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 …
Physics-based battery SOC estimation methods: Recent advances and future perspectives
The reliable prediction of state of charge (SOC) is one of the vital functions of advanced
battery management system (BMS), which has great significance towards safe operation of …
battery management system (BMS), which has great significance towards safe operation of …
Data-driven lithium-ion batteries capacity estimation based on deep transfer learning using partial segment of charging/discharging data
Accurate estimation of lithium-ion battery capacity is crucial for ensuring its safety and
reliability. While data-driven modelling is a common approach for capacity estimation …
reliability. While data-driven modelling is a common approach for capacity estimation …
A comprehensive review of digital twin—part 1: modeling and twinning enabling technologies
As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented
attention because of its promise to further optimize process design, quality control, health …
attention because of its promise to further optimize process design, quality control, health …
Physics-informed neural network approach for heat generation rate estimation of lithium-ion battery under various driving conditions
Accurate insight into the heat generation rate (HGR) of lithium-ion batteries (LIBs) is one of
key issues for battery management systems to formulate thermal safety warning strategies in …
key issues for battery management systems to formulate thermal safety warning strategies in …
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 enables rapid state of health estimation of each cell within battery pack
Q Yu, Y Nie, S Guo, J Li, C Zhang - Applied Energy, 2024 - Elsevier
The health and safety of the battery pack are directly influenced by the state of health of its
cells. However, due to the aging inconsistency among cells and the limited measurability of …
cells. However, due to the aging inconsistency among cells and the limited measurability of …
[HTML][HTML] Review of “grey box” lifetime modeling for lithium-ion battery: Combining physics and data-driven methods
Lithium-ion batteries are a popular choice for a wide range of energy storage system
applications. The current motivation to improve the robustness of lithium-ion battery …
applications. The current motivation to improve the robustness of lithium-ion battery …
[HTML][HTML] Physics-informed machine learning: a comprehensive review on applications in anomaly detection and condition monitoring
Condition monitoring plays a vital role in ensuring the reliability and optimal performance of
various engineering systems. Traditional methods for condition monitoring rely on physics …
various engineering systems. Traditional methods for condition monitoring rely on physics …
Accurate Model Parameter Identification to Boost Precise Aging Prediction of Lithium‐Ion Batteries: A Review
S Ding, Y Li, H Dai, L Wang, X He - Advanced Energy Materials, 2023 - Wiley Online Library
Precise prediction of lithium‐ion cell level aging under various operating conditions is an
imperative but challenging part of ensuring the quality performance of emerging applications …
imperative but challenging part of ensuring the quality performance of emerging applications …