Interval method for an efficient state of charge and capacity estimation of multicell batteries

Abstract

Concerning large battery systems, the estimation of pack state of charge and state of health remains a challenging problem which needs to be solved under limited computational resources of a battery management system. Instead of multiplicating the existing model-based techniques for individual cells, a novel method is proposed which aims at effectively and reliably determining the pack conditions for cells connected in series. In order to realize an accurate estimation, definitions of pack SOC and pack capacity are carefully studied first. Due to the fact that a battery pack is usually restricted by the two cells with maximum and minimum voltage during the charging and discharging process, respectively. The investigated approach computes the battery SOC by considering the voltage limit of a battery pack, regardless the number of cells. In this way, a trade-off between the accurate knowledge of all cells and the real-time capability is presented. In order to fulfill the task of verification, different approaches such as simulation with modeled cell variation, offline validation with measured data, and online test with a battery module are conducted. The state estimation for battery pack show convincing results in the entire operating range, while the computational complexity can be significantly reduced.