Diagnosis of lithium-ion batteries degradation with P2D model parameters identification: A case study on low temperature charging

The estimation of the state of health (SoH) of a lithium-ion battery is still a hot topic in the scientific research. This publication deals with the combined use of optimized tests, also involving impedance spectroscopy, and physical models to investigate lithium-ion batteries degradation. As a case study, this method is firstly applied on a low-temperature charging degradation campaign, in order to expectedly generate a lithium plating-dominated ageing state. Degradation tests, performed under previously selected combinations of operating conditions, are performed down to 75 % SoH on commercial samples, determining severe ageing rate up to 1.5 % capacity loss per equivalent full cycle. The proposed interpretation methodology identifies the ageing to be dominated by the loss of lithium inventory, consistently with the expected degradation mechanism. Large electrolyte consumption is also detected, which induces a strongly anisotropic utilization of the electrodes during discharge, as confirmed by pseudo-two-dimensional (P2D) model simulations. This activity contributes to verify the reliability of the methodology, elucidate the effect of lithium plating on the performance and underline the effect of the operating conditions at low temperature, paving the way to the application on real-world conditions. • The plateau during relaxation is correlated with the onset of lithium plating. • Low temperature, high C-rate and SoC enhance capacity loss rate. • Plating is associated with lithium loss and ionic conductivity decrease. • The P2D model reproduces the heterogeneity induced by low ionic conductivity.

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Publication Details

Journal
Future Batteries
Published
2024-10-05
DOI
https://doi.org/10.1016/j.fub.2024.100006
Citations
8
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
1.63
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article

Diagnosis of lithium-ion batteries degradation with P2D model parameters identification: A case study on low temperature charging

Gabriele Sordi, Andrea Casalegno, Claudio Rabissi, M. Sedzik
8 citations
Future Batteries
Advanced Battery Technologies Research
1.63
article

Diagnosis of lithium-ion batteries degradation with P2D model parameters identification: A case study on low temperature charging

Gabriele Sordi, Andrea Casalegno, Claudio Rabissi, M. Sedzik
article en
8 citations

Abstract

The estimation of the state of health (SoH) of a lithium-ion battery is still a hot topic in the scientific research. This publication deals with the combined use of optimized tests, also involving impedance spectroscopy, and physical models to investigate lithium-ion batteries degradation. As a case study, this method is firstly applied on a low-temperature charging degradation campaign, in order to expectedly generate a lithium plating-dominated ageing state. Degradation tests, performed under previously selected combinations of operating conditions, are performed down to 75 % SoH on commercial samples, determining severe ageing rate up to 1.5 % capacity loss per equivalent full cycle. The proposed interpretation methodology identifies the ageing to be dominated by the loss of lithium inventory, consistently with the expected degradation mechanism. Large electrolyte consumption is also detected, which induces a strongly anisotropic utilization of the electrodes during discharge, as confirmed by pseudo-two-dimensional (P2D) model simulations. This activity contributes to verify the reliability of the methodology, elucidate the effect of lithium plating on the performance and underline the effect of the operating conditions at low temperature, paving the way to the application on real-world conditions. • The plateau during relaxation is correlated with the onset of lithium plating. • Low temperature, high C-rate and SoC enhance capacity loss rate. • Plating is associated with lithium loss and ionic conductivity decrease. • The P2D model reproduces the heterogeneity induced by low ionic conductivity.

Future BatteriesVol. 4
Politecnico di Milano (IT)
Openalex Percentile: Top 17%
Advanced Battery Technologies Research
1.63
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