4.6 Article

Identifying Defects in Li-Ion Cells Using Ultrasound Acoustic Measurements

Journal

JOURNAL OF THE ELECTROCHEMICAL SOCIETY
Volume 167, Issue 12, Pages -

Publisher

ELECTROCHEMICAL SOC INC
DOI: 10.1149/1945-7111/abb174

Keywords

Batteries Li-ion; Ultrasound acoustics; State-of-health monitoring; Battery diagnostics; Battery manufacturing

Funding

  1. EPSRC [EP/R020973/1, EP/R023581/1, EP/N032888/1]
  2. Institute for Future Transport and Cities [EP/R023581/1]
  3. Innovate UK [104182]
  4. Royal Academy of Engineering [ICRF1718\1\34, CiET1718]
  5. Faraday Institution [EP/S003053/1, FIRG003, FIRG014]
  6. STFC [ST/K00171X/1]
  7. ACEA
  8. National Measurement System of the UK Department for Business, Energy and Industrial Strategy
  9. EPSRC [EP/S003053/1, EP/R020973/1, EP/R023581/1, EP/N032888/1] Funding Source: UKRI
  10. Innovate UK [104182] Funding Source: UKRI
  11. STFC [ST/K00171X/1] Funding Source: UKRI

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Identification of the state-of-health (SoH) of Li-ion cells is a vital tool to protect operating battery packs against accelerated degradation and failure. This is becoming increasingly important as the energy and power densities demanded by batteries and the economic costs of packs increase. Here, ultrasonic time-of-flight analysis is performed to demonstrate the technique as a tool for the identification of a range of defects and SoH in Li-ion cells. Analysis of large, purpose-built defects across multiple length scales is performed in pouch cells. The technique is then demonstrated to detect a microscale defect in a commercial cell, which is validated by examining the acoustic transmission signal through the cell. The location and scale of the defects are confirmed using X-ray computed tomography, which also provides information pertaining to the layered structure of the cells. The demonstration of this technique as a methodology for obtaining direct, non-destructive, depth-resolved measurements of the condition of electrode layers highlights the potential application of acoustic methods in real-time diagnostics for SoH monitoring and manufacturing processes.

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