Study on Online Identification Method of Low Frequency Electrochemical Impedance Spectroscopy for Lithium-Ion Battery Based on Step Wave
Sun Bingxiang1, Wang Jiaju2, Su Xiaojia1, Zhang Weige1, Zhao Xinze1
1. National Active Distribution Network Technology Research Center Beijing Jiaotong University Beijing 100044 China; 2. Yinchuan Power Supply Company State Grid Ningxia Power Co. Ltd Yinchuan 750011 China
Abstract：Electrochemical impedance spectroscopy (EIS) is an external characterization of the internal performance parameters of lithium-ion battery. How to get rid of the dependence on proprietary equipment for online identification of EIS, especially low-frequency EIS identification is of great significance for accurately estimating battery status. At present, the existing methods of online identification of EIS in engineering mainly obtain the corresponding sine wave by Fourier decomposition of the square wave. However, there are differences between the harmonic amplitudes obtained after decomposition and the fundamental amplitudes, and the identification results have relatively large errors in the low frequency band of EIS. Therefore, in order to further improve the identification accuracy of the EIS low frequency band, this paper takes NCM lithium-ion battery as the research object in the framework of the communication protocols between battery management system (BMS) and bi-directional charging-discharging device. Further, an online identification method for lithium-ion batteries low-frequency EIS based on step waves is proposed via the transformation relationship of step signals and sine signals, the frequency range is selected to be below 2 Hz. In order to better analyze the EIS low-frequency identification method based on step wave proposed in this paper, three groups of experiments are mainly designed. The feasibility of the step wave EIS (STEIS) identification method, the accuracy of the STEIS low-frequency identification results with different sampling frequencies, and the advantages of the EIS test method compared with the square wave Fourier decomposition are mainly analyzed. The test frequency is 10 mHz~2 Hz, and the temperature is all carried out at 25℃. The equipment and components used in the experiment include Bio-Logic VMP-300 electrochemical workstation for electrochemical impedance spectroscopy, high and low temperature test chamber for controlling ambient temperature, power battery under test, and computer for control and data storage. The experimental results show that the ten-step step wave can realize the accurate fitting of the sine wave, and the goodness of fit is 0.96, which can realize the online identification of the EIS of the lithium-ion battery. From the analysis of the identification results, it can be found that at different SOC points, as long as the sampling frequency is high enough, the EIS test in a wider frequency domain can be realized. When the sampling frequency is 50 Hz, high-precision STEIS results can be obtained in the test frequency range of 10 mHz~2 Hz, and the average relative error is within 1.12%. Comparing the STEIS method with the square wave Fourier decomposition method, the average relative error in the measurement frequency domain is 6.4% smaller than that of the square wave. It can be seen that the STEIS method is significantly better than the square wave. The method proposed in this paper can get rid of the dependence on the sine wave equipment. Within the framework of the existing communication protocol, it can be realized by controlling the bidirectional charging and discharging equipment through the battery management system, which provides an important method support for the online active evaluation of the operating status of the battery.
孙丙香, 王家驹, 苏晓佳, 张维戈, 赵鑫泽. 基于阶梯波的锂离子电池电化学阻抗谱低频段在线辨识方法[J]. 电工技术学报, 2023, 38(11): 3064-3072.
Sun Bingxiang, Wang Jiaju, Su Xiaojia, Zhang Weige, Zhao Xinze. Study on Online Identification Method of Low Frequency Electrochemical Impedance Spectroscopy for Lithium-Ion Battery Based on Step Wave. Transactions of China Electrotechnical Society, 2023, 38(11): 3064-3072.
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