State-of-charge estimation and remaining useful life prediction of supercapacitors

C Liu, Q Li, K Wang - Renewable and Sustainable Energy Reviews, 2021 - Elsevier
As a new type of energy storage device, supercapacitors are widely applied in various fields
owing to their irreplaceable extraordinary characteristics. The remaining useful life …

A critical review of online battery remaining useful lifetime prediction methods

S Wang, S **, D Deng, C Fernandez - Frontiers in Mechanical …, 2021 - frontiersin.org
Lithium-ion batteries play an important role in our daily lives. The prediction of the remaining
service life of lithium-ion batteries has become an important issue. This article reviews the …

A novel online method for predicting the remaining useful life of lithium-ion batteries considering random variable discharge current

D Shen, L Wu, G Kang, Y Guan, Z Peng - Energy, 2021 - Elsevier
Lithium-ion batteries are widely used in many electronic and electrical devices, and
accurately predicting their remaining useful life is essential to ensure the safe and reliable …

Lithium-ion batteries health prognosis considering aging conditions

A El Mejdoubi, H Chaoui, H Gualous… - … on Power Electronics, 2018 - ieeexplore.ieee.org
The prognosis and health management of lithium-ion batteries are extremely important
issues for operating performance as well as the cost of energy storage systems in vehicular …

Parallel state fusion LSTM-based early-cycle stage lithium-ion battery RUL prediction under Lebesgue sampling framework

G Lyu, H Zhang, Q Miao - Reliability Engineering & System Safety, 2023 - Elsevier
Remaining useful life (RUL) prediction for lithium-ion batteries in early-cycle stage is of great
significance for improving battery performance and reducing losses caused by accidental …

An indirect RUL prognosis for lithium-ion battery under vibration stress using Elman neural network

W Li, Z Jiao, L Du, W Fan, Y Zhu - International Journal of Hydrogen Energy, 2019 - Elsevier
Remaining useful life (RUL) prognosis of lithium-ion battery can appraise the battery
reliability to determine the advent of failure and mitigate risk. To acquire measurement data …

Deep learning prognostics for lithium-ion battery based on ensembled long short-term memory networks

Y Liu, G Zhao, X Peng - IEEE Access, 2019 - ieeexplore.ieee.org
In recent years, a notable development for predicting the remaining useful life (RUL) of
components is prognostics that use data-driven approaches based on deep learning. In …

Model-based health diagnosis for lithium-ion battery pack in space applications

Y Song, Y Peng, D Liu - IEEE Transactions on Industrial …, 2020 - ieeexplore.ieee.org
Lithium-ion battery packs are critical to ensure the operational reliability and service life of
spacecraft. The battery pack health diagnosis is meaningful for reasonable mission plan and …

RUL prediction and uncertainty management for multisensor system using an integrated data-level fusion and UPF approach

H Zhang, E Liu, B Zhang, Q Miao - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Due to the fact that single sensor data contains only partial information about complex
systems, multiple sensors are often embedded to simultaneously monitor the health state …

Cost-effective Lebesgue sampling long short-term memory networks for lithium-ion batteries diagnosis and prognosis

H Zhang, G Niu, B Zhang, Q Miao - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Diagnosis and prognosis are critical for the safe operation of lithium-ion batteries in avoiding
serious damage and economic loss caused by power failure, fire, or explosion. With …