Optimal Binary Sequence Design With Minimum Sampled Rate for Fast Lithium-Ion Battery Impedance Measurement

High sampling rate in the time domain has been widely used for battery impedance measurement, but it increases data volume, storage demand, and extraction cost, limiting practical online deployment. This article develops an optimally sampled binary sequence for efficient battery frequency response extraction. Specifically, a switching-edge impulse–damped-oscillation equivalent model that incorporates the excitation amplitude, together with a sensing-chain noise model, is established to capture waveform distortions. Besides, a spectral-aliasing impact metric is introduced to quantify the influence of the time-domain sampling rate on frequency-domain aliasing. According to these models, an iterative optimization procedure is proposed to determine the minimum sampling rate that meets the accuracy requirement. The robustness of the proposed method is validated across different conditions and excitation sequences, achieving a maximum normalized root-mean-square error of 0.45%. The average Kramers-Kronig residuals for the impedance under charging and discharging conditions are 0.58% and 0.72%, respectively.