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Three-electrode Coin Cell Preparation and Electrodeposition Analytics for Lithium-ion Batteries
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Published on: May 22, 2018

Generalized EIS Measurement Method in Li-Ion Batteries.

Juan María Nogales1, Israel Corbacho1, Francisco Romero-Galán1

  • 1Department of Electrical, Electronic and Automation Engineering, University of Extremadura, 06006 Badajoz, Spain.

Sensors (Basel, Switzerland)
|June 12, 2026
PubMed
Summary
This summary is machine-generated.

A new compact sensor system uses electrical impedance spectroscopy (EIS) to characterize lithium-ion batteries. The system corrects for hardware errors, enabling accurate battery impedance measurement and analysis of state-of-charge and discharge current effects.

Keywords:
Li-ion battery cellsdischarge currentelectrical impedance spectroscopyembedded sensor systemmagnitude-ratio and phase-difference detectionparasitic correctionprinted circuit board (PCB)shunt impedancestate of charge (SoC)

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Area of Science:

  • Electrical Engineering
  • Materials Science
  • Electrochemistry

Background:

  • Accurate characterization of lithium-ion batteries is crucial for performance and safety.
  • Electrical Impedance Spectroscopy (EIS) is a powerful technique for battery analysis.
  • Existing EIS systems can be complex and susceptible to hardware-induced errors.

Purpose of the Study:

  • To develop a compact, embedded impedance-based sensor system for lithium-ion battery characterization.
  • To implement and extend the analog magnitude-ratio and phase-difference detection (MRPDD) method.
  • To correct for parasitic contributions from measurement hardware and printed circuit boards.

Main Methods:

  • Utilized a generalized formulation of the MRPDD method, modeling shunt elements as frequency-dependent impedances.
  • Developed a prototype with current-mode excitation (operational transconductance amplifier, power MOSFET, direct digital synthesizer) and voltage-mode measurement (instrumentation amplifiers, AD8302 vector detector).
  • Validated the system through simulations and experimental characterization using RC and Randles-type battery-equivalent models.

Main Results:

  • The generalized formulation successfully corrected magnitude and phase errors caused by parasitic effects.
  • Experimental validation with an RC model yielded a low magnitude error of 1.65% at 1 kHz.
  • The system was applied to characterize a commercial lithium-ion 18650 cell, showing dependence on state-of-charge and discharge current.

Conclusions:

  • The developed compact sensor system effectively characterizes lithium-ion batteries using EIS.
  • The generalized MRPDD formulation enhances accuracy by compensating for hardware parasitics.
  • The system provides valuable insights into battery impedance, state-of-charge, and discharge current effects.