An Enhanced Battery Aging Model Based on a Detailed Diffusing Mechanism in the SEI Layer. (9th September 2022)

• Record Type: Journal Article
• Authors: Lanjan, Amirmasoud; Srinivasan, Seshasai
• Is Part Of: ECS advances. Volume 1:Number 3(2022)
• Publication Date: 2022-09-09
• Subjects: aging -- SEI -- diffusion mechanism -- capacity fading -- mathematical modeling -- relative capacity -- LIB; Electrochemistry -- Periodicals; 541.3705
• DOI: 10.1149/2754-2734/ac8e84
• Languages: English
• ISSNs: 2754-2734

Abstract

Abstract : The impetus for this study is the lack of a detailed knowledge on the formation mechanism of the solid electrolyte interface (SEI) layer and the diffusion mechanisms within this layer that impacts the predictive abilities of the current mathematical models. Specifically, most models continue to employ a constant value of diffusion coefficient along with several lumped fitting parameters, instead of a variable formulation that is dependent on the temperature and concentration of Li-ions, to characterize Li-ion batteries (LIBs). As a result, the current models fail in predicting the capacity fading accurately. In overcoming this gap, we have employed a previously proposed temperature and concentration-dependent diffusion equation to present a modified mathematical model that is capable of accurately predicting the capacity fading and SEI growth rate as a function of temperature, concentration, and time, with just two significantly simplified temperature dependent fitting parameters. Further, these parameters need to be adjusted only for new temperatures. Our enhanced model is validated with respect to the experimental data for different operational conditions, including open circuit condition with different initial state of charges (SOCs) as well as cycling with a constant current.