Robust Approach to Battery Equivalent-Circuit-Model Parameter Extraction Using Electrochemical Impedance Spectroscopy

Marzia Abaspour, Krishna R. Pattipati, Behnam Shahrrava and Balakumar Balasingam ()
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Marzia Abaspour: Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON N9B 3P4, Canada
Krishna R. Pattipati: Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269, USA
Behnam Shahrrava: Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON N9B 3P4, Canada
Balakumar Balasingam: Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON N9B 3P4, Canada

Energies, 2022, vol. 15, issue 23, 1-26

Abstract: Electrochemical impedance spectroscopy (EIS) is a well-established method of battery analysis, where the response of a battery to either a voltage or current excitation signal spanning a wide frequency spectrum is measured and analyzed. State-of-the-art EIS analysis is limited to high-precision measurement systems within laboratory environments. In order to be relevant in practical applications, EIS analysis needs to be carried out with low-cost sensors, which suffer from high levels of measurement noise. This article presents an approach to estimate the equivalent circuit model (ECM) parameters of a Li-Ion battery pack based on EIS measurements in the presence of high levels of noise. The proposed algorithm consists of a fast Fourier transform, feature extraction, curve fitting, and least-squares estimation. The results of the proposed parameter-estimation algorithm are compared to that of recent work for objective performance comparison. The error analysis of the proposed approach, in comparison to the existing approach, demonstrated significant improvement in parameter estimation accuracy in low signal-to-noise ratio (SNR) regions. Results show that the proposed algorithm significantly outperforms the previous method under high-measurement-noise scenarios without requiring a significant increase in computational resources.

Keywords: Li-ion batteries; battery management system; equivalent circuit model; impedance; electrochemical impedance spectroscopy (EIS); least squares estimation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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