learning regressions

A Lucas, R Barranco, N Refa - Energies, 2019 - mdpi.com
The adoption of electric vehicles (EV) has to be complemented with the right charging
infrastructure roll-out. This infrastructure is already in place in many cities throughout the …

Predicting popularity of electric vehicle charging infrastructure in urban context

M Straka, P De Falco, G Ferruzzi, D Proto… - IEEE …, 2020 - ieeexplore.ieee.org
The availability of charging infrastructure is essential for large-scale adoption of electric
vehicles (EV). Charging patterns and the utilization of infrastructure have consequences not …

[HTML][HTML] Estimating the charging profile of individual charge sessions of Electric Vehicles in The Netherlands

JJ Mies, JR Helmus, R Van den Hoed - World Electric Vehicle Journal, 2018 - mdpi.com
The mass adoption of Electric Vehicles (EVs) might raise pressure on the power system,
especially during peak hours. Therefore, there is a need for delayed charging. However, to …

[HTML][HTML] Assessing the value of information for electric vehicle charging strategies at office buildings

L Winschermann, NB Arias, G Hoogsteen… - … and Sustainable Energy …, 2023 - Elsevier
Smart charging strategies for electric vehicles (EVs) require as input information such as
energy requirement and dwell time. In practice, that information is often not available …

Deep learning approach for long-term prediction of electric vehicle (ev) charging station availability

R Luo, Y Zhang, Y Zhou, H Chen… - 2021 IEEE …, 2021 - ieeexplore.ieee.org
Traffic prediction with high accuracy has significance towards traffic facilities scheduling,
adaptive traffic control logic, even the urban economic development. EV charging station …

[HTML][HTML] Predicting electric vehicle charging station availability using ensemble machine learning

C Hecht, J Figgener, DU Sauer - Energies, 2021 - mdpi.com
Electric vehicles may reduce greenhouse gas emissions from individual mobility. Due to the
long charging times, accurate planning is necessary, for which the availability of charging …

A statistical analysis of EV charging behavior in the UK

J Quirós-Tortós, LF Ochoa… - 2015 IEEE PES Innovative …, 2015 - ieeexplore.ieee.org
To truly quantify the impact of electric vehicles (EVs) on the electricity network and their
potential interactions in the context of Smart Grids, it is crucial to understand their charging …

Coincidence factors for domestic EV charging from driving and plug-in behavior

J Bollerslev, PB Andersen, TV Jensen… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
This study models the coincidence factor (CF) of electric vehicle (EV) charging given driving
and plug-in behaviors by combining data sources from travel surveys and recorded EV …

[HTML][HTML] Artificial deep neural network enables one-size-fits-all electric vehicle user behavior prediction framework

A Ahmadian, V Ghodrati, R Gadh - Applied Energy, 2023 - Elsevier
As greener mobility becomes the norm with the advent of electric vehicles (EVs), a natural
question arises: how big of a change are we seeing in terms of the stochastic energy …

[HTML][HTML] Data-Driven, Short-Term Prediction of Charging Station Occupation

R Aghsaee, C Hecht, F Schwinger, J Figgener, M Jarke… - Electricity, 2023 - mdpi.com
Enhancing electric vehicle infrastructure by forecasting the availability of charging stations
can boost the attractiveness of electric vehicles. The transportation sector plays a crucial role …