Journal
JOURNAL OF POWER SOURCES
Volume 556, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.jpowsour.2022.232461
Keywords
Battery degradation; Phase transition; Nickel-rich positive electrodes; Degradation mode analysis
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Nickel-rich layered oxides are commonly used as positive electrode materials in lithium-ion batteries, but their degradation mechanisms are not well understood. In this study, a particle-level model is proposed to describe the structural degradation due to phase transition, including loss of active material, loss of lithium inventory, and resistance increase. The model is incorporated into a cell-level P2D model to investigate the effects of degradation on capacity fade. It is found that the loss of positive electrode active materials dominates the capacity loss, while trapped cyclable lithium in the degraded shell does not directly contribute to the loss.
Nickel-rich layered oxides have been widely used as positive electrode materials for high-energy-density lithium-ion batteries, but the underlying mechanisms of their degradation have not been well understood. Here we present a model at the particle level to describe the structural degradation caused by phase transition in terms of loss of active material (LAM), loss of lithium inventory (LLI), and resistance increase. The particle degradation model is then incorporated into a cell-level P2D model to explore the effects of LAM and LLI on capacity fade in cyclic ageing tests. It is predicted that the loss of cyclable lithium (trapped in the degraded shell) leads to a shift in the stoichiometry range of the negative electrode but does not directly contribute to the capacity loss, and that the loss of positive electrode active materials dominates the fade of usable cell capacity in discharge. The available capacity at a given current rate is further decreased by the additional resistance of the degraded shell layer. The change pattern of the state-of-charge curve provides information of more dimensions than the conventional capacity-fade curve, beneficial to the diagnosis of degradation modes. The model has been implemented into PyBaMM and the source codes are openly available in the GitHub repository https://github.com/mzzhuo/PyBaMM/tree/pe_degradation.
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