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 $\text{m}\Omega $ ± $26~ \mu \Omega $ .

Lithium-ion batteries are a key technology for electromobility; thus, quality control in cell production is a central aspect for the success of electric vehicles. The detection of defects and poor insulation behavior of the separator is essential for high-quality batteries. Optical quality control methods in cell production are unable to detect small but still relevant defects in the separator layer, e.g., pinholes or particle contaminations. This gap can be closed by executing high-potential testing to analyze the insulation performance of the electrically insulating separator layer in a pouch cell. Here, we present an experimental study to identify different separator defects on dry cell stacks on the basis of electric voltage stress and mechanical pressure. In addition, finite element modeling (FEM) is used to generate physical insights into the partial discharge by examining the defect structures and the corresponding electric fields, including topographical electrode roughness, impurity particles, and voids in the separator. The test results show that hard discharges are associated with significant separator defects. Based on the study, a voltage of 350 to 450 V and a pressure of 0.3 to 0.6 N/mm² are identified as optimum ranges for the test methodology, resulting in failure detection rates of up to 85%.

Characterization and classification of lithium-ion batteries (LIB) are of high relevance for cell and battery producers, especially with the rising demands on LIBs for electric vehicle applications. We present a compact measurement station with 256 multiplexed channels to measure the open-circuit voltage (OCV) and the alternating current internal resistance (ACIR) of a tray of 256 cylindrical cells. Four different cell types were distinguished based on the ACIR values ranging between 11 and 22 Ω. The measurement station performance was assessed based on the cell-fixture recontacting error and the electronic noise of the channels. Several calibration workflows of different complexity were evaluated. Data correction for the measure station was done by a two-term calibration procedure, including a short and gain correction. This resulted in a 67% improvement on the real part of ACIR and 83% on the imaginary part both compared to a bench-top-based reference system. Electromagnetic finite element method (FEM) modeling was done to model the cables and the cell fixture, including different wire lengths. The state of health (SoH) of cycled cells was computed, and their correlation to ACIR was discussed, including the electrochemical interpretation based on an equivalent electric circuit model. Overall, we show how this multiplexed measurement station can be used for classification and LIB quality control in battery manufacturing.

We developed an impedance quartz crystal microbalance (QCM) approach with the ability to simultaneously record mass changes and calibrated energy dissipation with high sensitivity using an impedance analyzer. This impedance QCM measures frequency shifts and resistance changes of sensing quartz crystals very stable, accurately, and calibrated, thus yielding quantitative information on mass changes and dissipation. Resistance changes below 0.3 Ω were measured with corresponding dissipation values of 0.01 µU (micro dissipation units). The broadband impedance capabilities allow measurements between 20 Hz and 120 MHz including higher harmonic modes of up to 11th order for a 10 MHz fundamental resonance frequency quartz crystal. We demonstrate the adsorbed mass, calibrated resistance, and quantitative dissipation measurements on two biological systems including the high affinity based avidin-biotin interaction and nano-assemblies of polyelectrolyte layers. The binding affinity of a protein-antibody interaction was determined. The impedance QCM is a versatile and simple method for accurate and calibrated resistance and dissipation measurements with broadband measurement capabilities for higher harmonics measurements.