Electrochemical Impedance Analysis of LiCoO2/Graphite Lithium Ion Batteries By Distribution of Relaxation Times Method

Electrochemical impedance spectroscopy (EIS) is one of the most important non-destructive diagnosis tools in lithium-ion battery (LIB) technology. EIS is routinely used for characterization of battery materials, optimization of manufacturing processes, and understanding of degradation mode. However, interpretation of EIS spectra is not a straightforward procedure. Typical EIS data of LIB have heavily overwrapped capacitive semicircles in Nyquist (complex impedance) plot because LIBs’ anodes and cathodes both involve several conduction processes. Widely used method for information separation is least-squares fitting based on discrete equivalent circuit model. However, this method requires a priori assumption on the number of capacitive processes. Destructive EIS measurement methods, such as insertion of reference electrode and symmetry cell construction, are powerful for separation of cathode/anode information. But these involve meticulous work, and battery structure or degradation state often make it difficult to obtain an accurate measurement result. Recently, distribution of relaxation times (DRT) analysis has increasingly used for EIS interpretation. This analysis treats an EIS spectrum as a continuous function of relaxation time, or time constant of infinitesimal RC equivalent circuit element. DRT analysis can distinguish several different capacitive processes without the need of prior model assumption. Application field of DRT analysis currently focuses on solid oxide fuel cell, but several LIB studies have been reported for LiFePO4 cathode system[1] and LiMn2O4-LiNixCoyMnzO2 cathode system[2]. Here we demonstrate that DRT analysis is a powerful tool for degradation analysis of LIBs with LiCoO2(LCO)-based cathode and graphite anode, and provide experimental verification of information obtained by DRT analysis. Commercial-size prototype LIBs with LCO-based cathode and graphite anode are used for this work. Charge-discharge cycling tests of the cells are performed at different temperature conditions. EIS measurements are conducted at fully charged state of every fifty cycles, with frequency range of 1 MHz to 10 mHz. For better separation of different processes, the EIS spectra are obtained at 23 deg C, 10 deg C and 0 deg C in a climate chamber. DRT is calculated by MATLAB with in-house code, which is based on Fourier transfer methods utilizing window function preprocessing[3]. To understand DRT results in physical viewpoints, several electrode analyses of disassembled cells are conducted at initial and the cycled state. Figure 1 shows Nyquist plots and the corresponding DRT plots of (a) low-temperature and (b) high-temperature cycled LIBs obtained at 10 deg C. In Nyquist plot, all spectra exhibit the shape of two depressed capacitive semicircles. At a first glance, both low-temperature cycling and high-temperature cycling appear to increase the size of low-frequency semicircles. But closer look shows that low-temperature cycling cause “merge” or heavier overwrap of two semicircles, whereas high-temperature cycling retains the separated feature. These characteristics are further clarified by DRT analysis. In each cell, we can identify four different peaks in DRT plots. The high-temperature cycled cell shows gradual increase in the lowest-frequency (1) peak, whereas the peak remains almost the same intensity in the low-temperature cycled cell and the middle-frequency (2) peak increases significantly. No change is observed for the (3) peak during the cycle test. Both cycling condition cause the increase in the highest-frequency (4) peak. Further teardown analyses verify that these DRT peaks can be attributed to different electrode degradation phenomena, which are related to cycling temperature. These results demonstrate the ability of DRT analysis as a degradation diagnostics tool for LIBs with various kinds of material systems. [1] J. P. Schmidt, T. Chrobak, M. Ender, J. Illig, D. Klotz, E. Ivers-Tiffée, J. Power Sources, 196 5342 (2011). [2] B. Stiaszny, J. Ziegler, E. Krauß, J. P. Schmidt, E. Ivers-Tiffée, J. Power Sources, 251 439 (2014). [3] H. Schichlein, A. C. Müller, M. Voigts, A. Krügel, E. Ivers-Tiffée, J. Appl. Electrochem., 32 875 (2002). Figure 1