TY - JOUR
T1 - Comparison of methodologies to estimate state-of-health of commercial Li-ion cells from electrochemical frequency response data
AU - Chan, Hoon Seng
AU - Dickinson, Edmund J.F.
AU - Heins, Tom P.
AU - Park, Juyeon
AU - Gaberšček, Miran
AU - Lee, Yan Ying
AU - Heinrich, Marco
AU - Ruiz, Vanesa
AU - Napolitano, Emilio
AU - Kauranen, Pertti
AU - Fedorovskaya, Ekaterina
AU - Moškon, Jože
AU - Kallio, Tanja
AU - Mousavihashemi, Seyedabolfazl
AU - Krewer, Ulrike
AU - Hinds, Gareth
AU - Seitz, Steffen
N1 - Funding Information:
This project (17IND10-LiBforSecUse) has received funding from the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme. Pierre Kubiak (National Physical Laboratory, Teddington, UK) provided helpful comments on the text.
PY - 2022/9/15
Y1 - 2022/9/15
N2 - 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.
AB - 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.
KW - Distribution of relaxation times
KW - Electrochemical impedance spectroscopy
KW - Equivalent circuit
KW - Nonlinear frequency response analysis
KW - State-of-health prediction
UR - http://www.scopus.com/inward/record.url?scp=85133901374&partnerID=8YFLogxK
U2 - 10.1016/j.jpowsour.2022.231814
DO - 10.1016/j.jpowsour.2022.231814
M3 - Article
SN - 0378-7753
VL - 542
JO - Journal of Power Sources
JF - Journal of Power Sources
M1 - 231814
ER -