The increasing adoption of battery electric vehicles, (BEVs) whose backbone is the lithium-ion battery (LIB), requires a deeper understanding of the degradation mechanisms under realistic operating conditions. This study is centered around battery pack hygiene defined as structured operational and diagnostic practices aimed at mitigating degradation and extending battery life. A hybrid diagnostic framework for battery pack hygiene, combining Incremental Capacity Analysis/Differential Voltage Analysis (ICA/DVA) and Electrochemical Impedance Spectroscopy (EIS) is introduced to identify dominant degradation modes, including loss of lithium inventory (LLI), loss of active material (LAM), and loss of conductivity (LC). The proposed framework is evaluated using realistic EV drive cycles and varying charging rates to capture degradation behavior often overlooked in conventional aging studies. Publicly available aging datasets from the Stanford Laboratory is analyzed, where cells were cycled under the Urban Dynamometer Driving Schedule (UDDS) with C/2 and 3C charging rates. Results show that ICA/DVA effectively captures capacity fade and lithium loss, while EIS provides complementary insight into impedance growth associated with active material and conductivity degradation. The findings highlight the strong influence of charging rate on degradation pathways and their impact on capacity and power fade. While qualitative insights are robust, further refinement is required to improve quantitative accuracy. • ICA/DVA and EIS are combined to diagnose lithium-ion battery aging under EV conditions. • UDDS profiles with C/2 and 3C charging reveal charging-rate-dependent degradation pathways. • ICA/DVA tracks capacity fade and anode degradation, including lithium inventory loss. • EIS captures impedance growth and conductivity loss from interfacial and transport limits. • Correlation analysis validates the combined approach for battery health and pack monitoring.
Khan et al. (Thu,) studied this question.