Modelling of modular battery systems under cell capacity variation and degradation

We propose a simple statistical model of electrochemical cell degradation based on the general characteristics observed in previous large-scale experimental studies of cell degradation. This model is used to statistically explore the behaviour and lifetime performance of battery systems where the cells are organised into modules that are controlled semi-independently. Intuitively, such systems should offer improved reliability and energy availability compared to monolithic systems as the system ages and cells degrade and fail. To validate this intuition, this paper explores the capacity evolution of populations of systems composed of random populations of cells. This approach allows the probability that a given system design meets a given lifetime specification to be calculated. A cost model that includes the effect of uncertainty in degradation behaviour is introduced and used to explore the cost-benefit trade-offs arising from the interaction of degradation and module size. Case studies of an electric vehicle battery pack and a grid-connected energy storage system are used to demonstrate the use of the model to find lifetime cost-optimum designs. It is observed that breaking a battery energy storage system up into smaller modules can lead to large increases in accessible system capacity and may lead to a decision to use lower-quality, lower-cost cells in a cost-optimum system.

Automated summary

A statistical model is proposed to explore the behavior and lifetime performance of battery systems, considering the degradation of cells and the benefits of organizing cells into semi-independent modules. The cost model is introduced to analyze the trade-offs between degradation, module size, and cost benefits. Case studies reveal that breaking a battery energy storage system into smaller modules can increase system capacity and reduce costs.