Development of a Correction Algorithm for Structural Elements to Enhance EIS Measurement Reliability in Battery Modules

With the increasing demand for electric vehicles (EVs) and energy storage systems, electrochemical impedance spectroscopy (EIS) has emerged as a promising method for battery pack diagnostics. However, existing EIS research has been predominantly limited to single cells, presenting challenges for practical implementation in actual battery pack systems. In real battery packs, structural elements such as bus plates introduce additional impedance artifacts into measurement data. This parasitic impedance becomes more pronounced as the number of parallel-connected cells increases, degrading measurement reliability. This study presents a systematic analysis of bus plate effects on EIS measurements of parallel battery modules and develops a correction algorithm to extract pure module impedance. Standalone bus plate EIS measurements were conducted to establish geometry-based impedance prediction formulas, and correction factors accounting for current distribution and frequency dependence were derived. The algorithm was validated on 2P-4P parallel modules of NCA and LFP batteries, achieving RMSE reduction from 1.18–2.65 mΩ to 0.10–0.17 mΩ, corresponding to an 88–96% error reduction. These results demonstrate that the proposed algorithm effectively improves module-level EIS measurement reliability regardless of battery chemistry and parallel configuration.