Synergizing machine learning and the aviation sector in lithium-ion battery applications: a review
J Chen, G Qi, K Wang - Energies, 2023 - mdpi.com
Lithium-ion batteries, as a typical energy storage device, have broad application prospects.
However, developing lithium-ion batteries with high energy density, high power density, long …
However, developing lithium-ion batteries with high energy density, high power density, long …
Opportunities and Challenges in Transformer Neural Networks for Battery State Estimation: Charge, Health, Lifetime, and Safety
Battery technology plays a crucial role across various sectors, powering devices from
smartphones to electric vehicles and supporting grid-scale energy storage. To ensure their …
smartphones to electric vehicles and supporting grid-scale energy storage. To ensure their …
[HTML][HTML] Artificial intelligence-driven real-world battery diagnostics
Addressing real-world challenges in battery diagnostics, particularly under incomplete or
inconsistent boundary conditions, has proven difficult with traditional methodologies such as …
inconsistent boundary conditions, has proven difficult with traditional methodologies such as …
State of health estimation for lithium-ion batteries using Gaussian process regression-based data reconstruction method during random charging process
State of health (SOH) estimation is a critical technology to guarantee the safe and reliable
operation of battery energy systems. Data-driven methods have been widely studied in the …
operation of battery energy systems. Data-driven methods have been widely studied in the …
AI‐Driven Digital Twin Model for Reliable Lithium‐Ion Battery Discharge Capacity Predictions
The present study proposes a novel method for predicting the discharge capabilities of
lithium‐ion (Li‐ion) batteries using a digital twin model in practice. By combining cutting …
lithium‐ion (Li‐ion) batteries using a digital twin model in practice. By combining cutting …
[HTML][HTML] Optimized XGBoost modeling for accurate battery capacity degradation prediction
Lithium-ion batteries have notable benefits in their elevated energy power, density, and
efficiency. However, the deterioration of capacity remains a prominent concern throughout …
efficiency. However, the deterioration of capacity remains a prominent concern throughout …
Refined lithium-ion battery state of health estimation with charging segment adjustment
K Zheng, J Meng, Z Yang, F Zhou, K Yang, Z Song - Applied Energy, 2024 - Elsevier
Accurately monitoring the state of health (SOH) of lithium-ion batteries (LIBs) is crucial for
battery management systems (BMS), yet there lack of the possibility to fully use the random …
battery management systems (BMS), yet there lack of the possibility to fully use the random …
A real-time prognostic-based control framework for hybrid electric vehicles
The increasing popularity of electric vehicles is driven by their compatibility with sustainable
energy goals. However, the decline in the performance of energy storage systems, such as …
energy goals. However, the decline in the performance of energy storage systems, such as …
Battery pack capacity estimation for electric vehicles based on enhanced machine learning and field data
Accurate capacity estimation is of great importance for the reliable state monitoring, timely
maintenance, and second-life utilization of lithium-ion batteries. Despite numerous works on …
maintenance, and second-life utilization of lithium-ion batteries. Despite numerous works on …
Deep neural network-enabled battery open-circuit voltage estimation based on partial charging data
Battery management systems (BMSs) play a vital role in ensuring efficient and reliable
operations of lithium-ion batteries. The main function of the BMSs is to estimate battery …
operations of lithium-ion batteries. The main function of the BMSs is to estimate battery …