(150c) Operando Electrochemical Impedance Spectroscopy Using Segmented Chirp Signals for Real-Time Battery Monitoring

Electrochemical Impedance Spectroscopy (EIS) is a prominent characterization technique as it captures temporal changes across the spectrum of frequencies. The various processes and reaction mechanisms occur inside battery at different time scale. Slower reaction mechanisms, such as diffusion between electrodes, manifest at lower frequencies, while faster processes, like current collection at electrode tabs, are observable at higher frequencies [1]. Hence, a single impedance spectrum provides a comprehensive signature of the current state of the battery. The Conventional EIS available in various scientific potentiostats uses a single sine technique to measure the impedance spectra, and it is a time-consuming process.

In contrast, Chirp-based EIS has emerged as an effective method for faster impedance measurement, particularly in linear or nonlinear stationary systems [2,3]. However, its utilization for real-time, operando measurements during dynamic conditions, such as battery charging and discharging, has not yet been fully explored. Operando EIS has previously been limited to slower single sine or multisine methods [1, 4]. This study presents a segmented chirp-based approach for operando EIS, spanning frequencies from 10^-2 Hz to 10⁴ Hz. The segmented chirp method, achieves rapid impedance characterization by sweeping through the frequency range with high-bandwidth, low-duration chirp signals. For the calculation of chirp-based EIS, the full frequency range ( 10^-2 Hz to 10⁴ Hz.) is segmented into two regions - (10^-2 Hz to 10¹ Hz.) and (10¹ Hz to 10⁴ Hz.) to reduce aliasing effects and spectral leakage.

Simulations were carried out on a Doyle-Fuller-Newman (DFN) model of the LGM50 Li-ion battery in the PyBaMM environment [5]. The exponential chirp signal of amplitude 500mA is superimposed on the input charging current signal of 1A. Whereas, the conventional EIS has been carried out at 61 discrete frequency points, and each point contained 14 cycles of sinusoidal signal. For each frequency, only the final 5 cycles were used in calculating impedance to ensure stable measurements.

The total time required to generate operando EIS using conventional and chirp technique is 6800 sec and 210 sec respectively. The chirp based EIS has total of 720000 datapoints whereas conventional has only 61 datapoints as equal to no. of frequency perturbations. Hence, the chirp-based EIS generates the same EIS plot 30 times faster than conventional EIS in operando conditions, with enhanced temporal resolution.

Therefore, the segmented chirp EIS technique shows promising potential for real-time monitoring and fault detection in electric vehicles, where rapid battery health assessments during charging and discharging are critical.

References:
1. X. Wang, X. Wei, J. Zhu, H. Dai, Y. Zheng, X. Xu, Q. Chen “A review of modeling, acquisition, and application of lithium-ion battery impedance for onboard battery management”, eTransportation, 7 (2021) 100093
2. R. Suresh, S. Swaminathan, R. Rengaswamy, “Rapid impedance spectroscopy using dual phase shifted chirp signals for electrochemical applications” International Journal of Hydrogen Energy 45, 17 (2020) 10536-10548.
3. R. Samant, R. Suresh, O.S. Deshmukh, R. Thangavel, “Rapid Electrochemical Impedance Spectroscopy via, Continuous Amplitude Envelope of Chirp Signal on, Li-ion 21700 battery ”, 9th International Youth Conference on Energy (IYCE), (2024) IEEE
4. N. Hallemans, W. D. Widanage, X. Zhu, S. Moharana, M. Rashid, A. Hubin, J. Lataire “Operando electrochemical impedance spectroscopy and its application to commercial Li-ion batteries”
5. V. Sulzer, S. G. Marquis, R. Timms, M. Robinson, S. J. Chapman, “Python Battery Mathematical Modelling (PyBaMM)”. Journal of Open Research Software, 9, 1 (2021), 14