Differential pulse voltammetry analytics for lithium-ion battery degradation

• Published in: Cell reports physical science 2024-09, Vol.5 (9), p.102168, Article 102168
• Main Authors: Kabra, Venkatesh, Fear, Conner, Northrop, Paul W.C., Cole, J. Vernon, Mukherjee, Partha P.
• Format: Article
• Language: English
• Subjects: battery safety; degradation analytics; differential pulse voltammetry; fast charging; lithium-ion batteries
• ISSN: 2666-3864; 2666-3864
• DOI: 10.1016/j.xcrp.2024.102168

With the growing need for lithium-ion batteries in high-power applications, an accurate estimation of battery state of health is critical for long cyclability. In this work, an analytics approach based on pulse voltammetry is presented for lithium-ion batteries. A physics-based modeling framework is developed to predict pulse voltammogram signatures for generic voltage pulses. In combination with a parameter estimation technique, this model presents an in situ diagnostic tool that captures key electrode-specific parameters with rapid accuracy. Using this approach, we quantify degradation descriptors such as the growth of the resistive layer, interfacial area evolution, and lithium-intercalation state. Pulse voltammetry signatures, obtained periodically during fast-charge cycling experiments, show distinct trends at low temperature and room temperature. Active particle cracking plays a major role in the low-temperature capacity fade of lithium-ion cells, while a combination of cracking and impedance rise is the major cause of degradation at room temperature. [Display omitted] •An analytics approach based on pulse voltammetry is developed for lithium-ion batteries•A physics-based model is developed to capture key degradation mechanisms•Distinct degradation signatures manifest at different temperatures•Active material cracking plays a major role in the capacity fade at low temperatures Accurate quantification of state of health is critical to understand the lifetime of lithium-ion cells. Here, Kabra et al. develop a physics-based diagnostic framework based on pulse voltammetry that quantifies key degradation descriptors—such as the growth of the resistive layer, interfacial area evolution, and lithium-intercalation state—as a function of cycle number.