Passive tracking of the electrochemical impedance of a hybrid electric vehicle battery and state of charge estimation through an extended Kalman filter

Abstract

Significant information concerning the characteristics of a Lithium battery is provided by the electrical impedance measurements. The reference method of analysis consists of performing electrochemical impedance spectroscopy (EIS). Although robust, it usually cannot be used for an embedded system, such as the hybrid electric vehicle (HEV) because it is an expensive, complex, and very time-consuming method. The contribution of this paper allows to overcome these issues and to address embedded applications. This article proposes a passive methodology for impedance estimation that consists of using the natural current and voltage profile produced by the battery through its regular use without adding any excitation signal. The validity of this impedance estimation is proved by obtaining similar impedance measurement of the same battery with a different passive current and voltage profile. Moreover, this impedance measurement is used for estimating the battery state of charge (SoC) through an extended Kalman filter (EKF).