Determination of the Differential Capacity of Lithium-Ion Batteries by the Deconvolution of Electrochemical Impedance Spectra

Electrochemical impedance spectroscopy (EIS) is a powerful tool for investigating electrochemical systems, such as lithium-ion batteries or fuel cells, given its high frequency resolution. The distribution of relaxation times (DRT) method offers a model-free approach for a deeper understanding of EIS data. However, in lithium-ion batteries, the differential capacity caused by diffusion processes is non-negligible and cannot be decomposed by the DRT method, which limits the applicability of the DRT method to lithium-ion batteries. In this study, a joint estimation method with Tikhonov regularization is proposed to estimate the differential capacity and the DRT simultaneously. Moreover, the equivalence of the differential capacity and the incremental capacity is proven. Different types of commercial lithium-ion batteries are tested to validate the joint estimation method and to verify the equivalence. The differential capacity is shown to be a promising approach to the evaluation of the state-of-health (SOH) of lithium-ion batteries based on its equivalence with the incremental capacity.

[1]  Steffen Limmer,et al.  Evaluation of Optimization-Based EV Charging Scheduling with Load Limit in a Realistic Scenario , 2019, Energies.

[2]  Amad Zafar,et al.  Online Remaining Useful Life Prediction for Lithium-Ion Batteries Using Partial Discharge Data Features , 2019, Energies.

[3]  Shang Gao,et al.  A comparative investigation of aging effects on thermal runaway behavior of lithium-ion batteries , 2019, eTransportation.

[4]  Rui Xiong,et al.  A review on state of health estimation for lithium ion batteries in photovoltaic systems , 2019, eTransportation.

[5]  Lei Zhang,et al.  A fast measurement of Warburg-like impedance spectra with Morlet wavelet transform for electrochemical energy devices , 2019, Electrochimica Acta.

[6]  L. Helseth Modelling supercapacitors using a dynamic equivalent circuit with a distribution of relaxation times , 2019, Journal of Energy Storage.

[7]  Thomas Bäck,et al.  Modeling and Prediction of Remaining Useful Lifetime for Maintenance Scheduling Optimization of a Car Fleet , 2019, International Journal of Performability Engineering.

[8]  Xuning Feng,et al.  Lithium-ion battery fast charging: A review , 2019, eTransportation.

[9]  G. Plett,et al.  Comparing four model-order reduction techniques, applied to lithium-ion battery-cell internal electrochemical transfer functions , 2019, eTransportation.

[10]  Zhe Li,et al.  A review on the key issues of the lithium ion battery degradation among the whole life cycle , 2019, eTransportation.

[11]  Hongwen He,et al.  Aging characteristics-based health diagnosis and remaining useful life prognostics for lithium-ion batteries , 2019, eTransportation.

[12]  Zhengqiang Pan,et al.  Impedance characterization of lithium-ion batteries aging under high-temperature cycling: Importance of electrolyte-phase diffusion , 2019, Journal of Power Sources.

[13]  Dirk Uwe Sauer,et al.  Separation of predominant processes in electrochemical impedance spectra of lithium-ion batteries with nickel-manganese-cobalt cathodes , 2019, Journal of Power Sources.

[14]  Prasad Enjeti,et al.  Advanced Electric Vehicle Fast-Charging Technologies , 2019, Energies.

[15]  Marc A. Rosen,et al.  Electric Vehicle Battery Lifetime Extension through an Intelligent Double-Layer Control Scheme , 2019, Energies.

[16]  Kt Malkow A theory of distribution functions of relaxation times for the deconvolution of immittance data , 2019, Journal of Electroanalytical Chemistry.

[17]  Zhengqiang Pan,et al.  An easy-to-implement multi-point impedance technique for monitoring aging of lithium ion batteries , 2019, Journal of Power Sources.

[18]  Kelvin Yi-Wen Hong,et al.  Experimental Assessment and Stability Analysis of a Discrete-Time Battery Model with Multiple Constant Phase Elements , 2019, 2019 IEEE Applied Power Electronics Conference and Exposition (APEC).

[19]  Weige Zhang,et al.  Modeling Study for Li-ion Batteries Considering High-frequency Inductance Characteristics Based on Electrochemical Impedance Spectroscopy , 2019, DEStech Transactions on Environment, Energy and Earth Sciences.

[20]  Haifeng Dai,et al.  Estimation of state of health of lithium-ion batteries based on charge transfer resistance considering different temperature and state of charge , 2019, Journal of Energy Storage.

[21]  Francesco Ciucci,et al.  Modeling electrochemical impedance spectroscopy , 2019, Current Opinion in Electrochemistry.

[22]  B. Bedürftig,et al.  Investigation of the low frequency Warburg impedance of Li-ion cells by frequency domain measurements , 2019, Journal of Energy Storage.

[23]  B. Delobel,et al.  On the electrochemical impedance response of composite insertion electrodes – Toward a better understanding of porous electrodes , 2019, Electrochimica Acta.

[24]  T. Osaka,et al.  Systematic analysis of interfacial resistance between the cathode layer and the current collector in lithium-ion batteries by electrochemical impedance spectroscopy , 2019, Journal of Power Sources.

[25]  Pouyan Shafiei Sabet,et al.  RETRACTED: Non-invasive investigation of predominant processes in the impedance spectra of high energy lithium-ion batteries with Nickel-Cobalt-Aluminum cathodes , 2018, Journal of Power Sources.

[26]  Pouyan Shafiei Sabet,et al.  Non-invasive investigation of predominant processes in the impedance spectra of high energy lithium-ion batteries with nickel–cobalt–aluminum cathodes , 2018 .

[27]  Ellen Ivers-Tiffée,et al.  Impedance based time-domain modeling of lithium-ion batteries: Part I , 2018 .

[28]  M. Bazant,et al.  Electrochemical Impedance Imaging via the Distribution of Diffusion Times. , 2017, Physical review letters.

[29]  B. Boukamp Derivation of a Distribution Function of Relaxation Times for the (fractal) Finite Length Warburg. , 2017 .

[30]  W. D. Widanage,et al.  A Comparison between Electrochemical Impedance Spectroscopy and Incremental Capacity-Differential Voltage as Li-ion Diagnostic Techniques to Identify and Quantify the Effects of Degradation Modes within Battery Management Systems , 2017 .

[31]  H. Takenouti,et al.  Electrochemical Impedance Spectroscopy response study of a commercial graphite-based negative electrode for Li-ion batteries as function of the cell state of charge and ageing , 2017 .

[32]  Alon Oz,et al.  Analysis of impedance spectroscopy of aqueous supercapacitors by evolutionary programming: Finding DFRT from complex capacitance , 2016 .

[33]  E. Ivers-Tiffée,et al.  The Distribution Function of Differential Capacity as a new tool for analyzing the capacitive properties of Lithium-Ion batteries , 2015 .

[34]  Ting Hei Wan,et al.  Influence of the Discretization Methods on the Distribution of Relaxation Times Deconvolution: Implementing Radial Basis Functions with DRTtools , 2015 .

[35]  E. Ivers-Tiffée,et al.  Approximability of Impedance Spectra By RC Elements and Implications for Impedance Analysis , 2015 .

[36]  Susan L. Rose-Pehrsson,et al.  Expanding the Operational Limits of the Single-Point Impedance Diagnostic for Internal Temperature Monitoring of Lithium-ion Batteries , 2015 .

[37]  Francesco Ciucci,et al.  Analysis of Electrochemical Impedance Spectroscopy Data Using the Distribution of Relaxation Times: A Bayesian and Hierarchical Bayesian Approach , 2015 .

[38]  Ting Hei Wan,et al.  Optimal Regularization in Distribution of Relaxation Times applied to Electrochemical Impedance Spectroscopy: Ridge and Lasso Regression Methods - A Theoretical and Experimental Study , 2014 .

[39]  Jörg Illig,et al.  Understanding the impedance spectrum of 18650 LiFePO4-cells , 2013 .

[40]  Xuning Feng,et al.  Using probability density function to evaluate the state of health of lithium-ion batteries , 2013 .

[41]  Dirk Uwe Sauer,et al.  Experimental investigation of the lithium-ion battery impedance characteristic at various conditions and aging states and its influence on the application , 2013 .

[42]  Ellen Ivers-Tiffée,et al.  The distribution of relaxation times as basis for generalized time-domain models for Li-ion batteries , 2013 .

[43]  J. Schmidt,et al.  The Distribution of Relaxation Times as Beneficial Tool for Equivalent Circuit Modeling of Fuel Cells and Batteries , 2012 .

[44]  Moses Ender,et al.  Separation of Charge Transfer and Contact Resistance in LiFePO4-Cathodes by Impedance Modeling , 2012 .

[45]  D. Sauer,et al.  Characterization of high-power lithium-ion batteries by electrochemical impedance spectroscopy. I. Experimental investigation , 2011 .

[46]  J. Schmidt,et al.  Studies on LiFePO4 as cathode material using impedance spectroscopy , 2011 .

[47]  D. Sauer,et al.  Characterization of high-power lithium-ion batteries by electrochemical impedance spectroscopy. II: Modelling , 2011 .

[48]  M. Dubarry,et al.  Incremental Capacity Analysis and Close-to-Equilibrium OCV Measurements to Quantify Capacity Fade in Commercial Rechargeable Lithium Batteries , 2006 .

[49]  J. Kilner,et al.  Differential impedance analysis of single crystal and polycrystalline yttria stabilized zirconia , 2006 .

[50]  Daria Vladikova,et al.  Secondary differential impedance analysis – a tool for recognition of CPE behavior , 2004 .

[51]  H. Schichlein,et al.  Deconvolution of electrochemical impedance spectra for the identification of electrode reaction mechanisms in solid oxide fuel cells , 2002 .

[52]  H. Schichlein System Identification: A New Modelling Approach for SOFC Single Cells , 1999 .