Simple and Comparable Computation of Incremental Capacity Curves

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Abstract
Incremental capacity (IC) analysis is a widely used non-destructive method to characterize the state of Li-ion batteries. However, there is no standard approach to compute IC curves robustly and reproducibly. Most implementations rely on numerical differentation, which amplifies measurement noise and thus requires extensive noise filtering. The smoothing method and associated parameters are selected by trial-and-error, producing inconsistent ad hoc IC curves hindering reliable comparison across studies. We promote voltage histograms as a simple alternative for computing IC curves and introduce voltage reconstruction as an objective criterion to assess their quality. Histogram-based ICs use the intuitive bin size as the only parameter, are robust to voltage noise, require little or no filtering, handle non-monotonic voltage features, and apply to the low-rate voltage curves of a variety of active materials. Voltage histograms also reconstruct the voltage curve accurately, enabling quantification of individual IC contributions. We discuss the limitations of the method and associated mitigation strategies. Together, histogram-based implementation and voltage reconstruction offer a reproducible framework for computing IC curves comparable across battery materials, samples, and studies.
Funding Information
  • HORIZON EUROPE Climate, Energy and Mobility (101069765)

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