Model-Based Prediction of Composition of an Unknown Blended Lithium-Ion Battery Cathode

A model-based approach to accurately predict the composition of unknown blended Li-ion battery cathodes by fitting to experimental discharge curves is demonstrated. The electrochemically active constituents of the electrode are first determined by coupling information from low-rate galvanostatic lithiation data and SEM/EDX analyses of the electrode. The electrode composition is then estimated using a physics-based mathematical model of the electrode. The accuracy of this method has been assessed by comparison of the estimated composition with the value obtained from an independent, non-electrochemical experimental technique involving the deconvolution of XRD spectra. The electrode compositions obtained in these two ways are found to be in excellent agreement, within 1% of each other, demonstrating the promise of this new model-based approach. The method detailed in this work involves destructive and ex-situ testing, but only a relatively simple model is required to accurately determine the composition of a blended cathode in a Li-ion battery. This approach could also be useful for tracking the evolution of the blended electrode composition over the course of aging and gain a better understanding of the degradation mechanisms at play in cases where the active material loss contributes significantly to the overall capacity/power loss of the battery. (C) 2015 The Electrochemical Society. All rights reserved.