Uncertainty characterization of rapid battery impedance measurements using binary sequence

Pseudo-random binary sequence (PRBS) and discrete-interval binary sequence (DIBS) are two common binary sequence, which can be employed for rapid measurement of electrochemical impedance spectroscopy (EIS), providing a foundation for state analysis and fault diagnosis of the lithium-ion battery. In this paper, we employ the uncertainty characterization to evaluate EIS measurement results, which is crucial for optimizing binary sequences and enhancing measurement techniques. The battery is measured repeatedly, and confidence ellipses are constructed to characterize the uncertainty at each frequency point. The separation of random error and systematic error is achieved. Then, the influence of the sampling window length, battery temperature, and excitation current amplitude is analyzed based on uncertainty. The sampling window should be slightly longer than the signal length, in order to decrease the consistency divergence in the middle and low frequencies. As battery temperature decreases, the semi-major axis of the confidence ellipse gets longer, reflecting battery state is easier to change by measurement. As the excitation current amplitude increases, measurement uncertainty declines. Finally, the measurement uncertainties of PRBS and DIBS are compared. The results shows that their measurement uncertainties are determined by the energy at frequency points.