Comparison of methodologies to estimate state-of-health of commercial Li-ion cells from electrochemical frequency response data

Hoon Seng Chan, Edmund J.F. Dickinson, Tom P. Heins, Juyeon Park, Miran Gaberšček, Yan Ying Lee, Marco Heinrich, Vanesa Ruiz, Emilio Napolitano, Pertti Kauranen, Ekaterina Fedorovskaya, Jože Moškon, Tanja Kallio, Seyedabolfazl Mousavihashemi, Ulrike Krewer, Gareth Hinds, Steffen Seitz

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Various impedance-based and nonlinear frequency response-based methods for determining the state-of-health (SOH) of commercial lithium-ion cells are evaluated. Frequency response-based measurements provide a spectral representation of dynamics of underlying physicochemical processes in the cell, giving evidence about its internal physical state. The investigated methods can be carried out more rapidly than controlled full discharge and thus constitute prospectively more efficient measurement procedures to determine the SOH of aged lithium-ion cells. We systematically investigate direct use of electrochemical impedance spectroscopy (EIS) data, equivalent circuit fits to EIS, distribution of relaxation times analysis on EIS, and nonlinear frequency response analysis. SOH prediction models are developed by correlating key parameters of each method with conventional capacity measurement (i.e., current integration). The practical feasibility, reliability and uncertainty of each of the established SOH models are considered: all models show average RMS error in the range 0.75%–1.5% SOH units, attributable principally to cell-to-cell variation. Methods based on processed data (equivalent circuit, distribution of relaxation times) are more experimentally and numerically demanding but show lower average uncertainties and may offer more flexibility for future application.

Original languageEnglish
Article number231814
JournalJournal of Power Sources
Volume542
DOIs
Publication statusPublished - 15 Sep 2022
MoE publication typeA1 Journal article-refereed

Keywords

  • Distribution of relaxation times
  • Electrochemical impedance spectroscopy
  • Equivalent circuit
  • Nonlinear frequency response analysis
  • State-of-health prediction

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