董明, 范文杰, 刘王泽宇, 张志斌, 任明. 基于特征频率阻抗的锂离子电池健康状态评估[J]. 中国电机工程学报, 2022, 42(24): 9094-9104. DOI: 10.13334/j.0258-8013.pcsee.212036
引用本文: 董明, 范文杰, 刘王泽宇, 张志斌, 任明. 基于特征频率阻抗的锂离子电池健康状态评估[J]. 中国电机工程学报, 2022, 42(24): 9094-9104. DOI: 10.13334/j.0258-8013.pcsee.212036
DONG Ming, FAN Wenjie, LIU Wangzeyu, ZHANG Zhibin, REN Ming. Health Assessment of Lithium-ion Batteries Based on Characteristic Frequency Impedance[J]. Proceedings of the CSEE, 2022, 42(24): 9094-9104. DOI: 10.13334/j.0258-8013.pcsee.212036
Citation: DONG Ming, FAN Wenjie, LIU Wangzeyu, ZHANG Zhibin, REN Ming. Health Assessment of Lithium-ion Batteries Based on Characteristic Frequency Impedance[J]. Proceedings of the CSEE, 2022, 42(24): 9094-9104. DOI: 10.13334/j.0258-8013.pcsee.212036

基于特征频率阻抗的锂离子电池健康状态评估

Health Assessment of Lithium-ion Batteries Based on Characteristic Frequency Impedance

  • 摘要: 随着锂电池的广泛使用,快速准确的估计锂电池健康状态对于电池安全管理十分重要。为准确估计锂电池健康状态,为电池管理系统提供策略,该文在电池正常工作温度范围内对不同荷电状态、不同健康状态的锂电池进行电化学阻抗谱测试,并对锂电池电化学阻抗谱的弛豫时间分布进行分析,筛选出可有效表征锂电池健康状态的特征频率,建立包含温度影响的锂电池健康状态估计模型,提出基于电化学阻抗谱的锂电池健康状态估计方法。实验结果表明,处于低频区的极化过程S1与S2不受锂电池荷电状态的影响。在不同温度下,极化过程S1与S2受电池健康状态的影响较为显著,可以有效表征电池健康状态。该文建立的电池健康状态估计模型可以将健康状态估计误差控制在2.5%以内。弛豫时间分布方法可以实现锂电池特征频率的筛选,且电化学阻抗谱可用于电池健康状态估计,提升电池安全水平。

     

    Abstract: With the widespread use of lithium batteries, accurate estimation of the health status of lithium batteries is very important for battery safety management. In order to accurately estimate the health status of lithium batteries and provide strategies for battery management systems, this paper conducted electrochemical impedance spectroscopy tests on lithium batteries with different states of charge and health in a wide temperature range, and analyzed the lithium battery distribution of relaxation time. A method for estimating the state of health of lithium batteries based on electrochemical impedance spectroscopy was proposed within the operating temperature range of the battery. The test results show that the polarization processes S1 and S2 in the low frequency region are not affected by the state of charge of the lithium battery. However, at different temperatures, the polarization processes S1 and S2 are significantly affected by the state of health, and can effectively characterize the state of battery health. After that, a polarization resistance estimation method based on the relaxation time distribution was proposed to screen out the characteristic frequencies that can effectively characterize the health of the battery, and established a lithium battery health estimation model including the influence of temperature. Finally, the verification experiment shows that the battery health state estimation model established in the article can control the health state estimation error within 2.5%. It can be proved that the distribution of relaxation time method can realize the screening of the characteristic frequencies of batteries, and electrochemical impedance spectroscopy can be used to estimate the state of battery health and improve the level of battery safety.

     

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