Nondestructive diagnostics and quantification of battery aging under different degradation paths

Identification and quantification of degradation mechanisms of lithium ion batteries are crucial but highly challenging due to their complex coupling effects and varying operating conditions. In this paper, we propose a nondestructive aging diagnostics methodology by identifying aging-related parameters of a physics-based battery model from the beginning-of-life (BOL) to end-of-life (EOL). The proposed method is applied and validated on 7 cells at 4 test conditions, considering different cycling conditions, cell-to-cell variations and calendar aging. Nearly 200 identifications of 12 aging-related parameters are performed at different degradation stages across the lifetimes of those cells. By observing the evolution trajectories of those parameters at different cycle and calendar aging scenarios, we show quantitatively that the degradation rates of the cells are impacted by different patterns in the changes of aging parameters. The method could also capture subtle cell-to-cell variations in battery degradation by quantifying the discrepancies of the aging parameters over time. This work demonstrates the promise of applying physics-based models for nondestructive degradation diagnostics and provides a quantitative perspective for degradation modes analysis.

Automated summary

In this paper, a nondestructive aging diagnostics methodology is proposed to identify aging-related parameters of a physics-based battery model from the beginning-of-life (BOL) to end-of-life (EOL). The proposed method is applied and validated on 7 cells at 4 test conditions, considering different cycling conditions, cell-to-cell variations, and calendar aging. The results show that the degradation rates of the cells are impacted by different patterns in the changes of aging parameters and the method can capture subtle cell-to-cell variations in battery degradation.