State of health prediction of lithium-ion batteries based on machine learning: Advances and perspectives
Accurate state of health (SOH) prediction is significant to guarantee operation safety and
avoid latent failures of lithium-ion batteries. With the development of communication and …
avoid latent failures of lithium-ion batteries. With the development of communication and …
Hybrid methods using neural network and Kalman filter for the state of charge estimation of lithium‐ion battery
Z Cui, J Dai, J Sun, D Li, L Wang… - … Problems in Engineering, 2022 - Wiley Online Library
With the increasing carbon emissions worldwide, lithium‐ion batteries have become the
main component of energy storage systems for clean energy due to their unique …
main component of energy storage systems for clean energy due to their unique …
A combined state-of-charge estimation method for lithium-ion battery using an improved BGRU network and UKF
Lithium-ion batteries have become the fastest-growing energy storage equipment available
for extrinsic and intrinsic reasons. State of Charge (SOC) is one of the lithium-ion batteries' …
for extrinsic and intrinsic reasons. State of Charge (SOC) is one of the lithium-ion batteries' …
SOC estimation for lithium-ion battery using the LSTM-RNN with extended input and constrained output
J Chen, Y Zhang, J Wu, W Cheng, Q Zhu - Energy, 2023 - Elsevier
The state of charge (SOC) estimation of lithium-ion battery (LIB) based on recurrent neural
network (RNN) has been a popular research due to its suitability for time series data …
network (RNN) has been a popular research due to its suitability for time series data …
State of health estimation for lithium-ion batteries based on temperature prediction and gated recurrent unit neural network
Accurate state of health estimation for lithium-ion batteries is crucial to ensure the safety and
reliability of electric vehicles. This study presents an accurate state of health estimation …
reliability of electric vehicles. This study presents an accurate state of health estimation …
OCV-SOC-temperature relationship construction and state of charge estimation for a series–parallel lithium-ion battery pack
Q Yu, Y Huang, A Tang, C Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Accurate state of charge (SOC) estimation of a battery pack is more meaningful than that of a
cell in practical applications. The existing methods are difficult to provide an accurate SOC of …
cell in practical applications. The existing methods are difficult to provide an accurate SOC of …
Physics-informed neural network approach for heat generation rate estimation of lithium-ion battery under various driving conditions
Accurate insight into the heat generation rate (HGR) of lithium-ion batteries (LIBs) is one of
key issues for battery management systems to formulate thermal safety warning strategies in …
key issues for battery management systems to formulate thermal safety warning strategies in …
A novel lithium-ion battery state of charge estimation method based on the fusion of neural network and equivalent circuit models
Accurate estimating the state of charge (SOC) can improve battery reliability, safety, and
extend battery service life. The existing battery models used for SOC estimation …
extend battery service life. The existing battery models used for SOC estimation …
Optimized multi-hidden layer long short-term memory modeling and suboptimal fading extended Kalman filtering strategies for the synthetic state of charge estimation …
Y Xie, S Wang, G Zhang, Y Fan, C Fernandez… - Applied Energy, 2023 - Elsevier
With the demand for high-endurance lithium-ion batteries in new energy vehicles,
communication and portable devices, high energy density lithium-ion batteries have become …
communication and portable devices, high energy density lithium-ion batteries have become …
A flexible state-of-health prediction scheme for lithium-ion battery packs with long short-term memory network and transfer learning
The application of machine learning-based state-of-health (SOH) prediction is hindered by
the large demand for training data. To conquer this defect, a flexible and easily transferred …
the large demand for training data. To conquer this defect, a flexible and easily transferred …