Lithium-ion batteries (LIBs) are crucial for the large-scale utilization of clean energy.
However, because of the complexity and real-time nature of internal reactions, the …

This is a critical review of artificial intelligence/machine learning (AI/ML) methods applied to
battery research. It aims at providing a comprehensive, authoritative, and critical, yet easily …

Accurate estimation of lithium-ion battery capacity is crucial for ensuring its safety and
reliability. While data-driven modelling is a common approach for capacity estimation …

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 …

Lithium-ion batteries are ubiquitous in applications ranging from portable electronics to
electric vehicles. Irrespective of the application, reliable real-time estimation of battery state …

Accurate battery life prediction is a critical part of the business case for electric vehicles,
stationary energy storage, and nascent applications such as electric aircraft. Existing …

Designing and deployment of state-of-the-art electric vehicles (EVs) in terms of low cost and
high driving range with appropriate reliability and security are identified as the key towards …

Abstract State-of-health (SOH) monitoring of lithium-ion batteries plays a key role in the
reliable and safe operation of battery systems. Influenced by multiple factors, SOH is an …

Forecasting the state of health and remaining useful life of Li-ion batteries is an unsolved
challenge that limits technologies such as consumer electronics and electric vehicles. Here …

Accurate degradation monitoring over battery life is indispensable for the safe and durable
operation of battery-powered applications. In this work, we extend conventional capacity …