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3ε-A Versatile Operando Analytics Toolbox in Energy Storage.

Sobana P Rangarajan1, Susmita Sarkar1, Yevgen Barsukov2

  • 1School of Mechanical Engineering, Purdue University, West Lafayette, Indiana 47907, United States.

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|December 20, 2021
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Summary
This summary is machine-generated.

Three-electrode (3ε) analytics enable precise diagnostics of lithium-ion battery degradation. This technique helps understand electrode aging mechanisms for improved battery management systems and future designs.

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Area of Science:

  • Electrochemistry
  • Materials Science
  • Battery Technology

Background:

  • Lithium-ion battery performance and safety are compromised by complex, nonlinear aging mechanisms.
  • Electrochemical-thermal interactions, usage history, and operating conditions significantly influence battery degradation.
  • Accurate diagnostics and prognostics require understanding fundamental electrode degradation mechanisms.

Purpose of the Study:

  • To present three-electrode (3ε) analytics as a versatile toolbox for investigating lithium-ion battery degradation.
  • To highlight recent techniques and parameters for diagnosing and controlling electrode degradation modes.
  • To emphasize the role of 3ε analytics in advancing battery management systems.

Main Methods:

  • Utilizing cells with a stable, nonpolarizable reference electrode for in situ and operando measurements.
  • Decoupling electrochemical interplay between electrodes by measuring individual electrode responses simultaneously with cell response.
  • Analyzing responses in both time and frequency domains for comprehensive characterization.

Main Results:

  • 3ε analytics provide high-precision operando techniques to investigate distinct electrode degradation modes.
  • The method allows for characterization across a wide range of operational variability.
  • Simultaneous measurement of individual electrode and cell responses aids in understanding complex interactions.

Conclusions:

  • Three-electrode (3ε) analytics are crucial for deconvoluting lithium-ion battery aging mechanisms.
  • This approach facilitates the development of effective degradation diagnostics and control strategies.
  • 3ε analytics are expected to drive the future design of advanced battery management systems.