Battery storage

Grid-scale battery energy storage differs from other rechargeable battery applications, such as mobility or portable electronics, as the mass and volume are much less important. However, the lifetime and safety are paramount for stationary applications, and therefore after years of research on increasing capacity of lithium ion cells, the focus in industry has shifted to extending battery life. This is particularly important for application of batteries for grid storage, where warrantying the cycle life of the expensive storage unit is more important than decreasing its size and mass.

Although many cell degradation mechanisms are identified and studied, they are not yet well enough understood to be predicted quantitatively in real-life battery cells, particularly in response to the range of load conditions that may be faced during grid storage applications, which can be more varied than current-controlled charge/discharge for consumer electronics.

Degradation of battery is understood to result from loss processes associated with the chemistry, e.g. the consumption of lithium during solid-electrolyte interphase formation, and structural heterogeneity, e.g. restricted transport can lead to overpotentials and lithium plating during charge.

Due to the complexity of materials used in a modern battery cell, and their operation principles, in order to adequately model the battery materials and processes multiscale modelling approaches need to be used, as performance and degradation of the batteries can be on atomic, materials or its component level. Each of them need to be accounted for in order to understand the aging processes and being able to regenerate the health of the battery, where possible.

Therefore, our project is designated to develop algorithms to identify safety-endangering states of battery as well as predict lifetime of compatible battery chemistries. In addition, their resilience to various unpredictable “abuse” scenarios is evaluated. The aim is to create an experimental-data driven model, allowing the knowledge to be integrated into a battery management system or an overall control system.

Please contact Sigita Trabesinger for more information.