Advancing state of charge management in electric vehicles with machine learning: a technological review

A Mousaei, Y Naderi, IS Bayram - IEEE Access, 2024 - ieeexplore.ieee.org
As the share of electric vehicles increases, electric vehicles are exposed to broader of
driving conditions (eg, extreme weather), which reduce the performance and driving ranges …

Intelligent charging and discharging of electric vehicles in a vehicle-to-grid system using a reinforcement learning-based approach

J Maeng, D Min, Y Kang - Sustainable Energy, Grids and Networks, 2023 - Elsevier
Recent advances in electric vehicle (EV) technology have increased the importance of
vehicle-to-grid (V2G) systems in the smart grid domain. These systems allow bidirectional …

Sensitivity analysis of a real-time trip planning assisted energy management system for connected plug-in hybrid electric vehicles

S Ekhtiari, M Faieghi, NL Azad - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Recent advances in transportation have proved that the use of upcoming trip data in energy
management of plug-in hybrid electric vehicles (PHEVs) is extremely effective in promoting …

State of charge estimation of the lithium-ion battery based on neural network in electric vehicles

CC Lee, P Hu, CY Li, SH Wang - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
In recent years, Lithium-ion batteries have been widely applied in electric vehicles (EVs).
The accurate estimation of state of charge (SOC) of EV battery is important for prolonging the …

Real-time prediction of battery power requirements for electric vehicles

E Kim, J Lee, KG Shin - Proceedings of the ACM/IEEE 4th International …, 2013 - dl.acm.org
A battery management system (BMS) is responsible for protecting the battery from damage,
predicting battery life, and maintaining the battery in an operational condition. In this paper …

Uncertainty-Aware Prediction of Battery Energy Consumption for Hybrid Electric Vehicles

J Khiari, C Olaverri-Monreal - 2022 IEEE Intelligent Vehicles …, 2022 - ieeexplore.ieee.org
The usability of vehicles is highly dependent on their energy consumption. In particular, one
of the main factors hindering the mass adoption of electric (EV), hybrid (HEV), and plug-in …

Effectiveness comparison of range estimator for battery electric vehicles

KW Chew, YR Yong - Information Science and Applications (ICISA) 2016, 2016 - Springer
Battery electric vehicle is a promising candidate for future passenger vehicles due to its
potential to reduce air pollution, efficient use of energy, and has regenerative braking …

Improved deep learning based state of charge estimation of lithium ion battery for electrified transportation

U Khan, S Kirmani, Y Rafat, MU Rehman… - Journal of Energy …, 2024 - Elsevier
The increasing interests and recent advancements in artificial intelligence and machine
learning have significantly accelerated the development of novel techniques for the state …

Effective charging planning based on deep reinforcement learning for electric vehicles

C Zhang, Y Liu, F Wu, B Tang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Electric vehicles (EVs) are viewed as an attractive option to reduce carbon emission and fuel
consumption, but the popularization of EVs has been hindered by the cruising range …

An electric vehicle charging load prediction model for different functional areas based on multithreaded acceleration

Z Guo, H Bian, C Zhou, Q Ren, Y Gao - Journal of Energy Storage, 2023 - Elsevier
This paper proposes an electric vehicle (EV) charging load prediction model for different
functional areas based on multithreaded technology. This model comprehensively …