Abstract Machine learning (ML) and deep learning (DL) have enabled algorithms to
autonomously acquire knowledge from data, facilitating predictive and decision-making …

The widespread growth of electric vehicles (EV) s has highlighted the need for effective
diagnostic and prognostic techniques for EV battery faults. Lately, deep learning (DL) …

Accurately estimating the state of charge (SOC) of lithium-ion batteries by the battery
management system (BMS) is crucial for safe electric vehicle (EV) operations. This paper …

Batteries have been considered a key element in several applications, ranging from grid-
scale storage systems through electric vehicles to daily-use small-scale electronic devices …

Several currently popular data-driven estimators such as Long Short-Term Memory-
Recurrent Neural Networks (LSTM-RNN) rely on a single strong model which produces …

Batteries play a crucial role as energy storage devices across various industries. However,
achieving high performance often comes at the cost of safety. Continuous monitoring is …

The primary focus in electrifying the transportation sector should be sustainability. This can
be effectively attained through the application of the seven eco-efficiency principles, which …

Accurate estimation of the state of charge (SOC) and available capacity is crucial for the
rational use and safety protection of a battery. In this paper, an adaptive SOC estimation …

Lithium-ion batteries (LIBs) are used as energy storage systems due to their high efficiency.
State of charge (SOC) estimation is one of the key functions of the battery management …

To ensure the safety and reliability of an echelon-use lithium-ion battery (EULIB), the
performance of a EULIB is accurately reflected. This paper presents a method of estimating …