Review on modeling and soc/soh estimation of batteries for automotive applications

P Dini, A Colicelli, S Saponara - Batteries, 2024‏ - mdpi.com
Lithium-ion batteries have revolutionized the portable and stationary energy industry and
are finding widespread application in sectors such as automotive, consumer electronics …

Feature engineering and artificial intelligence-supported approaches used for electric powertrain fault diagnosis: A review

X Zhang, Y Hu, J Deng, H Xu, H Wen - IEEE Access, 2022‏ - ieeexplore.ieee.org
Electric powertrain is constituted by electric machine transmission unit, inverter and battery
packs, etc., is a highly-integrated system. Its reliability and safety are not only related to …

A compact and optimized neural network approach for battery state-of-charge estimation of energy storage system

Y Guo, Z Yang, K Liu, Y Zhang, W Feng - Energy, 2021‏ - Elsevier
Accurate estimations of battery state-of-charge (SOC) for energy storage systems are
popular research topics in recent years. Numerous challenges remain in several aspects …

A novel estimation of state of charge for the lithium-ion battery in electric vehicle without open circuit voltage experiment

R **ao, Y Hu, X Jia, G Chen - Energy, 2022‏ - Elsevier
The estimation of the state-of-charge (SOC) based on equivalent circuit model (ECMs) for
the lithium-ion battery has been widely adopted. The relationship between the open-circuit …

An improved forgetting factor recursive least square and unscented particle filtering algorithm for accurate lithium-ion battery state of charge estimation

X Hao, S Wang, Y Fan, Y **e, C Fernandez - Journal of energy storage, 2023‏ - Elsevier
As an indispensable part of the battery management system, accurately predicting the
estimation of the state of charge (SOC) has attracted more attention, which can improve the …

Battery management system to estimate battery aging using deep learning and machine learning algorithms

S Harippriya, EE Vigneswaran… - Journal of Physics …, 2022‏ - iopscience.iop.org
One of the greatest challenges faced by Electric Vehicle (EV) manufactures is insufficient
charging stations. Estimating the aging of the battery in the electric vehicle helps the driver to …

A parallel deep learning algorithm with applications in process monitoring and fault prediction

H Qian, B Sun, Y Guo, Z Yang, J Ling… - Computers and Electrical …, 2022‏ - Elsevier
Effective and timely fault detection and status monitoring of the industrial production process
is essential to fully guarantee the operational safety. However, massive multi-source …

[HTML][HTML] State of charge estimation of li-ion batteries based on the noise-adaptive interacting multiple model

C Huang, X Yu, Y Wang, Y Zhou, R Li - Energy Reports, 2021‏ - Elsevier
This paper presents a type of noise-adaptive (NA) interacting multiple model (IMM) algorithm
combined with an unscented Kalman filter (UKF) in order to address problems in poor …

A novel joint support vector machine-cubature Kalman filtering method for adaptive state of charge prediction of lithium-ion batteries

Q Song, S Wang, W Xu, Y Shao… - International Journal of …, 2021‏ - Elsevier
Accurate estimation of SOC of lithium-ion batteries has always been an important work in the
battery management system. However, it is often very difficult to accurately estimate the SOC …

Deep learning with spatial attention-based CONV-LSTM for SOC estimation of lithium-ion batteries

H Tian, J Chen - Processes, 2022‏ - mdpi.com
Accurate estimation of the state of charge (SOC) is an indispensable part of a vehicle
management system. The accurate estimation of SOC can ensure the safe and reliable …