Condition Monitoring and Life Prediction of Lithium-Ion Batteries
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D2: Electrochem: Batteries, Fuel Cells, Capacitors".
Deadline for manuscript submissions: 10 September 2026 | Viewed by 2
Special Issue Editor
Special Issue Information
Dear Colleagues,
Lithium-ion batteries have become a core enabler of modern electrification—powering electric vehicles, renewable integration, grid-scale storage, and portable electronics. As deployments scale up and operating profiles become harsher (fast charging, temperature variability, high utilization, etc.), the need for reliable condition monitoring and accurate lifetime prediction is more urgent than ever. Better diagnostics and prognostics translate directly into improved safety, availability, warranty confidence, and total cost of ownership, while also unlocking smarter second-life decisions.
This Special Issue aims to bring together the most recent advances in battery diagnostics, health estimation, and prognostics, spanning lab-to-field validation and methods ready for BMS/embedded implementation. We especially welcome submissions that connect measurable signals (V–I–T, impedance, expansion, etc.) to actionable outputs (SOC/SOH/SOP, degradation modes, RUL) with clear validation and uncertainty awareness.
Topics of interest include (but are not limited to) the following:
- Online/offline condition monitoring and early fault detection (anomaly detection, thermal/fast-charge risks);
- SOC/SOH/SOP estimation under realistic operating conditions;
- RUL and lifetime prediction with uncertainty quantification;
- Feature extraction and diagnostics: ICA/DVA, impedance-based indicators, and resistance and polarization tracking;
- Data-driven approaches (ML/DL, LSTM/transformers, transfer learning) and hybrid/physics-informed models (digital twins);
- Cell-to-pack scaling, robustness with limited sensors, explainability, and benchmarking;
- Aging datasets, test protocols, and validation on real duty cycles (EV, grid, fast charging).
If you offer recent results, a strong methodology, or a compelling dataset in this area, your contribution would be very welcome. Feel free to share this invitation with your group and collaborators.
Dr. Panagiotis Eleftheriadis
Guest Editor
Manuscript Submission Information
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Keywords
- lithium-ion batteries
- state of health (SOH)
- remaining useful life (RUL)
- condition monitoring
- data-driven diagnostics
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