The Lithium-Ion Battery Temperature Field Prediction Model
This study focuses on the internal temperature field of lithium-ion batteries, aiming to address the temperature variation issues arising from complex operating conditions in new
A hybrid neural network based on KF-SA-Transformer for SOC prediction
To verify the effectiveness of the algorithm in predicting battery SOC, an open-source lithium-ion battery dataset was used as a case study in this paper.
Lithium–Ion Battery Data: From Production to Prediction
From data generation to the most advanced analysis techniques, this article addresses the concepts, tools and challenges related to battery informatics with a holistic
Enhancing Lithium-Ion Battery Temperature Prediction with a
Abstract: This study focuses on the internal temperature field of lithium-ion batteries, aimed at addressing the temperature variations caused by complex operating conditions in
A hybrid neural network based on KF-SA
To verify the effectiveness of the algorithm in predicting battery SOC, an open-source lithium-ion battery dataset was used as a
Operational risk analysis of a containerized lithium-ion battery
This work discusses the operational risks of MW-class containerized lithium-ion BESS and provides technical guidance for engineers in system designs, safe operations, and
Three-dimensional Temperature Field Reconstruction for A
In this study, three-dimensional thermal model is established first for a LiB pack configured in series. spatially resolved, this model captures spatial thermal behavior
Lithium–Ion Battery Data: From Production to
From data generation to the most advanced analysis techniques, this article addresses the concepts, tools and challenges
Lithium-Ion Battery Data: From Production to Prediction
From data generation to the most advanced analysis techniques, this article addresses the concepts, tools and challenges related to battery informatics with a holistic
Enhancing Lithium-Ion Battery Temperature
Abstract: This study focuses on the internal temperature field of lithium-ion batteries, aimed at addressing the temperature variations
An interpretable capacity prediction method for lithium-ion
Predicting the capacity of lithium‐ion battery (LIB) plays a crucial role in ensuring the safe operation of LIBs and prolonging their lifespan. However, LIBs are easily afected by...
Lithium-Ion Battery Data: From Production to
From data generation to the most advanced analysis techniques, this article addresses the concepts, tools and challenges
The Lithium-Ion Battery Temperature Field Prediction Model
Abstract: This study focuses on the internal temperature field of lithium-ion batteries, aiming to address the temperature variation issues arising from complex operating condi-tions in new
Advancing Lithium-ion Battery Prognostics: A Novel Deep
The field of Lithium-ion battery prognostics has witnessed a surge in research employing deep learning methodologies to forecast both the Remaining Useful Life