State of health diagnosis model for lithium ion batteries based on real-time impedance and open circuit voltage parameters identification method

Abstract

Impedance and open circuit voltage (OCV) parameter identification is the key technology for state of health (SOH) diagnosis of lithium ion battery (LIB) in an equivalent circuit model (ECM). The current identification methods of impedance and OCV parameter are time consuming, destructive, non-real-time and costly. It is usually difficult to identify each component from the overall impedance parameter using aforesaid impedance identification methods, which severely affects the identification precision of impedance parameter. Furthermore, fast OCV identification is another difficult issue to be resolved. In this paper, a new real-time and nondestructive method is developed to identify dynamic impedance parameter for SOH diagnosis ECM (SDEM) of LIB. This method can identify ohmic impedance and charge transfer impedance from internal impedance and realize the transformation of Warburg diffusion impedance from frequency domain to time domain. Fast determination method of OCV is proposed based on the short-time and low current pulse to realize real-time measurement and identification of the OCV. Dynamic update of the all parameters is conducted based on least squares method (LSM). SDEM with new developed impedance and OCV parameter identification method is validated with high accuracy.