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<p>The actual and future concern of sustainability politics is the replacement of fossil fuels with clean and efficient energy. In this way, lithium-ion batteries (LIB) are the chosen technology due to their long lifetime capacity and high energy density. However, the chemicals used to build LIB (cobalt, nickel, aluminum, manganese) require a management system to be operated under control and ideal conditions to avoid failures. Failures such as over-discharging (OD) can shorten the LIB’s Lifetime and even provoke accidents because they reduce the energy density and increase the internal resistance of the LiB. In this way, it is mandatory to understand the impacts of OD in LIB to anticipate and avoid this type of fault. Then, this work presents a curve of LIB degradation under different OD levels. Therefore, 360 cycles have been carried out with four LIBs under OD at the following lower voltage thresholds: ninety cycles discharged until #3.0V (regular operation), ninety cycles discharged until #2.0V, ninety cycles discharged until #1.0V, and ninety cycles discharged until #0.1V. The results indicated the critical loss capacity under different levels of energy discharge. A Linear degradation rate was observed for OD at 0.1V, 1.0V, and 2.0V. On the other side, low loss capacity was observed for regular operation of the cell during ninety cycles under discharging until 3V. Finally, Ordinary least squares (OLS) and Polynomial Regression Techniques were used to analyze the results and predict the rate of degradation of the four experiments. OLS could represent the degradation rate well, with <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\text {R}^{2}\)</EquationSource> <EquationSource Format="MATHML"><math> <msup> <mtext>R</mtext> <mn>2</mn> </msup> </math></EquationSource> </InlineEquation> above 98% for OD under #0.1V and #1.0V. However, OLS has difficulty predicting the degradation for a regular operation (#3.0V) because the standard loss capacity for regular operation is not Linear. Polynomial models fit the data of the 360 cycles, but they had poor performance for the new data prediction. The study demonstrated the rate degradation of the LIB under OD and OLS, and Polynomial Regression models could explain the rate degradation of the cells.</p>

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Regression analysis of over-discharge effects on cell capacity degradation across cycles

  • 期刊论文

  • 发表日期：

    2025年10月3日

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  • Joelton Deonei Gotz,
  • Samuel Henrique Werlich,
  • José Rodolfo Galvão,
  • Fernanda Cristina Corrêa,
  • Emilson Ribeiro Viana,
  • Milton Borsato,
  • Alceu André Badin

摘要

The actual and future concern of sustainability politics is the replacement of fossil fuels with clean and efficient energy. In this way, lithium-ion batteries (LIB) are the chosen technology due to their long lifetime capacity and high energy density. However, the chemicals used to build LIB (cobalt, nickel, aluminum, manganese) require a management system to be operated under control and ideal conditions to avoid failures. Failures such as over-discharging (OD) can shorten the LIB’s Lifetime and even provoke accidents because they reduce the energy density and increase the internal resistance of the LiB. In this way, it is mandatory to understand the impacts of OD in LIB to anticipate and avoid this type of fault. Then, this work presents a curve of LIB degradation under different OD levels. Therefore, 360 cycles have been carried out with four LIBs under OD at the following lower voltage thresholds: ninety cycles discharged until #3.0V (regular operation), ninety cycles discharged until #2.0V, ninety cycles discharged until #1.0V, and ninety cycles discharged until #0.1V. The results indicated the critical loss capacity under different levels of energy discharge. A Linear degradation rate was observed for OD at 0.1V, 1.0V, and 2.0V. On the other side, low loss capacity was observed for regular operation of the cell during ninety cycles under discharging until 3V. Finally, Ordinary least squares (OLS) and Polynomial Regression Techniques were used to analyze the results and predict the rate of degradation of the four experiments. OLS could represent the degradation rate well, with \(\text {R}^{2}\) R 2 above 98% for OD under #0.1V and #1.0V. However, OLS has difficulty predicting the degradation for a regular operation (#3.0V) because the standard loss capacity for regular operation is not Linear. Polynomial models fit the data of the 360 cycles, but they had poor performance for the new data prediction. The study demonstrated the rate degradation of the LIB under OD and OLS, and Polynomial Regression models could explain the rate degradation of the cells.