[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 …
Battery prognostics and health management from a machine learning perspective
Transportation electrification is gaining prominence as a significant pathway for reducing
emissions and enhancing environmental sustainability. Central to this shift are lithium-ion …
emissions and enhancing environmental sustainability. Central to this shift are lithium-ion …
Machine learning for predicting battery capacity for electric vehicles
Predicting the evolution of multiphysics battery systems face severe challenges, including
various aging mechanisms, cell-to-cell variation and dynamic operating conditions. Despite …
various aging mechanisms, cell-to-cell variation and dynamic operating conditions. Despite …
[HTML][HTML] Two-stage aging trajectory prediction of LFP lithium-ion battery based on transfer learning with the cycle life prediction
With the wide application of the LFP lithium-ion batteries, more attention is paid to the battery
life and future aging behaviors as the safety and performance of the battery are guaranteed …
life and future aging behaviors as the safety and performance of the battery are guaranteed …
Early prediction of battery lifetime via a machine learning based framework
Accurately predicting the lifetime of lithium-ion batteries in early cycles is crucial for ensuring
the safety and reliability, and accelerating the battery development cycle. However, most of …
the safety and reliability, and accelerating the battery development cycle. However, most of …
An overview of data-driven battery health estimation technology for battery management system
Battery degradation, caused by multiple coupled degradation mechanisms, severely affects
the safety and sustainability of a battery management system (BMS). The battery state of …
the safety and sustainability of a battery management system (BMS). The battery state of …
Deep feature extraction in lifetime prognostics of lithium-ion batteries: Advances, challenges and perspectives
The wide application of lithium-ion batteries makes their lifecycle prognosis a challenging
and hot topic in the battery management research field. Feature extraction is a key step for …
and hot topic in the battery management research field. Feature extraction is a key step for …
Towards machine-learning driven prognostics and health management of Li-ion batteries. A comprehensive review
Prognostics and health management (PHM) has emerged as a vital research discipline for
optimizing the maintenance of operating systems by detecting health degradation and …
optimizing the maintenance of operating systems by detecting health degradation and …
The role of natural resources in the management of environmental sustainability: Machine learning approach
This study examines the ability of Asia's natural resources to manage environmental
sustainability through digitalization. We analyse 19 Asian nations from 1990 to 2020. In …
sustainability through digitalization. We analyse 19 Asian nations from 1990 to 2020. In …
Voltage-temperature health feature extraction to improve prognostics and health management of lithium-ion batteries
Prognostics and health management (PHM) of lithium-ion batteries are important to ensure
the safety of electric vehicles. To date, there has not been an adequate method to accurately …
the safety of electric vehicles. To date, there has not been an adequate method to accurately …