[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 …
A critical review of online battery remaining useful lifetime prediction methods
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 …
service life of lithium-ion batteries has become an important issue. This article reviews the …
Improved anti-noise adaptive long short-term memory neural network modeling for the robust remaining useful life prediction of lithium-ion batteries
Safety assurance is essential for lithium-ion batteries in power supply fields, and the
remaining useful life (RUL) prediction serves as one of the fundamental criteria for the …
remaining useful life (RUL) prediction serves as one of the fundamental criteria for the …
An adaptive remaining useful life prediction approach for single battery with unlabeled small sample data and parameter uncertainty
Accurate prediction of the remaining useful life (RUL) of lithium-ion battery is of great
significance for the reliability of electronic equipment. In the conventional approaches, there …
significance for the reliability of electronic equipment. In the conventional approaches, there …
Joint nonlinear-drift-driven Wiener process-Markov chain degradation switching model for adaptive online predicting lithium-ion battery remaining useful life
The accurate prediction of the remaining useful life (RUL) of lithium-ion batteries is very
important for battery management systems and predictive maintenance. However, lithium …
important for battery management systems and predictive maintenance. However, lithium …
Overview of machine learning methods for lithium-ion battery remaining useful lifetime prediction
Lithium-ion batteries play an indispensable role, from portable electronic devices to electric
vehicles and home storage systems. Even though they are characterized by superior …
vehicles and home storage systems. Even though they are characterized by superior …
Evolving Marine Predators Algorithm by dynamic foraging strategy for real-world engineering optimization problems
Abstract The Marine Predators Algorithm (MPA) is a novel hunting-based optimizer. The
MPA's central concept is based on the well-known Lévy Flight (LF) and Brownian Motion …
MPA's central concept is based on the well-known Lévy Flight (LF) and Brownian Motion …
Unmanned aerial vehicle flight data anomaly detection and recovery prediction based on spatio-temporal correlation
With the development of unmanned aerial vehicle (UAV) technology, a UAV is gradually
applied to a variety of civil fields, such as photography, power line inspection, and …
applied to a variety of civil fields, such as photography, power line inspection, and …
Multiscale similarity ensemble framework for remaining useful life prediction
Accurate prediction of remaining useful life (RUL) is crucially important to perform
prognostics and health management. A new similarity-based autoencoder multiscale …
prognostics and health management. A new similarity-based autoencoder multiscale …
Remaining useful life prediction and cycle life test optimization for multiple-formula battery: A method based on multi-source transfer learning
Achieving highly accurate predictions based on less data with multiple formulations has
become a significant challenge. Unlike the traditional prediction model that ignores the …
become a significant challenge. Unlike the traditional prediction model that ignores the …