电阻抗
电池(电)
介电谱
计算机科学
信号(编程语言)
材料科学
电子工程
功率(物理)
电气工程
工程类
化学
物理
电极
电化学
物理化学
量子力学
程序设计语言
作者
Jichang Peng,Jinhao Meng,Xinghao Du,Lei Cai,Daniel‐Ioan Stroe
标识
DOI:10.1109/tii.2022.3217474
摘要
Electrochemical impedance spectroscopy (EIS) can provide fruitful information for Lithium-ion (Li-ion) battery modeling and diagnosis, yet EIS measurement is time-consuming with low-frequency signal injection. By stacking a group of broadband signals, pseudorandom sequence (PRS) makes it possible to obtain the battery EIS in a few seconds at the expense of measurement accuracy and signal-to-noise ratio (SNR). Thus, this article focuses on developing a highly effective signal processing procedure to extract useful information from the PRS for accurate EIS measurement. To enhance the ability of the data cleaning procedure, a three-dimensional cloud is first reconstructed for each impedance by integrating its power spectrum (PS). The impedance with lower PS can be easily removed through a statistical based multiple selection mechanism, which enables the extraction of the EIS without altering the original measurement. Experimental results on a 3000 mAh Li-ion battery prove the effectiveness of the proposed method.
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