The rapid development of lithium-ion battery (LIB) technology promotes its wide application
in electric vehicle (EV), aerospace, and mobile electronic equipment. During application …

Further applications of electric vehicles (EVs) and energy storage stations are limited
because of the thermal sensitivity, volatility, and poor durability of lithium-ion batteries (LIBs) …

Accurate capacity estimation is crucial for the reliable and safe operation of lithium-ion
batteries. In particular, exploiting the relaxation voltage curve features could enable battery …

Accurately monitoring battery states over battery life plays a central role in building
intelligent battery management systems. This study proposes a flexible method using only …

Predicting future capacities and remaining useful life (RUL) with uncertainty quantification is
a key but challenging issue in the applications of battery health diagnosis and management …

Lithium ion batteries (LIBs) are booming due to their high energy density, low maintenance,
low self-discharge, quick charging and longevity advantages. However, the thermal stability …

Abstract Machine learning-based methods have emerged as a promising solution to
accurate battery capacity estimation for battery management systems. However, they are …

Accurate state of health estimation for lithium-ion batteries is crucial to ensure the safety and
reliability of electric vehicles. This study presents an accurate state of health estimation …

Battery state-of-health (SOH) estimation is a critical concern of the battery management
system, which significantly affects the safe and stable operation of electric vehicles. The …

State of health (SOH) is a key parameter to assess lithium-ion battery feasibility for
secondary usage applications. SOH estimation based on machine learning has attracted …