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Cross-Scale Decoupling Kinetic Processes in Lithium-Ion Batteries Using the Multi-Dimensional Distribution of

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|October 8, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a new framework to accurately diagnose lithium-ion battery degradation. The method enhances the distribution of relaxation times (DRT) analysis for reliable battery health monitoring.

Keywords:
cross‐scale identificationdistribution of relaxation timekinetic processes decouplinglithium‐ion batteriesreconstructed interfacial impedance

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Area of Science:

  • Electrochemistry
  • Materials Science
  • Battery Technology

Background:

  • Non-destructive diagnosis of lithium-ion battery (LIB) degradation is crucial for reliable operation.
  • Distribution of Relaxation Times (DRT) is a powerful tool for analyzing kinetic processes but is hindered by low interfacial impedance in LIBs.
  • Existing DRT methods lack sufficient resolution and validation for complex LIB systems.

Purpose of the Study:

  • To develop a hierarchical analytical framework for enhanced timescale resolution and reduced uncertainty in DRT analysis of LIBs.
  • To enable reliable, non-destructive diagnosis of degradation mechanisms in LIBs.
  • To improve the accuracy of kinetic process deconvolution in LIBs.

Main Methods:

  • Interfacial impedance reconstruction using a high-fidelity frequency-domain model to remove inductive and diffusive components.
  • Multi-dimensional DRT analysis incorporating state of charge (SOC) reversibility to decouple solid electrolyte interphase (SEI) and charge transfer (CT) processes.
  • Characterization of electrode kinetic evolution based on SOC and temperature variations.

Main Results:

  • Reconstructed impedance improved the accuracy of identified time constants by approximately 20%.
  • Cross-scale DRT effectively distinguished electrode kinetics at low SOC (below 10%) and 25 °C due to strong cathodic CT-SOC correlation.
  • Kinetic metrics identified anodic SEI or CT as distinct rate-limiting steps for low-temperature performance in different cells.

Conclusions:

  • The proposed hierarchical framework significantly enhances the reliability and accuracy of DRT for LIB diagnostics.
  • The method allows for precise deconvolution of SEI and CT processes, providing insights into degradation mechanisms.
  • This work demonstrates a promising approach for non-destructive monitoring of LIB kinetic evolution and health.