Quantitative Estimation of Capacity Fade of Sony 18650 cells Cycled at Elevated Temperatures

1. Quantitative Estimation of Capacity Fade of Sony 18650 cells Cycled at Elevated Temperatures by Branko N. Popov, P.Ramadass and Bala S. Haran Center for Electrochemical Engineering Department of Chemical Engineering University of South Carolina Columbia, SC 29208

2. Objectives • Develop a methodology to determine the cause of capacity fade in Li-ion cells: • Primary Active Material (Li+) loss • Secondary Active Material (LiCoO2/Carbon) losses • Rate Capability loss • Factors that control the capacity loss: • Charging protocol • Cycling Temperature • Charge and discharge rates • The depth of discharge (DOD) • Quantify capacity fade using experimental data. • Develop a capacity fade model that would predict cycle life of a Li-ion cell

3. Experimental – Cycling Studies Studies of 18650 Li-ion Cell: • Cells cycled using Constant Current-Constant Potential (CC-CV) protocol. • Charged at 1A current till potential reaches 4.2 V • Hold potential at 4.2V till current decays to 50 mA. • Cells were discharged at a constant current of 1 A. • Batteries were cycled at four temperatures: RT(25oC), 45oC, 50oC and 55oC. • Rate capability studies done after 150, 300 and 800 cycles • Cells charged at 1 A and discharged at different rates (C/9 to 1C). • EIS measurements were done for fresh and cycled cells. (100 kHz ~ 1 mHz ±5 mV) Studies of fresh and cycled electrode materials were carried out using a T-Cell assembly with Li metal being the counter and reference electrode.

4. Discharge Curves at Various Cycles 25 deg C 45 deg C 50 deg C 55 deg C

5. Capacity Fade as a Function of Cycle Life

6. Change in Charging Times with Cycling Constant Current Constant Voltage

7. Rate Capability with Cycling 45 deg C 25 deg C 50 deg C 55 deg C

8. Variation of Cell Impedance with Cycling

9. Comparison of Electrode Resistances 150 Cycles 300 Cycles 800 Cycles

10. Specific Capacity of Positive and Negative Electrodes at Various Cycles and Temperature

11. Capacity Fade Balance Q = Q1 + Q2 + Q3 Q: Total Capacity Loss • Q1: Capacity Fade due to rate capability loss • Difference in capacity between C/9 and C/2 rate discharges. • Q2: Capacity Fade due to loss of secondary active material (LiCoO2 and Carbon) • Measurement done on T-cells • Q3: Capacity Fade due to loss of primary active material (Li+) and other losses.

12. Capacity Fade - Quantified 25oC 50oC

13. Simplified Diffusion Model • Concentration variations in the solution phase can be neglected for low to medium discharge currents. • Solid phase potential drop is negligible as compared to kinetic and concentration over-potentials. • Eliminating the above two results in a simple diffusion model which can be used to simulate the performance of the Li-ion Battery. • Model considers Li+ reaction at carbon/LiCoO2 particle interface and subsequent transport in these materials.

14. Governing Equations: Diffusion Model Fickian diffusion in spherical coordinates in carbon and LiCoO2 Initial Condition Boundary Conditions

15. Electrode Reaction Rates Lithium intercalation/deintercalation reaction: Rf refer to total resistance that includes ohmic R and polarization RP resistances. (Rf=R+RP) Concentration dependent exchange current density:

16. Uref A Function of SOC LiCoO2 Urefn Urefp SOCn Carbon SOCp

17. Parameters Considered for Diffusion Model • State of Charge of the electrode limited by capacity • To account for capacity loss due to primary and secondary active materials. • Solid Phase Diffusion Coefficient • To account for capacity loss due to rate capability. • Film Resistance • To account for the drop in cell voltage due to increase in ohmic resistance and polarization losses.

18. Incorporation of Q2 and Q3 in Diffusion Model • SOC of the electrode material could be estimated from active material losses. • Calculate SOC of the negative electrode based on the capacity loss (Q2 + Q3). • Develop a correlation for variation of SOC of negative electrode with cycle number. • Using this capacity fade due to active material losses could be incorporated in the diffusion model.

19. Comparison of Diffusion Model and RT Experimental Data

20. Comparison of Diffusion Model and RT Experimental Data for Utilization (Rate Capability)

21. Conclusions • A diffusion model was developed to simulate the discharge curves of Li-ion cell. • Empirical correlations have been developed for variation of SOC of Li-ion cell with continuous cycling. • Active material losses have been accounted through the variation of negative electrode SOC in the diffusion model. • Rate capability losses and Polarization resistance increase have been accounted through varying the diffusion coefficient and exchange current density respectively. • Inclusion of effect of charging and discharge rates and DOD into diffusion model is currently in progress.

22. Acknowledgements This work was carried out under a contract with the National Reconnaissance Office for Hybrid Advanced Power Sources # NRO-00-C-1034.