Advanced Modelling, Operation, Management and Diagnosis of Lithium Batteries

Submission Deadline: 28 February 2025 Submit to Special Issue

Guest Editors

Summary

Lithium batteries are currently used in many fields because of the advantages of low self-discharge rate, long cycle life, high power density, and environmental friendliness, etc. Due to the aging of lithium-ion batteries, local short circuits, leakage, and insulation damage may occur. If not detected in time, it will have adverse effects on the safe operation of the energy storage power station where it is located. Therefore, in the field of advanced lithium battery technology, modeling, operation, management, state monitoring, and diagnosis are indispensable key elements, and batteries management systems are crucial for the safe and efficient operation of batteries. Through precise modeling, a deeper understanding of the internal chemical and physical processes of lithium batteries is gained, which can provide a foundation for optimizing performance. At the operational aspect, advanced control strategies ensure stable operation of the systems of batteries under various working conditions and extend the lifespans of batteries. In terms of management, special attention is paid to the health status of batteries, and through real-time monitoring and diagnostic algorithms, batteries performance degradation can be effectively evaluated. Therefore, it is imperative to develop and apply advanced technologies for modelling, operation, management, and diagnosis of various lithium batteries.

This special section aims to make effective contributions, highlighting all solutions, methods, methods, and tools to collect state-of-the-art research, with a focus on the latest investigations and research on lithium batteries modeling, operation, management, and diagnostic strategies. We invite researchers and experts from all over the world to submit high-quality original research papers and commentary articles on potential future topics.

Potential topics aim at covering themes including, but not limited to:

Modelling and simulation of lithium batteries;

Intelligent optimization operation planning and control of lithium batteries;

State monitoring and estimation of lithium batteries (e.g., state-of-charge estimation, state-of-health estimation, etc.);

Life prediction and management of lithium batteries (e.g., remaining life prediction, etc.);

Fault detection and diagnosis of lithium batteries systems.

Keywords

Published Papers