Semi-empirical cyclic aging model for stationary storages based on graphite anode aging mechanisms

Battery life prediction is steadily becoming more relevant due to the increased use of batteries in stationary and mobile applications. Current semi-empirical aging models are often supplemented by empirical model equations and parametrized on the entire available measurement data set. This practice limits their extrapolation capability and transferability. The model in this work describes the two important anode aging mechanisms, solid electrolyte interface (SEI) cracking and reforming and cracking of the active material, by completely physically based equations. A simple incremental capacity analysis (ICA) method is introduced to allow targeted parameterization of the model equations with measurement data, in which the aging modes associated with the respective aging mechanism are present. The overall model can accurately describe the battery capacity loss under dynamic frequency containment reserve loading. It is transferable to all graphite-based battery cell chemistries and provides a basis for future semi-empirical aging models, describing the capacity loss in a wide variety of applications by considering further aging mechanisms.

Automated summary

Battery life prediction is important due to increased battery use. This study presents a physically based model that accurately describes battery capacity loss under dynamic frequency containment reserve loading. The model considers two important aging mechanisms and can be applied to graphite-based battery cell chemistries.