Degradation Mode Quantification and Analysis of Lithium-ion Battery Cell Over Dynamic Load Profile and Different State of Charge Conditions

Identification and quantification of degradation modes in lithium-ion batteries are critically important to protect the batteries from thermal runaway. Battery packs, composed of individual cells, are complex systems that must be operated within specified limits to ensure safe and reliable performance. As the battery ages, the cells begin to degrade; however, this degradation can be managed by carefully monitoring the aging behavior. Degradation is divided into three interdependent modes, all of which must be identified to avoid sudden breakdowns. Accurate degradation estimation requires diagnostic tests to estimate the State of Health (SOH) of the battery. There are several articles that address cyclic aging under constant current (CC) discharging cycling; however, very few have addressed aging under dynamic loading conditions. In this paper, we used an open-source dataset provided by Stanford’s Energy Control Lab that consists of the cyclic aging of cells under 225 cycles of the Urban Dynamometer Drive Schedule (UDDS). Electrochemical Impedance Spectroscopy (EIS) and capacity tests were used to diagnose battery degradation. Our analysis estimated $\mathbf{5. 9 1 \%}$ conduction losses, whereas $\mathbf{2 8. 1 6 \%}$ and $\mathbf{3 2. 1 \%}$ lithium inventory and active material losses, respectively.