A review of deep learning approach to predicting the state of health and state of charge of lithium-ion batteries
In the field of energy storage, it is very important to predict the state of charge and the state of
health of lithium-ion batteries. In this paper, we review the current widely used equivalent …
health of lithium-ion batteries. In this paper, we review the current widely used equivalent …
Machine learning toward advanced energy storage devices and systems
Technology advancement demands energy storage devices (ESD) and systems (ESS) with
better performance, longer life, higher reliability, and smarter management strategy …
better performance, longer life, higher reliability, and smarter management strategy …
Prediction of the remaining useful life of supercapacitors
As a new type of energy‐storage device, supercapacitors are widely used in various energy
storage fields because of their advantages such as fast charging and discharging, high …
storage fields because of their advantages such as fast charging and discharging, high …
[HTML][HTML] A literature review of fault diagnosis based on ensemble learning
Z Mian, X Deng, X Dong, Y Tian, T Cao, K Chen… - … Applications of Artificial …, 2024 - Elsevier
The accuracy of fault diagnosis is an important indicator to ensure the reliability of key
equipment systems. Ensemble learning integrates different weak learning methods to obtain …
equipment systems. Ensemble learning integrates different weak learning methods to obtain …
Deep learning enhanced lithium-ion battery nonlinear fading prognosis
With the assistance of artificial intelligence, advanced health prognosis technique plays a
critical role in the lithium-ion (Li-ion) batteries management system. However, conventional …
critical role in the lithium-ion (Li-ion) batteries management system. However, conventional …
State of charge estimation of supercapacitors based on multi‐innovation unscented Kalman filter under a wide temperature range
Y Xu, H Zhang, F Yang, L Tong, D Yan… - … Journal of Energy …, 2022 - Wiley Online Library
Supercapacitors are characterized by a long service lifetime and high power density, which
can meet the instantaneous high‐power demand during the acceleration of electric vehicles …
can meet the instantaneous high‐power demand during the acceleration of electric vehicles …
Rapid ultracapacitor life prediction with a convolutional neural network
C Wang, R ** next‐generation functional materials
Abstract Machine learning (ML) is a versatile technique to rapidly and efficiently generate
insights from multidimensional data. It offers a much‐needed avenue to accelerate the …
insights from multidimensional data. It offers a much‐needed avenue to accelerate the …
In-situ grown bimetallic FeCu MOF-MXene composite for solid-state asymmetric supercapacitors
MXene (2D titanium carbide) is thoroughly investigated and studied in recent years for
energy storage purposes. It has excellent properties such as hydrophilicity, metallic …
energy storage purposes. It has excellent properties such as hydrophilicity, metallic …
A comprehensive review on MoSe 2 nanostructures with an overview of machine learning techniques for supercapacitor applications
In the past few decades, supercapacitors (SCs) have emerged as good and reliable energy
storage devices due to their impressive power density, better charge–discharge rates, and …
storage devices due to their impressive power density, better charge–discharge rates, and …