Abstract

Li-ion batteries gradually lose their capacity with time and use; therefore, aging forecasts are key to designs of battery powered systems. So far, cell-type-specific studies without standardized testing practices have lead to a variety of aging models in which generality, simplicity, and accuracy seem exclusive. Previous studies hint to an interplay of multiple mechanisms leading to capacity loss, which depend on cell chemistry and are affected by temperature, state of charge, and cycling rate. Here we show that, despite this complexity, the time dependence of the actual capacity follows a unique master curve, for several cell types aged under various different conditions. We discuss the statistical origin of this common behavior, and the testing practice required for the characterisation of a model. The master curve is a stretched exponential that describes many other phenomena in nature and is theoretically justified within a diffusion-to-traps depletion model. These findings provide a simple and broadly applicable framework for accurate life-time predictions.

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