[HTML][HTML] A critical review of improved deep learning methods for the remaining useful life prediction of lithium-ion batteries
As widely used for secondary energy storage, lithium-ion batteries have become the core
component of the power supply system and accurate remaining useful life prediction is the …
component of the power supply system and accurate remaining useful life prediction is the …
An encoder-decoder fusion battery life prediction method based on Gaussian process regression and improvement
The prediction ability of all traditional machine learning models is limited to a few batteries.
When the RUL of more batteries needs to be predicted, the prediction performance of …
When the RUL of more batteries needs to be predicted, the prediction performance of …
A novel method for state of health estimation of lithium-ion batteries based on improved LSTM and health indicators extraction
Y Ma, C Shan, J Gao, H Chen - Energy, 2022 - Elsevier
State of health (SOH) is a crucial challenge to guarantee the reliability and safety of the
electric vehicles (EVs), due to the complex aging mechanism. A novel SOH estimation …
electric vehicles (EVs), due to the complex aging mechanism. A novel SOH estimation …
Remaining useful life and state of health prediction for lithium batteries based on empirical mode decomposition and a long and short memory neural network
Accurate estimation and prediction of the state of health (SOH) and remaining useful life
(RUL) are crucial for battery management systems, which have an important role in the field …
(RUL) are crucial for battery management systems, which have an important role in the field …
Remaining useful life prediction for lithium-ion batteries based on a hybrid model combining the long short-term memory and Elman neural networks
This paper presents a novel hybrid Elman-LSTM method for battery remaining useful life
prediction by combining the empirical model decomposition algorithm and long short-term …
prediction by combining the empirical model decomposition algorithm and long short-term …
LSTM-based battery remaining useful life prediction with multi-channel charging profiles
Remaining useful life (RUL) prediction of lithium-ion batteries can reduce the risk of battery
failure by predicting the end of life. In this paper, we propose novel RUL prediction …
failure by predicting the end of life. In this paper, we propose novel RUL prediction …
Remaining useful life and state of health prediction for lithium batteries based on differential thermal voltammetry and a deep-learning model
B Ma, S Yang, L Zhang, W Wang, S Chen, X Yang… - Journal of Power …, 2022 - Elsevier
Lithium-ion batteries (LIBs) are widely used in the assembly of battery packs for electric
vehicles and energy storage grids due to their high power density, low self-discharge rate …
vehicles and energy storage grids due to their high power density, low self-discharge rate …
Battery health prognosis with gated recurrent unit neural networks and hidden Markov model considering uncertainty quantification
With the widespread use of lithium-ion batteries in various fields, battery failures become the
most critical concerns that may lead to enormous economic losses and even serious safety …
most critical concerns that may lead to enormous economic losses and even serious safety …
End-cloud collaboration method enables accurate state of health and remaining useful life online estimation in lithium-ion batteries
Though the lithium-ion battery is universally applied, the reliability of lithium-ion batteries
remains a challenge due to various physicochemical reactions, electrode material …
remains a challenge due to various physicochemical reactions, electrode material …
Health prognosis with optimized feature selection for lithium-ion battery in electric vehicle applications
The widespread use of lithium-ion batteries in electric vehicles has attracted widespread
attention in both academia and industry. Among them, lithium-ion batteries' prognosis and …
attention in both academia and industry. Among them, lithium-ion batteries' prognosis and …