Machine learning in state of health and remaining useful life estimation: Theoretical and technological development in battery degradation modelling
Designing and deployment of state-of-the-art electric vehicles (EVs) in terms of low cost and
high driving range with appropriate reliability and security are identified as the key towards …
high driving range with appropriate reliability and security are identified as the key towards …
Echelon utilization of retired power lithium-ion batteries: Challenges and prospects
The explosion of electric vehicles (EVs) has triggered massive growth in power lithium-ion
batteries (LIBs). The primary issue that follows is how to dispose of such large-scale retired …
batteries (LIBs). The primary issue that follows is how to dispose of such large-scale retired …
Remaining useful life prediction of lithium-ion battery with adaptive noise estimation and capacity regeneration detection
As an indispensable energy device, 18650 lithium-ion battery has widespread applications
in electric vehicles. Remaining useful life (RUL) prediction of lithium-ion battery is critical for …
in electric vehicles. Remaining useful life (RUL) prediction of lithium-ion battery is critical for …
Towards the swift prediction of the remaining useful life of lithium-ion batteries with end-to-end deep learning
This paper presents the first full end-to-end deep learning framework for the swift prediction
of lithium-ion battery remaining useful life. While lithium-ion batteries offer advantages of …
of lithium-ion battery remaining useful life. While lithium-ion batteries offer advantages of …
Remaining useful life prediction of lithium-ion batteries based on false nearest neighbors and a hybrid neural network
Accurate estimation of the remaining useful life of lithium-ion batteries is critically important
for electronic devices. In the existing literature, the widely applied model-based approaches …
for electronic devices. In the existing literature, the widely applied model-based approaches …
An empirical-data hybrid driven approach for remaining useful life prediction of lithium-ion batteries considering capacity diving
Considering the variabilities among each cell especially during the battery accelerated
decay period, the parameterized empirical model is doubtful for predicting the Lithium-ion (Li …
decay period, the parameterized empirical model is doubtful for predicting the Lithium-ion (Li …
A hybrid approach based on decomposition algorithm and neural network for remaining useful life prediction of lithium-ion battery
T Tang, H Yuan - Reliability Engineering & System Safety, 2022 - Elsevier
Aiming at the problems of non-linearity, non-stationary and low prediction accuracy of the
original capacity degradation data for lithium-ion battery, a novel remaining useful life …
original capacity degradation data for lithium-ion battery, a novel remaining useful life …
State of health monitoring and remaining useful life prediction of lithium-ion batteries based on temporal convolutional network
D Zhou, Z Li, J Zhu, H Zhang, L Hou - IEEE Access, 2020 - ieeexplore.ieee.org
State of health (SOH) monitoring and remaining useful life (RUL) prediction are the key to
ensuring the safe use of lithium-ion batteries. However, the commonly used models are …
ensuring the safe use of lithium-ion batteries. However, the commonly used models are …
SOH and RUL prediction of lithium-ion batteries based on Gaussian process regression with indirect health indicators
The state of health (SOH) and remaining useful life (RUL) of lithium-ion batteries are two
important factors which are normally predicted using the battery capacity. However, it is …
important factors which are normally predicted using the battery capacity. However, it is …
A lithium-ion battery remaining useful life prediction method based on the incremental capacity analysis and Gaussian process regression
Remaining useful life (RUL) is a critical metric of lithium-ion battery prognostic and health
management. Accurate prediction of RUL is of great significance to the safety and reliability …
management. Accurate prediction of RUL is of great significance to the safety and reliability …