Early prediction of Li-ion cell failure from EIS derived from current–voltage time series
The ability to reliably detect the forthcoming failure of a rechargeable cell without removing it from its normal operating environment remains a significant goal in battery research. In this work we have cycled in the laboratory a previously-aged 3.2 A h, 3.6 V 18650 INR LiNi _x Mn _y Co $ _{1-x-y}...
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IOP Publishing
2025-01-01
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| Series: | JPhys Energy |
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| Online Access: | https://doi.org/10.1088/2515-7655/ad97df |
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| author | M T Wilson V Farrow C J Dunn L Cowie M J Cree J Bjerkan A Stefanovska J B Scott |
| author_facet | M T Wilson V Farrow C J Dunn L Cowie M J Cree J Bjerkan A Stefanovska J B Scott |
| author_sort | M T Wilson |
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| description | The ability to reliably detect the forthcoming failure of a rechargeable cell without removing it from its normal operating environment remains a significant goal in battery research. In this work we have cycled in the laboratory a previously-aged 3.2 A h, 3.6 V 18650 INR LiNi _x Mn _y Co $ _{1-x-y}$ O _2 cell for 300 d until failure was apparent, using a current waveform representative of use in an electric vehicle application. Electrochemical impedance spectroscopy (EIS) down to 5 µ Hz was also performed on the cell as a ‘gold-standard’ measure, at the beginning, end and part way through the cycling. Analysis of voltage and current time series data using both parametric (equivalent circuit model) and non-parametric (wavelet-based analysis) approaches allowed us to successfully reconstruct the EIS data. As the battery aged, impedance gradually increased at frequencies between 10 ^−4 Hz—10 ^−1 Hz. The increase accelerated around 50 d before the battery ultimately failed. The acceleration in rate of change of impedance was detectable while the cycle efficiency remained high, indicating that a user of the cell would be unlikely to detect any change in the cell based on its performance or by common measures of state-of-health. The results imply upcoming failure may be detectable from time series analysis weeks before any noticeable drop in cell performance. |
| format | Article |
| id | doaj-art-5547c7d2fd9b4ea1930274160e11de05 |
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| language | English |
| publishDate | 2025-01-01 |
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| spelling | doaj-art-5547c7d2fd9b4ea1930274160e11de052025-08-20T01:48:15ZengIOP PublishingJPhys Energy2515-76552025-01-017202500110.1088/2515-7655/ad97dfEarly prediction of Li-ion cell failure from EIS derived from current–voltage time seriesM T Wilson0https://orcid.org/0000-0001-6214-7727V Farrow1C J Dunn2L Cowie3M J Cree4J Bjerkan5A Stefanovska6https://orcid.org/0000-0001-6952-8370J B Scott7Te Aka Mãtuatua—School of Science, University of Waikato , Private Bag 3105, Hamilton 3240, New ZealandTe Kura Mata-Ao—School of Engineering, University of Waikato , Private Bag 3105, Hamilton 3240, New ZealandTe Kura Mata-Ao—School of Engineering, University of Waikato , Private Bag 3105, Hamilton 3240, New ZealandTe Kura Mata-Ao—School of Engineering, University of Waikato , Private Bag 3105, Hamilton 3240, New ZealandTe Kura Mata-Ao—School of Engineering, University of Waikato , Private Bag 3105, Hamilton 3240, New ZealandDepartment of Physics, Lancaster University , Lancaster LA1 4YB, United KingdomDepartment of Physics, Lancaster University , Lancaster LA1 4YB, United KingdomTe Kura Mata-Ao—School of Engineering, University of Waikato , Private Bag 3105, Hamilton 3240, New ZealandThe ability to reliably detect the forthcoming failure of a rechargeable cell without removing it from its normal operating environment remains a significant goal in battery research. In this work we have cycled in the laboratory a previously-aged 3.2 A h, 3.6 V 18650 INR LiNi _x Mn _y Co $ _{1-x-y}$ O _2 cell for 300 d until failure was apparent, using a current waveform representative of use in an electric vehicle application. Electrochemical impedance spectroscopy (EIS) down to 5 µ Hz was also performed on the cell as a ‘gold-standard’ measure, at the beginning, end and part way through the cycling. Analysis of voltage and current time series data using both parametric (equivalent circuit model) and non-parametric (wavelet-based analysis) approaches allowed us to successfully reconstruct the EIS data. As the battery aged, impedance gradually increased at frequencies between 10 ^−4 Hz—10 ^−1 Hz. The increase accelerated around 50 d before the battery ultimately failed. The acceleration in rate of change of impedance was detectable while the cycle efficiency remained high, indicating that a user of the cell would be unlikely to detect any change in the cell based on its performance or by common measures of state-of-health. The results imply upcoming failure may be detectable from time series analysis weeks before any noticeable drop in cell performance.https://doi.org/10.1088/2515-7655/ad97dfequivalent circuit modelstate of healthcycle capacityfractional integralconstant phase elementelectrochemical impedance spectroscopy |
| spellingShingle | M T Wilson V Farrow C J Dunn L Cowie M J Cree J Bjerkan A Stefanovska J B Scott Early prediction of Li-ion cell failure from EIS derived from current–voltage time series JPhys Energy equivalent circuit model state of health cycle capacity fractional integral constant phase element electrochemical impedance spectroscopy |
| title | Early prediction of Li-ion cell failure from EIS derived from current–voltage time series |
| title_full | Early prediction of Li-ion cell failure from EIS derived from current–voltage time series |
| title_fullStr | Early prediction of Li-ion cell failure from EIS derived from current–voltage time series |
| title_full_unstemmed | Early prediction of Li-ion cell failure from EIS derived from current–voltage time series |
| title_short | Early prediction of Li-ion cell failure from EIS derived from current–voltage time series |
| title_sort | early prediction of li ion cell failure from eis derived from current voltage time series |
| topic | equivalent circuit model state of health cycle capacity fractional integral constant phase element electrochemical impedance spectroscopy |
| url | https://doi.org/10.1088/2515-7655/ad97df |
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