Inter-laboratory comparison of S-parameter measurements with dynamic uncertainty evaluation

Singh, D.; Salter, M J; Votsi, Haris; Ridler, N M

doi:10.1109/arftg47584.2020.9071655

Cited by 2 publications

(1 citation statement)

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“…In addition to calibration, uncertainty characterization is essential for precision measurements and reliable further analysis of the results. For example, several studies investigated the uncertainty sources and their characterization in microwave measurements at GHz frequencies, where typically a vector network analyzer (VNA) is used [18], [19], [20], [21], [22]. For instance, in the field of telecommunication, the study of uncertainty characterization of random and systematic errors is a common effort in providing precision measurements for high-frequency applications.…”

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confidence: 99%

Measurement Uncertainty in Battery Electrochemical Impedance Spectroscopy

Moradpour

Kasper

Hoffmann

et al. 2022

IEEE Trans. Instrum. Meas.

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Electrochemical impedance spectroscopy (EIS) is a widely used method for battery tests in manufacturing and automotive field applications. As such, accurate measurement of the impedance over a broad frequency spectrum is of high relevance, also requiring specific calibration methods and evaluation of error bounds. Here, we report for the first time a comprehensive uncertainty analysis of calibrated EIS for batteries. We aim to identify two uncertainty sources, the fixture repeatability and measurement noise, and evaluate their effect on the measured impedances. To this end, an error model assigned to each of them and the real and imaginary parts of the model parameters are characterized in the frequency range of 100 mHz-5 kHz by performing specific impedance measurements on a shunt resistor and a short standard. We demonstrate how different uncertainties are combined with the measured impedances, incorporating also the impedance calibration procedure. The errors are propagated through the calibration and correction functions by applying the linear error propagation method provided by the UncLib package from METAS. The error bounds are derived from uncertainty propagation in the shunt standard and the prismatic battery cell EIS and verified by conducting a series of measurements. Thereby, the uncertainty is shown as ellipsoids in every frequency point of the Nyquist plot. For instance, at 1 Hz, the 34-Ah prismatic cell shows a calibrated real-part impedance and two standard deviation error bounds of 1.07 m ± 26 μ.

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confidence: 99%