Accelerated Electrochemical Impedance Spectroscopy of LFP Modules Using Gradient-Based Sensitivity and D-Optimal Selection

Efficient and accurate characterization of lithium-ion battery packs is critical for both first-life applications and second-life reuse. Electrochemical Impedance Spectroscopy (EIS) provides detailed insight into internal electrochemical processes, but full-spectrum measurements are time-consuming, especially at low frequencies. This work presents a methodology combining cell-level equivalent circuit modeling, integrated gradients sensitivity analysis, and D-optimal frequency selection to reduce the number of measurement points while preserving parameter identifiability. Individual 16s5p LFP cells were characterized using full-spectrum EIS at 10 °C, and the resulting equivalent circuit models were scaled to the pack level. Integrated gradients were used to quantify the frequency-dependent influence of each parameter on the real and imaginary parts of the impedance, identifying the regions containing the most information. Using the per-frequency Jacobian and the Fisher Information Matrix, a D-optimal frequency selection was performed to demonstrate that a reduced set of measurements is sufficient to estimate key parameters reliably. The results show that variations in parameters due to aging are accurately captured using the reduced frequency set, validating the approach for fast, accurate, and traceable characterization at the pack level. The proposed methodology highlights a systematic strategy for frequency selection, enabling faster EIS measurements, maintaining sensitivity to aging and degradation mechanisms, and supporting standardized and sustainable evaluation of lithium-ion batteries.