Health prognostics for lithium-ion batteries: mechanisms, methods, and prospects
Lithium-ion battery aging mechanism analysis and health prognostics are of great
significance for a smart battery management system to ensure safe and optimal use of the …
significance for a smart battery management system to ensure safe and optimal use of the …
Battery technologies and functionality of battery management system for EVs: Current status, key challenges, and future prospectives
Research and development towards electric vehicles (EVs) are getting exclusive attention
because of their eco-friendly nature, suppression of petroleum products, greener transport …
because of their eco-friendly nature, suppression of petroleum products, greener transport …
[HTML][HTML] Overview of batteries and battery management for electric vehicles
Popularization of electric vehicles (EVs) is an effective solution to promote carbon neutrality,
thus combating the climate crisis. Advances in EV batteries and battery management …
thus combating the climate crisis. Advances in EV batteries and battery management …
A review on second-life of Li-ion batteries: Prospects, challenges, and issues
High energy density has made Li-ion battery become a reliable energy storage technology
for transport-grid applications. Safely disposing batteries that below 80% of their nominal …
for transport-grid applications. Safely disposing batteries that below 80% of their nominal …
Machine learning: an advanced platform for materials development and state prediction in lithium‐ion batteries
Lithium‐ion batteries (LIBs) are vital energy‐storage devices in modern society. However,
the performance and cost are still not satisfactory in terms of energy density, power density …
the performance and cost are still not satisfactory in terms of energy density, power density …
Cloud-based in-situ battery life prediction and classification using machine learning
Y Zhang, M Zhao - Energy Storage Materials, 2023 - Elsevier
In-situ battery life prediction and classification can advance lithium-ion battery prognostics
and health management. A novel physical features-driven moving-window battery life …
and health management. A novel physical features-driven moving-window battery life …
Machine learning for battery systems applications: Progress, challenges, and opportunities
Abstract Machine learning has emerged as a transformative force throughout the entire
engineering life cycle of electrochemical batteries. Its applications encompass a wide array …
engineering life cycle of electrochemical batteries. Its applications encompass a wide array …
Remaining useful life and state of health prediction for lithium batteries based on empirical mode decomposition and a long and short memory neural network
Accurate estimation and prediction of the state of health (SOH) and remaining useful life
(RUL) are crucial for battery management systems, which have an important role in the field …
(RUL) are crucial for battery management systems, which have an important role in the field …
Predictive machine learning in optimizing the performance of electric vehicle batteries: Techniques, challenges, and solutions
This research paper explores the importance of optimizing the performance of electric
vehicle (EV) batteries to align with the rapid growth in EV usage. It uses predictive machine …
vehicle (EV) batteries to align with the rapid growth in EV usage. It uses predictive machine …
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 …