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 …

Rechargeable batteries are vital in the domain of energy storage. However, traditional
experimental or computational simulation methods for rechargeable batteries still pose time …

Advanced battery management is as important for lithium-ion battery systems as the brain is
for the human body. Its performance is based on the use of fast and accurate battery models …

In recent years, batteries have evolved increasingly overall in numerous applications.
Among batteries, LIBs are the most advantageous technology because of their raised power …

Accurate forecasting of the lifetime and degradation mechanisms of lithium-ion batteries is
crucial for their optimization, management, and safety while preventing latent failures …

Battery characterization and prognosis are essential for analyzing underlying
electrochemical mechanisms and ensuring safe operation, especially with the assistance of …

An accurate state estimator is critical to Battery Management Systems (BMSs). In more
advanced BMSs, state estimators based on electrochemical-thermal battery models are …

The optimization of the electrode manufacturing process is important for upscaling the
application of Lithium-Ion Batteries (LIBs) to cater for growing energy demand. LIB …

Data selection is a practical technique for improving parameter estimation accuracy through
the strategic selection of information-rich data for use in the estimation algorithm. Traditional …

Monitoring the health of lithium-ion batteries' internal components as they age is crucial for
optimizing cell design and usage control strategies. However, quantifying component-level …