Degradation Analysis of Commercial Lithium-Ion Batteries Using Voltage Curves and Thermal Behaviors

Abstract

Introduction Large scale Lithium-ion batteries are starting to be installed in the world to stabilize the voltage and frequency because variable powers such as photovoltaic and wind powers are installed for the electrical power systems. Life-time estimation is very important for maintenance of batteries and degradation analysis is developed to contribute to this estimation. We have developed the degradation analysis of small size cells by using cell disassembly and reproduction of cells [1, 2]. Misalignment of the operational area of the positive and negative electrodes in the cell due to the lithium irreversible consumption at the anode mainly occurred in the degrade cells. In this study, we investigate the degradation behavior of large size lithium-ion batteries with several ten Ah. Experimental 30Ah class commercial cells were tested in this study. Galvanostatically cycle test were performed in the 10-90% SOC range during charge and discharge at 25, 35 and 45 degC. The other cells were charged up to 50%, 70% and 100% SOC at 25 degC and stored at 25, 35 and 45 degC. The test intervals are 80 and 120 cycle at cycle test and 15 and 20 days at storage one. Capacity test were performed in C/20 rate at 25degC among the cycle and starage test period. Temperature test was conducted using the original thermal insulator. Postmortem analysis were performed at cycled and SOC 50% aged sells at 45degC. These cells were disassembled in an Ar globe box and reassembled to coin cells. Capacity tests were performed in C/20 rate with half-cells and “Nico-ichi” cell with quasi-reference electrode. Results and Discussion The cells were analyzed by the results of the differential voltage versus capacity, dV/dQ vs. Q analysis using “Nico-ichi” coin cell and temperature measurement during charge and discharge using a quasi-adiabatic cell folder. It was observed that dV/dQ peaks and temperature peaks shifted with decreasing cell capacity as shown in Fig.1. The analysis of peak shifts has potentials to the non-destructive prediction of the cell life.