Data-selection for state estimation of large-scale battery systems

Abstract

Large-scale battery energy storage systems (BESS) are drawing the attention of researchers as numbers installed globally is rising rapidly. Like single cells, the battery states, most importantly state of charge (SOC) and state of health (SOH) of BESSs are essential for their operation. However, for large-scale battery systems, the data granularity, accuracy and quality are limited compared with the cell-level. To achieve accurate state estimation of battery systems the selection of data used for processing is essential. In this paper, it is shown that how to evaluate and select system-level data for SOC and SOH estimation. These methods are expected to be used for other BESSs.