Estimating the state of health is a critical function of a battery management system, but
remains challenging due to variability of operating conditions and usage requirements in …

Accurately predicting the future health of batteries is necessary to ensure reliable operation,
minimise maintenance costs, and calculate the value of energy storage investments. The …

Lithium-ion batteries are increasingly ubiquitous in modern society but the degradation of
lithium-ion cells is complex and challenging to predict. Data-driven approaches to estimating …

Equivalent circuit models for batteries are commonly used in electric vehicle battery
management systems to estimate state of charge and other important latent variables. They …

Accurately predicting in-situ battery life is critical to evaluate the system's reliability and
residual value. The high complexity of battery aging evolution under variable conditions …

The wide usage of Lithium-ion batteries (LIBs) requires a deep understanding about battery
health. Estimation of battery state-of-health (SOH) is a crucial but yet still challenging task …

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 …

Accurately predicting battery aging is critical for mitigating performance degradation during
battery usage. While the automotive industry recognizes the importance of utilizing field data …

Accurately predicting the future capacity and remaining useful life of batteries is necessary to
ensure reliable system operation and to minimise maintenance costs. The complex nature of …

Lithium-ion batteries (LIBs) have attracted widespread attention as an efficient energy
storage device on electric vehicles (EV) to achieve emission-free mobility. However, the …