In situ identification of electrochemical impedance spectra for Li-ion batteries

Abstract

The monitoring and control of battery systems can be enhanced by data collection and analysis that provide insight into the internal behavior of the battery. A well-known example is electrochemical impedance spectroscopy (EIS), which is equivalent to estimating the frequency response of the battery impedance at a particular operating condition. System identification provides a method for implementing EIS using hardware commonly found in advanced battery-management systems. In this chapter, a possible implementation of online system identification is discussed and illustrated using both simulation and experimental data.