Abstract
The longer measurement time and high equipment cost of traditional electrochemical impedance spectroscopy (EIS) testing techniques make it difficult to be applied to engineering practice. To address the above issues, firstly, this paper proposes a rapid impedance spectroscopy testing method based on M sequence. Three sets of M sequences with different frequencies and orders are applied to the battery in turn as current excitation signals to get the corresponding voltage response signals, and then the impedance information of batteries at each frequency is obtained using the continuous wavelet transform algorithm, which greatly reduces test time. Secondly, according to the characteristics of the impedance spectroscopy of LiCoO2 batteries, a third-order fractional-order equivalent circuit model is established, and the impedance spectroscopy of each aging state is fitted to obtain the corresponding model parameters. After the correlation analysis of parameters, this paper builds a multiple linear regression equation between internal resistance parameters and state of health (SOH) for SOH estimation. Finally, it has been verified that the error of the proposed SOH estimation algorithm is within 0.3%.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Zhuang, Q., Yang, Z., Zhang, L., Cui, Y.: Research progress on diagnosis of electrochemical impedance spectroscopy in lithium-ion batteries. Progress Chem. 32(6), 761–791 (2020). (in Chinese)
Felder, M.P., Banerjee, S., Jansen, P., et al.: SoLE—an alternative approach for impedance measurement of Lithium-ion battery cells. In: 8th IET International Conference on Power Electronics, Machines and Drives (PEMD). IET (2016)
Waligo. A., Barendse. P.: A comparison of the different broadband impedance measurement techniques for lithium-ion batteries. In: 2016 IEEE Energy Conversion Congress and Exposition (ECCE). IEEE (2017)
Das, L., Srinivasan, B., Rengaswamy, R.: On-line performance monitoring of PEM fuel cell using a fast EIS approach. Proc. Am. Control. Conf. 2015, 1611–1616 (2015)
Katayama, N., Kogoshi, S.: Real-time electrochemical impedance diagnosis for fuel cells using a DC–DC converter. IEEE Trans. Energy Convers. 30(2), 707–713 (2015)
Sihvo, J., Stroe, D., Messo, T., Roinila, T.: Fast approach for battery impedance identification using pseudo-random sequence signals. IEEE Trans. Power Electron. 35(3), 2548–2557 (2020)
Geng, Z., Savvidis, C.: On-board impedance diagnostics method of Li-ion traction batteries using pseudo-random binary sequences. In: 20th European Conference on Power Electronics and Applications (ECCE). IEEE (2018)
Weddle, P.J., Kee, R.J., Vincent, T.: A stitching algorithm to identify wide-bandwidth electrochemical impedance spectra for Li-Ion Batteries using binary perturbations. J. Electrochem. Soc. 165(9), A1679–A1684 (2018)
Li, W., Huang, Q., Yang, W. et al.: Rapid impedance spectroscopy reconstruction based on pseudo-random binary sequences and its application in electrochemical energy field. J. Electrochem. 26(3), 19 (2020) (in Chinese)
He, X., Sun, B., Zhang, W., Fan, X., Su, X., Ruan, H.: Multi-time scale variable-order equivalent circuit model for virtual battery considering initial polarization condition of lithium-ion battery. Energy 244, Part B (2022)
Yang, B., Dai, H.: Quantification method of aging mode of lithium-ion battery based on AC impedance spectroscopy. Eng J Wuhan Univ 52(7), 7 (2019). (in Chinese)
Acknowledgments
This research was partially funded by the National Key R&D Program of China 2021YFB2400700, and by the China Three Gorges Corporation 202103408.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 Beijing Paike Culture Commu. Co., Ltd.
About this paper
Cite this paper
Liu, Y., Li, J., Hou, L., Cai, X., Zhang, C. (2023). Rapid Impedance Spectroscopy Reconstruction Based on M Sequence for SOH Estimation of Lithium-Ion Battery. In: Sun, F., Yang, Q., Dahlquist, E., Xiong, R. (eds) The Proceedings of the 5th International Conference on Energy Storage and Intelligent Vehicles (ICEIV 2022). ICEIV 2022. Lecture Notes in Electrical Engineering, vol 1016. Springer, Singapore. https://doi.org/10.1007/978-981-99-1027-4_81
Download citation
DOI: https://doi.org/10.1007/978-981-99-1027-4_81
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-1026-7
Online ISBN: 978-981-99-1027-4
eBook Packages: EngineeringEngineering (R0)