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1.华南理工大学 机械与汽车工程学院,广东 广州 510640
2.中山大学 材料学院,广东 深圳 518107
3.中山大学 化学学院,广东 广州 510275
赵 杰,博士,副教授,研究方向:智能电化学传感系统,E-mail:zhaoj77@scut.edu.cn
纸质出版日期:2025-02-15,
收稿日期:2024-05-06,
修回日期:2024-06-01,
录用日期:2024-06-11
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袁剑英,邹明佳,赵杰,黄扬春,于耀光,崔国峰.应用于锂电池荷电状态估计的电流型阻抗谱分析仪的开发及应用[J].分析测试学报,2025,44(02):369-377.
YUAN Jian-ying,ZOU Ming-jia,ZHAO Jie,HUANG Yang-chun,YU Yao-guang,CUI Guo-feng.Development and Application of a Galvanostatic Electrochemical Impedance Spectroscopy Analyzer Applied for Estimating the State of Charge of Lithium Batteries[J].Journal of Instrumental Analysis,2025,44(02):369-377.
袁剑英,邹明佳,赵杰,黄扬春,于耀光,崔国峰.应用于锂电池荷电状态估计的电流型阻抗谱分析仪的开发及应用[J].分析测试学报,2025,44(02):369-377. DOI: 10.12452/j.fxcsxb.24050614.
YUAN Jian-ying,ZOU Ming-jia,ZHAO Jie,HUANG Yang-chun,YU Yao-guang,CUI Guo-feng.Development and Application of a Galvanostatic Electrochemical Impedance Spectroscopy Analyzer Applied for Estimating the State of Charge of Lithium Batteries[J].Journal of Instrumental Analysis,2025,44(02):369-377. DOI: 10.12452/j.fxcsxb.24050614.
研制了一种高功率密度紧凑型的锂电池电流型电化学阻抗谱(GEIS)分析仪,其具有集成度高、精度高、输出激励大和测试频率范围广等优点,满足不同锂电池GEIS测试的需求。在完成仪器整体方案设计后,对硬件系统模块展开深入测试,以确保系统可靠性和准确性。通过对实际18650型锂电池进行GEIS测试,并将结果与专业仪器Gamry Reference 600+进行比较,结果显示本仪器测试阻抗模值的相对误差和相位绝对误差分别不超过2%和3°。为验证所提出的电池荷电状态(SOC)估计算法,使用该仪器对实际电池样本进行测试,共获得60组不同SOC下锂电池的阻抗谱数据。将阻抗谱数据作为高斯过程回归(GPR)的输入,可以实现对锂电池SOC的估计,平均绝对误差在3.9%以内。该文研发的锂电池GEIS分析仪,有望集成于电池管理系统,为更多基于阻抗谱的锂电池状态估计算法提供实时的数据来源,以实现锂电池更高水平的运行状态监测。
In this paper,a high-power-density compact galvanostatic electrochemical impedance spectroscopy(GEIS) measuring instrument for lithium batteries is developed. It offers the advantages of high integration,high accuracy,large output excitation and wide range of test frequency to meet the requirements of different lithium battery GEIS tests. After the overall schematic design of the instrument is completed,the hardware system modules are thoroughly tested to ensure the reliability and accuracy of the system. Through the GEIS test on the actual 18650 lithium batteries and comparing the results with the professional instrument Gamry Reference 600+,both sets of results indicate that the relative impedance modulus error and the absolute phase error of this instrument are no more than 2% and 3°,respectively. In order to validate the battery state of charge(SOC) estimation algorithm proposed in this paper,the instrument was used to test actual battery samples,resulting in a total of 60 sets of impedance spectral data from lithium batteries at various SOCs. Using the impedance spectrum data as the input for Gaussian process regression(GPR),the estimation of SOC of lithium batteries can be achieved with an average absolute error of 3.9%. The lithium battery GEIS meter developed in this paper is expected to be integrated into the battery management system,thereby furnishing a real-time data source for impedance spectrum-based lithium battery state estimation algorithms. This integration is intended to facilitate a more comprehensive monitoring of the operational state of lithium batteries.
电流型电化学阻抗谱荷电状态估计阻抗谱测试锂电池高斯过程回归
galvanostatic electrochemical impedance spectroscopystate of charge estimationimpedance spectrum testlithium batteryGaussian process regression
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