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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 …
Review on state of charge estimation techniques of lithium-ion batteries: A control-oriented approach
Energy storage has become one of the most critical issues of modern technology. In this
regard, lithium-ion batteries have proven effective as an energy storage option. To optimize …
regard, lithium-ion batteries have proven effective as an energy storage option. To optimize …
[HTML][HTML] Intelligent fault diagnosis methods toward gas turbine: A review
LIU **aofeng, C Yingjie, L **ong, W Jianhua… - Chinese Journal of …, 2024 - Elsevier
Fault diagnosis plays a significant role in conducting condition-based maintenance and
health management for gas turbines (GTs) to improve reliability and reduce costs. Various …
health management for gas turbines (GTs) to improve reliability and reduce costs. Various …
Characterization and identification towards dynamic-based electrical modeling of lithium-ion batteries
Lithium-ion batteries are widely recognized as a crucial enabling technology for the
advancement of electric vehicles and energy storage systems in the grid. The design of …
advancement of electric vehicles and energy storage systems in the grid. The design of …
[HTML][HTML] Systematic analysis of the impact of slurry coating on manufacture of Li-ion battery electrodes via explainable machine learning
The manufacturing process strongly affects the electrochemical properties and performance
of lithium-ion batteries. In particular, the flow of electrode slurry during the coating process is …
of lithium-ion batteries. In particular, the flow of electrode slurry during the coating process is …
Data‐Driven Battery Characterization and Prognosis: Recent Progress, Challenges, and Prospects
Battery characterization and prognosis are essential for analyzing underlying
electrochemical mechanisms and ensuring safe operation, especially with the assistance of …
electrochemical mechanisms and ensuring safe operation, especially with the assistance of …
Multilevel data-driven battery management: From internal sensing to big data utilization
A battery management system (BMS) is essential for the safety and longevity of lithium-ion
battery (LIB) utilization. With the rapid development of new sensing techniques, artificial …
battery (LIB) utilization. With the rapid development of new sensing techniques, artificial …
[HTML][HTML] A review of the applications of explainable machine learning for lithium–ion batteries: From production to state and performance estimation
Lithium–ion batteries play a crucial role in clean transportation systems including EVs,
aircraft, and electric micromobilities. The design of battery cells and their production process …
aircraft, and electric micromobilities. The design of battery cells and their production process …
Explainable neural network for sensitivity analysis of lithium-ion battery smart production
Battery production is crucial for determining the quality of electrode, which in turn affects the
manufactured battery performance. As battery production is complicated with strongly …
manufactured battery performance. As battery production is complicated with strongly …
Advancing lithium-ion battery health prognostics with deep learning: A review and case study
Lithium-ion battery prognostics and health management (BPHM) systems are vital to the
longevity, economy, and environmental friendliness of electric vehicles and energy storage …
longevity, economy, and environmental friendliness of electric vehicles and energy storage …