Parameter Identification of Lithium-Ion Batteries by Coupling Electrochemical Impedance Spectroscopy with a Physics-Based Model. Issue 4 (1st April 2022)

• Record Type: Journal Article
• Authors: Duan, Xiting; Liu, Fuqiang; Agar, Ertan; Jin, Xinfang
• Is Part Of: Journal of the Electrochemical Society. Volume 169:Issue 4(2022)
• Publication Date: 2022-04-01
• Subjects: Electrochemistry -- Periodicals; 541.3705
• DOI: 10.1149/1945-7111/ac682f
• Languages: English
• ISSNs: 0013-4651

Abstract

Abstract : Nondestructive, quick, and accurate diagnosis of Lithium-ion batteries are critical tools to extend battery lifetime and ensure safe operation under complicated real-time power demand conditions. In this study, an electrochemical characterization approach coupling impedance spectroscopy with a physics-based model (EIS-Physical) has been demonstrated to accurately identify key transport and kinetic parameters for an in-house assembled Li(Ni0.5 Mn0.3 Co0.2 )O2 /Li-metal half-cell. The parameter identification process has been realized by a nonlinear optimization algorithm, along with proper sensitivity and dependence analyses on initial guesses. The parameters obtained using this approach have been compared with those determined from the benchmark Galvanostatic Intermittent Titration Technique (GITT). Equivalent circuit method as an important state-of-the-art modeling approach to interpret EIS has also been compared against the proposed method. The results show that: i) cathode Li-ion diffusivity and cathode/electrolyte exchange current density are quadratic functions of x Li, which indicates cathode is the capacity limiting electrode and operates in a wide SOC range. Therefore, cathode must be simulated using the concentrated solution theory. ii) EIS-Physical method can provide consistent and unique parameters with clear physical meanings compared to its equivalent circuit counterpart. iii) EIS-Physical method is as precise as GITT but less time consuming (i.e., <2.5 h vs > 200 h). Consequently, the proposed method is found to be more practical to implement as a Lithium-ion battery diagnostic tool.