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 …

A Comprehensive Review of Categorization and Perspectives on State-of-Charge Estimation Using Deep Learning Methods for Electric Transportation

K Das, R Kumar - Wireless Personal Communications, 2023 - Springer
Lithium-ion batteries are an excellent choice for electric transportation because of their high
energy density, minimum self-discharge, and prolonged cycle life. The performance of …

Deep reinforcement learning based state of charge estimation and management of electric vehicle batteries

I Saba, M Tariq, M Ullah, HV Poor - IET Smart Grid, 2023 - Wiley Online Library
In vehicle‐to‐grid (V2G) networks, electric vehicle (EV) batteries have significant potential as
storage elements to smooth out variations produced by renewable and alternative energy …

Enhancement of Charging Efficiency of Batteries for Electric Vehicles

MS Srinath, R Gunabalan - 2022 Fourth International …, 2022 - ieeexplore.ieee.org
To minimize emissions of greenhouse gases, the electric vehicle industry has grown
dramatically in recent years. Traditional vehicles are improved by a variety of technologies …

Performance analysis on artificial neural network based state of charge estimation for electric vehicles

M Aaruththiran, KM Begam, VR Aparow… - … on Internet of Things …, 2021 - ieeexplore.ieee.org
In the recent years, Artificial Neural Networks (ANNs) have gained wider interest in
estimating the State of charge (SOC) of Li-ion batteries used in electric vehicles. As the ANN …

Dual-task Learning for Joint State-of-Charge and State-of-Energy Estimation of Lithium-ion Battery in Electric Vehicle

Z Bao, J Nie, H Lin, Z Li, K Gao, Z He… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
State-of-X (SOX) estimation of lithium-ion batteries is crucial for safe operation of electric
vehicles (EVs). However, EVs have long suffered from complex and variable operation …

To Charge or Not to Charge: Enhancing Electric Vehicle Charging Management with LSTM-based Prediction of Non-Critical Charging Sessions and Renewable …

H Tayarani, CJ Nitta, G Tal - 2024 - escholarship.org
To maximize the greenhouse gas (GHG) emission reduction potential of Battery Electric
Vehicles (BEVs), it is critical to develop EV dynamic charging management strategies. These …

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 …

Comprehensive Review of Machine Learning, Deep Learning, and Digital Twin Data-Driven Approaches in Battery Health Prediction of Electric Vehicles

AP Renold, NS Kathayat - IEEE Access, 2024 - ieeexplore.ieee.org
This paper presents a comprehensive survey of machine learning, deep learning, and digital
twin technology methods for predicting and managing the battery state of health in electric …

An overview of methods and technologies for estimating battery state of charge in electric vehicles

TMB Marques, JLF dos Santos, DS Castanho… - Energies, 2023 - mdpi.com
Recently, electric vehicles have gained enormous popularity due to their performance and
efficiency. The investment in developing this new technology is justified by the increased …