As far as all modern electronics are concerned, lithium-ion batteries play a central role and are currently being increasingly implemented in electric vehicles.
Scientists develop an alternative diagnostic technology to evaluate the degradation mechanism of Li-ion batteries quickly. Image Credit: Gwangju Institute of Science and Technology.
Resultingly, a rapid increase has been found in its usage, and, with it, increasing demand for tools to test the “state of health” (SOH) of these batteries dependably. This is considered to be significant since understanding degradation symptoms in batteries is crucial for enhanced maintenance and accident prevention as a result of malfunctions.
Degradation of Li-ion batteries occurs through three different modes: conductivity loss (CL), loss of active materials (LAM) and loss of lithium inventory (LLI). Over the past few years, numerous methods have been developed by researchers to non-invasively analyze such modes.
The most extensively utilized among them is the incremental capacity-differential voltage (IC-DV) analysis due to its good correlation with the degradation modes. But IC-DV analysis is extremely laborious and cannot infer the complicated mechanisms linked to battery deterioration.
In a recent study headed by Professor Jaeyoung Lee from the Gwangju Institute of Science and Technology (GIST), scientists have currently developed an alternative method to the burdensome IC-DV technique and have characterized the degradation modes through cycling graphite/LiNi0.5Mn0.3Co0.2O2 (NMC532) pouch cells having two different capacities at low and high C-rates (charging and discharging rate of a battery).
While many studies have been conducted to investigate the degradation symptoms of fatigued lithium-ion batteries with charge and discharge cycling data, the technology for rapid diagnosis is still not sufficiently developed.
Jaeyoung Lee, Professor, Gwangju Institute of Science and Technology
We believe that a rapid degradation diagnosis technology using high C-rate could enable real-time detection of the degradation modes and its utilization for monitoring the state of health of individual cells efficiently,” Lee adds detailing the motivation behind this study.
The current study is published in the Journal of Energy Chemistry.
Initially, the researchers gathered low C-rate data every 100 cycles of high C-rate analysis and then transformed the data into IC-DV curves with the help of differential equations to assess the LAM and LLI modes of battery degradation.
The former was evaluated as a sum of the IC peak intensities as a result of its non-linear relation with C-rates, while the latter was estimated by extrapolation given its good linearity with C-rates. In return, this enabled quick detection of LLI degradation.
The views offered in the current research could assist in the quick and elaborate analysis of SOH, which could prove useful in the evaluation of onboard battery systems.
The aim of our study was to help establish a facile diagnostic protocol for lithium-ion battery maintenance. Our proposed mechanism not only makes the process cost-effective but also eco-friendly by providing a faster and reliable selection process for battery reuse.
Jaeyoung Lee, Professor, Gwangju Institute of Science and Technology
Journal Reference:
Seo, G., et al. (2022) Rapid determination of lithium-ion battery degradation: High C-rate LAM and calculated limiting LLI. Journal of Energy Chemistry. doi.org/10.1016/j.jechem.2021.11.009.
Source: https://www.gist.ac.kr/en/main.html