journal article·2026-08

Rapid impedance spectrum extraction from relaxation signals via a battery kinetics-informed neural network

Shiqin Chen, Qi Zhang, Ziwei Hao, Dafang Wang, Hao Li, Kai Xiong

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OpenAlex topics: Advanced Battery Technologies Research · Advanced battery technologies research · Advanced Battery Materials and Technologies

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References (49)

Show source-provided references
1. Comprehensive review of lithium-ion battery materials and development challenges
2. Electric vehicles batteries: requirements and challenges10.1016/j.joule.2020.01.013 ↗
3. Data-driven prediction of battery cycle life before capacity degradation10.1038/s41560-019-0356-8 ↗
4. Aging mechanisms, prognostics and management for lithium-ion batteries: recent advances
5. Dynamic electrochemical impedance spectroscopy: a forward application approach for lithium-ion battery status assessment
6. Operando detection for lithium plating in lithium-ion batteries via expansion force signal decoupling10.1016/j.jpowsour.2025.238644 ↗
7. Lithium-ion battery condition monitoring: a frontier in acoustic sensing technology
8. A comparison and accuracy analysis of impedance-based temperature estimation methods for Li-ion batteries10.1016/j.apenergy.2016.04.103 ↗
9. Optimization and application of the distribution of relaxation times based on characteristic frequency resolution and hyperparameters10.1016/j.jpowsour.2022.231955 ↗
10. Probing of internal short circuit in lithium-ion pouch cells by electrochemical impedance spectroscopy under mechanical abusive conditions10.1149/1945-7111/abd452 ↗
11. 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 systems10.1016/j.jpowsour.2017.03.042 ↗
12. Adaptive state of health estimation for lithium-ion batteries using impedance-based timescale information and ensemble learning10.1016/j.energy.2023.129283 ↗
13. Transfer learning with deep neural network for capacity prediction of Li-ion batteries using EIS measurement10.1109/TTE.2022.3170230 ↗
14. On the use of electrochemical impedance spectroscopy to characterize and model the aging phenomena of lithium-ion batteries: a critical review10.1016/j.jpowsour.2021.229860 ↗
15. In situ monitoring of lithium-ion battery degradation using an electrochemical model10.1016/j.apenergy.2019.05.038 ↗
16. Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning
17. A multi-frequency electrical impedance spectroscopy technique of artificial neural network-based for the static state of charge
18. Real-time overcharge warning and early thermal runaway prediction of Li-ion battery by online impedance measurement
19. Online impedance spectrum measurement of fuel cells based on Morlet wavelet transform10.1016/j.ijhydene.2021.05.012 ↗
20. Fast electrochemical impedance spectroscopy of lithium-ion batteries based on the large square wave excitation signal
21. A fast impedance calculation-based battery State-of-health estimation method10.1109/TIE.2021.3097668 ↗
22. Investigation of an M-sequence based impedance spectrum acquisition method for lithium-ion batteries from the engineering application perspective
23. Simultaneous determination of electrochemical impedance of lithium-ion rechargeable batteries with measurement of charge-discharge curves by wavelet transformation10.1016/j.electacta.2017.03.077 ↗
24. Predicting battery impedance spectra from 10-second pulse tests under 10 hz sampling rate10.1016/j.isci.2023.106821 ↗
25. Simultaneous prediction of impedance spectra and state for lithium-ion batteries from short-term pulses10.1016/j.electacta.2023.142218 ↗
26. Deep neural network battery impedance spectra prediction by only using constant-current curve
27. Constructing battery impedance spectroscopy using partial current in constant-voltage charging or partial relaxation voltage10.1016/j.apenergy.2023.122454 ↗
28. Battery impedance spectrum prediction from partial charging voltage curve by machine learning10.1016/j.jechem.2023.01.004 ↗
29. Transformer-based prediction of wide-frequency battery impedance spectra from low-rate time-domain data
30. Online multi-scenario impedance spectra generation for batteries based on small-sample learning10.1016/j.xcrp.2024.102134 ↗
31. Online generation of full-frequency electrochemical impedance spectra for lithium-ion batteries using early-stage partial relaxation voltage curve10.1016/j.etran.2025.100482 ↗
32. The timescale identification decoupling complicated kinetic processes in lithium batteries10.1016/j.joule.2022.05.005 ↗
33. Optimal regularization in distribution of relaxation times applied to electrochemical impedance spectroscopy: ridge and Lasso regression methods - A theoretical and experimental study10.1016/j.electacta.2014.09.058 ↗
34. On a variation of the Tikhonov regularization method for calculating the distribution function of relaxation times in impedance spectroscopy10.1016/j.electacta.2020.136683 ↗
35. Deconvolving distribution of relaxation times, resistances and inductance from electrochemical impedance spectroscopy via statistical model selection: exploiting structural-sparsity regularization and data-driven parameter tuning
36. How the distribution of relaxation times enhances complex equivalent circuit models for fuel cells10.1016/j.electacta.2020.136764 ↗
37. Electrochemical impedance preprocessing with distribution of relaxation time transform10.1016/j.jpowsour.2023.233062 ↗
38. Influence of the discretization methods on the distribution of relaxation times deconvolution: implementing radial basis functions with DRTtools10.1016/j.electacta.2015.09.097 ↗
39. Research progress and application of deep learning in remaining useful life, state of health and battery thermal management of lithium batteries10.1016/j.est.2023.107868 ↗
40. Studies on LiFePO4 as cathode material using impedance spectroscopy10.1016/j.jpowsour.2010.09.121 ↗
41. Non-iterative parameter identification for lithium-ion battery kinetics across multiple frequency ranges via electrochemical impedance model10.1016/j.jpowsour.2025.238533 ↗
42. Application of electrochemical impedance spectroscopy to degradation and aging research of lithium-ion batteries
43. Cross-scale decoupling kinetic processes in lithium-ion batteries using the multi-dimensional distribution of relaxation time10.1002/advs.202406934 ↗
44. An easy-to-implement multi-point impedance technique for monitoring aging of lithium ion batteries10.1016/j.jpowsour.2018.11.087 ↗
45. Impedance characterization of lithium-ion batteries aging under high-temperature cycling: importance of electrolyte-phase diffusion10.1016/j.jpowsour.2019.04.040 ↗
46. Modeling graphite anodes with serial and transmission line models10.1016/j.jpowsour.2015.02.038 ↗
47. Low-temperature separating lithium-ion battery interfacial polarization based on distribution of relaxation times (DRT) of impedance10.1109/TTE.2020.3028475 ↗
48. A review of composite solid-state electrolytes for lithium batteries: fundamentals, key materials and advanced structures
49. Transferring the internal processes of the lead–acid battery to the lithium–sulfur battery by verification with electrochemical impedance spectroscopy10.1016/j.est.2021.103148 ↗