Quantitative Cell Classification Based on Calibrated Impedance Spectroscopy and Metrological Uncertainty
Source abstract
Abstract
Abstract Electrochemical impedance spectroscopy (EIS) is widely used for battery cell testing in industrial production and R&D labs. This work addresses the use of EIS calibration and uncertainty analysis in cell classification. Five scenarios are investigated to discuss qualitatively the impact of calibration and uncertainty on classification. For an experimental demonstration, a cylindrical cell was measured with two mechanical fixtures of different qualities and characterized regarding random errors and calibrated impedances. The impact of uncertainty and impedance calibration on the cell classification is shown, and based on the uncertainty and corresponding error bounds, a confidence level was established for the classification results. Quantitative uncertainty bounds are presented for the full EIS frequency spectrum ranging from 150 mHz to 5 kHz.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Battery Technologies Research · Advancements in Battery Materials · Fault Detection and Control Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Keysight Laboratories Keysight Technologies Austria GmbH Linz 4020 Austria
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