Electric vehicles plug-in duration forecasting using machine learning for battery optimization

Y Chen, KSS Alamin, D Jahier Pagliari, S Vinco… - Energies, 2020 - mdpi.com
The aging of rechargeable batteries, with its associated replacement costs, is one of the
main issues limiting the diffusion of electric vehicles (EVs) as the future transportation …

On the use of machine learning for state-of-charge forecasting in electric vehicles

Y NaitMalek, M Najib, M Bakhouya… - … smart cities conference …, 2019 - ieeexplore.ieee.org
Nowadays, it is well known that a main solution for pollution reduction in cities will be the
introduction of electric and hybrid vehicles on transportation roads. Many research efforts …

Probabilistic forecasts of time and energy flexibility in battery electric vehicle charging

J Huber, D Dann, C Weinhardt - Applied energy, 2020 - Elsevier
Users charging the batteries of their electric vehicles in an uncoordinated manner can
present energy systems with a challenge. One possible solution, smart charging, relies on …

A hybrid approach for state-of-charge forecasting in battery-powered electric vehicles

Y NaitMalek, M Najib, A Lahlou, M Bakhouya, J Gaber… - Sustainability, 2022 - mdpi.com
Nowadays, electric vehicles (EV) are increasingly penetrating the transportation roads in
most countries worldwide. Many efforts are oriented toward the deployment of the EVs …

Electric Vehicles charging sessions classification technique for optimized battery charge based on machine learning

S Matrone, EGC Ogliari, A Nespoli, G Gruosso… - IEEE …, 2023 - ieeexplore.ieee.org
The fast increase in electric vehicle (EV) usage in the last 10 years has raised the need to
properly forecast their energy consumption during charge. Lithium-ion batteries have …

Predicting real life electric vehicle fast charging session duration using neural networks

A Deschênes, J Gaudreault… - 2022 IEEE Intelligent …, 2022 - ieeexplore.ieee.org
Predicting the time needed to charge an electric vehicle from X% to Y% is a difficult task due
to the nonlinearity of the charging process and other external factors such as temperature …

Short-term prediction of electric vehicle charging station availability using cascaded machine learning models

C Hecht, R Aghsaee, F Schwinger… - 6th E-Mobility Power …, 2022 - ieeexplore.ieee.org
Driving long distances with battery electric vehicles is becoming possible thanks to
increasing battery capacities and a growing network of fast-charging stations. During peak …

A deep learning approach for electric vehicle charging duration prediction at public charging stations: The case of Morocco

B Mouaad, M Farag, B Kawtar, K Tarik… - ITM Web of …, 2022 - itm-conferences.org
The adoption of electric vehicles (EVs) is increasing worldwide as it may help reduce
reliance on fossil fuels and greenhouse gas emissions. However, the large-scale use of …

A benchmark of electric vehicle load and occupancy models for day-ahead forecasting on open charging session data

Y Amara-Ouali, Y Goude, B Hamrouche… - Proceedings of the …, 2022 - dl.acm.org
The development of electric vehicles (EV) is a major lever towards low carbon
transportation. It comes with increasing numbers of charging infrastructures which can be …

Short-term individual electric vehicle charging behavior prediction using long short-term memory networks

AS Khwaja, B Venkatesh… - 2020 IEEE 25th …, 2020 - ieeexplore.ieee.org
In this paper, we present a novel approach for individual electric vehicle (EV) charging
prediction based on long short-term memory networks. Unlike existing methods, our …