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May 7, 2026BatteriesOpen Access

State of Health Estimation for Lithium-Ion Batteries Based on Alternating Electrical Signals Within a Specific Frequency Range

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Authors

BRBo RaoJDJinqiao DuJTJie Tian

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Overview

Proposed method estimates lithium-ion battery SOH using machine learning with impedance data across various working conditions.

Key Points

  • The aim is to estimate the State of Health (SOH) of lithium-ion batteries using a new impedance-based method.
  • Conducted aging tests on commercial 18650-type batteries.
  • Gathered capacity and impedance data under different discharge conditions.
  • Extracted frequency-specific features from impedance data.
  • Applied Gaussian process regression for SOH estimation.
  • Accurate SOH estimation achieved with a maximum absolute error of 1.59%.
  • Impedance features facilitated online monitoring through embedded battery management systems.

Cite This Study

Rao et al. (2026) studied this question.

synapsesocial.com/papers/69fbf004164b5133a91a44f8https://doi.org/10.3390/batteries12050153
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