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<p>Electrochemical noise analysis (ENA) was applied to LiCoO₂ based lithium-ion batteries (ICR 18650) to evaluate its potential for in situ battery diagnostics during discharge. Electrochemical noise was investigated through power spectral density (PSD) analysis in the frequency domain and statistical analysis in the time domain under different discharge loads. The results showed excellent reproducibility and revealed characteristic noise signatures across the state-of-charge (SOC) range. A V-shaped evolution of the standard deviation (STD) was observed, with a minimum near 38% of SOC. PSD spectra exhibited a 1/fᵅ behavior at low frequencies (<i>f</i> &lt; 1&#xa0;Hz) and white noise at very low frequencies (<i>f</i> &lt; 0.2&#xa0;Hz), independent of the applied load. Distinct PSD slopes were identified for high and low SOC regions (α = 2) and for the intermediate SOC range (α &lt; 2). Both noise amplitude and standard deviation increased with discharge current, with faster discharges (<i>R</i> = 2 Ω) generating higher noise levels. These findings highlight the potential of ENA as a non-invasive tool for lithium-ion battery diagnostics.</p>

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Spectral analysis of electrochemical noise for battery diagnostics under different loads

  • 期刊论文

  • 发表日期：

    2026年7月29日

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  • Radouane Maizia,
  • Anthony Thomas,
  • Abdelhafid Dib,
  • Serguei Martemianov

摘要

Electrochemical noise analysis (ENA) was applied to LiCoO₂ based lithium-ion batteries (ICR 18650) to evaluate its potential for in situ battery diagnostics during discharge. Electrochemical noise was investigated through power spectral density (PSD) analysis in the frequency domain and statistical analysis in the time domain under different discharge loads. The results showed excellent reproducibility and revealed characteristic noise signatures across the state-of-charge (SOC) range. A V-shaped evolution of the standard deviation (STD) was observed, with a minimum near 38% of SOC. PSD spectra exhibited a 1/fᵅ behavior at low frequencies (f < 1 Hz) and white noise at very low frequencies (f < 0.2 Hz), independent of the applied load. Distinct PSD slopes were identified for high and low SOC regions (α = 2) and for the intermediate SOC range (α < 2). Both noise amplitude and standard deviation increased with discharge current, with faster discharges (R = 2 Ω) generating higher noise levels. These findings highlight the potential of ENA as a non-invasive tool for lithium-ion battery diagnostics.