Lithium-ion batteries have become the primary electrical energy storage device in
commercial and industrial applications due to their high energy/power density, high …

The emergence of artificial intelligence (AI) and, more particularly, machine learning (ML),
has had a significant impact on engineering and the fundamental sciences, resulting in …

Accurate estimation of the state of charge (SOC) and temperature of batteries is essential to
ensure the safety of energy storage systems. However, it is very difficult to obtain multiple …

Due to the inability to directly measure the internal state of batteries, there are technical
challenges in battery state estimation, defect detection, and fault diagnosis. Ultrasonic …

Lithium-ion batteries have become one of the most critical energy storage systems due to
their long cycle life and high energy density. Ultrasonic testing technology has been applied …

Ultrasonic non-destructive testing technology has been applied to battery state estimation
applications to ensure the safety of the energy storage system. However, the accuracy and …

The uneven distribution of state of charge (SoC) in the lithium-ion battery is a key factor to
cause fast decay of local electrochemical performance. Here, we report an acoustic method …

The health management of batteries is a key enabler for the adoption of Electric Vertical
Take-off and Landing vehicles (eVTOLs). Currently, few studies consider the health …

Machine learning methods for state of charge (SOC) estimation of lithium-ion batteries (LiBs)
face the problem of domain shift. Varying conditions, such as different ambient temperatures …

This paper proposes methods of battery state-of-charge (SoC) estimation using Gaussian
processes (GPs): GP-Unscented Kalman filter (GP-UKF) and GP-Particle filter (GP-PF) …