Cover Feature: Combining a Data Driven and Mechanistic Model to Predict Capacity and Potential Curve‐Degradation (Batteries & Supercaps 10/2024)
The Cover Feature illustrates lithium-ion battery degradation. It demonstrates how individual aging modes—the loss of accessible active material from an electrode or the depletion of cyclable lithium ions—affect the capacities and balancing between the electrodes. These changes are visualized by color-coded surfaces that represent electrode potentials in the full cell′s cyclation window, transitioning from green to red to indicate degradation. Such alterations lead to a measurable capacity fade and changes in the full cell′s potential curve, as depicted by the differential voltage curve. The underlying work combines this mechanistic model with a data-driven model approach of the individual aging modes to predict both capacity fade and changes to the potential curve under various aging conditions. This will help to enhance understanding and prediction of battery degradation and can be the basis for a more precise onboard state-of-charge and state-of-health estimation of degraded batteries. More information can be found in the Research Article by J. Stadler and co-workers (DOI: 10.1002/batt.202400211).
Authors
- Arnulf Latz (ORCID: https://orcid.org/0000-0003-1449-8172)
- Jochen Stadler (ORCID: https://orcid.org/0000-0003-4339-8912)
- Johannes Philipp Fath (ORCID: https://orcid.org/0000-0002-5804-3797)
- Madeleine Ecker
Institutions
- Mercedes-Benz (Germany) (DE)
- Universität Ulm (DE)
- Helmholtz-Institute Ulm (DE)
Publication Details
- Journal
- Batteries & Supercaps
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1002/batt.202481003
- Primary Topic
- Advanced Battery Technologies Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00