A review of modeling, management, and applications of grid-connected Li-ion battery storage systems

M Rouholamini, C Wang, H Nehrir, X Hu… - … on Smart Grid, 2022 - ieeexplore.ieee.org
The intermittency of renewable energy sources makes the use of energy storage systems
(ESSs) indispensable in modern power grids for supply-demand balancing and reliability …

Critical review of the methods for monitoring of lithium-ion batteries in electric and hybrid vehicles

W Waag, C Fleischer, DU Sauer - Journal of Power Sources, 2014 - Elsevier
Lithium-ion battery packs in hybrid and pure electric vehicles are always equipped with a
battery management system (BMS). The BMS consists of hardware and software for battery …

State-of-charge estimation of Li-ion batteries using deep neural networks: A machine learning approach

E Chemali, PJ Kollmeyer, M Preindl, A Emadi - Journal of Power Sources, 2018 - Elsevier
Abstract Accurate State of Charge (SOC) estimation is crucial to ensure the safe and reliable
operation of Li-ion batteries, which are increasingly being used in Electric Vehicles (EV) …

Long short-term memory networks for accurate state-of-charge estimation of Li-ion batteries

E Chemali, PJ Kollmeyer, M Preindl… - IEEE Transactions …, 2017 - ieeexplore.ieee.org
State of charge (SOC) estimation is critical to the safe and reliable operation of Li-ion battery
packs, which nowadays are becoming increasingly used in electric vehicles (EVs), Hybrid …

State of charge and state of health estimation for lithium batteries using recurrent neural networks

H Chaoui, CC Ibe-Ekeocha - IEEE Transactions on vehicular …, 2017 - ieeexplore.ieee.org
This paper presents an application of dynamically driven recurrent networks (DDRNs) in
online electric vehicle (EV) battery analysis. In this paper, a nonlinear autoregressive with …

Electrochemical and electrostatic energy storage and management systems for electric drive vehicles: State-of-the-art review and future trends

E Chemali, M Preindl, P Malysz… - IEEE Journal of …, 2016 - ieeexplore.ieee.org
Recently, increased emissions regulations and a push for less dependence on fossil fuels
are factors that have enticed a growth in the market share of alternative energy vehicles …

Physics-informed neural networks for electrode-level state estimation in lithium-ion batteries

W Li, J Zhang, F Ringbeck, D Jöst, L Zhang, Z Wei… - Journal of Power …, 2021 - Elsevier
An accurate estimation of the internal states of lithium-ion batteries is critical to improving the
reliability and durability of battery systems. Data-driven methods have exhibited enormous …

Co-estimation of state-of-charge, capacity and resistance for lithium-ion batteries based on a high-fidelity electrochemical model

L Zheng, L Zhang, J Zhu, G Wang, J Jiang - Applied energy, 2016 - Elsevier
Lithium-ion batteries have been widely used as enabling energy storage in many industrial
fields. Accurate modeling and state estimation play fundamental roles in ensuring safe …

Online model identification and state-of-charge estimate for lithium-ion battery with a recursive total least squares-based observer

Z Wei, C Zou, F Leng, BH Soong… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
The state-of-charge (SOC) observer with online model adaption generally has high accuracy
and robustness. However, the unexpected sensing of noises is shown to cause the biased …

A systematic state-of-charge estimation framework for multi-cell battery pack in electric vehicles using bias correction technique

F Sun, R Xiong, H He - Applied Energy, 2016 - Elsevier
In order to maximize the capacity/energy utilization and guarantee safe and reliable
operation of battery packs used in electric vehicles, an accurate cell state-of-charge (SoC) …