Physics-Based State of Health Prediction of Lithium-Ion Battery during Fast Charging

Abstract

Electrification of the transportation sector and increased use in consumer electronics have driven the increasing demand for lithium-ion batteries (LiBs) (1). Despite their high energy density and long service life, LiBs suffer from capacity degradation due to continuous growth of solid electrolyte interface (SEI) layer and plating of lithium on the anode surface. Graphite, the anode in most LiBs, has a high tendency to catalyze the degradation of the electrolyte consisting of LiPF6 and ethylene carbonate to form an SEI of Li-rich carbonate, phosphate, and fluoride compounds (2, 3). The SEI film grows during service due to the deposition of reaction products and repeated cycles of damage and reformation due to the contraction and expansion associated with volume changes during Li-ion intercalation and deintercalation. Additionally, fast or low-temperature charging of batteries results in lithium plating on the anode surface because the elevated concentration of Li+ on the anode surface results in graphite potential falling below 0V vs. Li+/Li and increased likelihood of Li deposition compared to intercalation (4). Lithium loss due to the side reactions of SEI growth and plating contributes to capacity loss and may increase the likelihood of battery failure. Hence, accurate modeling of the side reactions is required to determine the state of health (SOH) and predict the remaining capacity of LiBs during operation (5).We report an experimentally validated single particle model (SPM) to estimate the influence of SEI growth and Li plating on the capacity changes in Lithium Cobalt Oxide (LCO)/Carbon cells during repeated cycling (6-8). The SPM model idealizes each electrode as a single particle to approximate the cell response. A. Sarkar et al. (5) included the influence of SEI growth, plating, SEI fracture, and temperature in the SPM model to determine the influence of the side reactions on battery performance. The parameters corresponding to side reactions, such as the SEI film growth rate, conductivity of the SEI film, and reversibility of the plating reaction, were determined through comparison of numerical predictions of cell voltage and capacity change with experimental response measured at charging rates of 0.1C and fast charging rate of 2C on PowerStream 35 mAh LCO/C coin cells (Lir2032) as shown in Figure 1. In addition, the coin cells were subjected to charge/discharge experiments at charging rates varying from 0.1C – 5C for 100 cycles. Experimental measurements of the cell capacity changes were compared to model predictions for the different charging rates to validate the modeling assumptions and determine the efficacy of the estimated parameters in describing the cell degradation. The agreement between the model prediction and measured experimental response showed that the single particle model augmented with side reaction mechanisms can describe the cell degradation and is suitable for predicting the remaining capacity and safety of LiBs subjected to a range of charging rates. The model can also predict the accumulation of irreversibly plated lithium on the anode surface during repeated fast charging. The amount of plated lithium determines the severity of dendritic growth, and thus, model predictions of lithium accumulation may be used to estimate the likelihood of battery failure under fast charging conditions. Acknowledgment:This work was supported by the National Science Foundation, Iowa State University, and University of Connecticut.