A Comparative Study of Diagnostic Methods for Lithium-Ion Batteries

Lithium-ion batteries are increasingly used in stationary energy storage and electric mobility, making reliable degradation assessment essential for improving lifetime, safety, and performance. Since aging is governed by coupled electrochemical processes influenced by temperature, state of charge (SOC), and cycling conditions, this work investigates the diagnostic information that can be extracted directly from experimental data without relying on predefined battery model fitting. A structured testing campaign was conducted on a commercial lithium nickel cobalt aluminum oxide cell at different temperature, SOC, and aging conditions. Charge/discharge voltage curve analysis, incremental capacity analysis (ICA), differential voltage analysis (DVA), electrochemical impedance spectroscopy (EIS) analysis, distribution of relaxation times (DRT) analysis, and voltage relaxation analysis were comparatively evaluated. The results show that charge/discharge voltage curve analysis provides global indicators of degradation, while ICA and DVA highlight aging-related changes in characteristic voltage features. EIS, DRT, and voltage relaxation analyses provide complementary information on resistive, interfacial, transport, and relaxation processes. Overall, the different techniques exhibit consistent aging trends and, when considered jointly, support the qualitative interpretation of degradation modes and aging mechanisms. The combined diagnostic approach provides complementary insights into battery aging directly from experimentally observable features while avoiding the uncertainties associated with predefined battery model fitting.