Life Prediction and Modelling

Estimating And Extrapolating Degradation Modes From Accelerated Aging Data To Estimate Both Capacity Fade And Open-Circuit-Voltage Curve Shifts Throughout Battery Lifetime Degradation modes like loss of lithium inventory LLI) and loss of active material in positive and negative electrodes LAM PE, LAMNE) have been calculated using differential voltage or incremental capacity analysis for many years. Karger et al. 1] and Stadler et al. 2] demonstrate mapping of LLI, LAM, and capacity evolution across many operating conditions, enabling estimation of open-circuit-voltage curve shifts and capacity changes in dynamic real-world operation. This approach can be implemented using standard accelerated aging data and substantially improves predictive accuracy.

Left Karger et al. 1] fit empirical models for LLI and LAM evolution versus operating conditions, including temperature, depth-of-discharge, upper cut-off voltage, of an NCA|Gr-Si cell. The resulting model reduces estimation error of the shape of the open-circuit-voltage curve by up to 8x, versus predicting using only capacity. Right Stadler et al. 2] summarize the workflow for identifying (‘Analysisʼ) and then extrapolating (‘Predictionʼ) capacity and OCV models.

Source: 1 Karger et al Journal of Power Sources 593, 2 Stadler et al Batteries and Supercaps e202400211

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