基于电化学-声学耦合模型的磷酸铁锂电池老化状态表征

doi:10.19595/j.cnki.1000-6753.tces.242325

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Abstract The life span reduction of lithium-ion batteries is closely related to the evolution of the internal structure during cyclic aging. Throughout the battery aging process, the stress on the electrode particles changes continuously, and the long-term stress changes will lead to fatigue damage within the electrode structure, resulting in irreversible strain, which ultimately diminishes the ability of the electrode particles to store lithium ions, thereby causing a degradation in battery capacity. However, the sealed packaging of lithium-ion batteries makes it difficult to directly observe their internal structures. Compared with traditional inspection methods like X-ray tomography that provides only limited penetration into lithium-ion battery materials and neutron diffraction which faces challenges in effectively distinguishing microstructural changes inside the battery, ultrasonic inspection stands out as an effective solution. It provides an effective means of monitoring the dynamic changes in the internal structure of lithium-ion batteries due to its ability to non-destructively detect the evolution of the internal structure of the workpiece and its high accuracy. This study establishes an electrochemical- acoustic coupling model for lithium-ion batteries based on the theory of stress and strain of electrode active particles and the principles of structural acoustics. The acoustic characterization method for lithium-ion battery aging is investigated through a combination of simulation and experimentation.
Firstly, the structural changes of electrode particles and the acoustic characteristic variations caused by these changes during the aging process of LiFePO₄ batteries are simulated using an electrochemical-acoustic coupling finite element model. This approach elucidates the evolution mechanism of the internal structure of the batteries during the aging process by investigating the relationship between structural mechanical parameters and acoustic characteristics. Additionally, it addresses the challenge of directly measuring the internal structural parameters of the sealed LiFePO₄ battery structures. The lithium-ion battery aging ultrasonic detection platform is constructed, and the accuracy of the simulation model is validated by comparing the simulation results with experimental outcomes from LiFePO₄ battery aging tests. Based on these experimental results, the response characteristics of the acoustic parameters during the aging process are analyzed, and a mapping relationship between the acoustic characteristic parameters and the health state of the battery is subsequently established.
Simulation and experimental results demonstrate that the acoustic characteristics are effective in characterizing the aging of lithium-ion batteries. The growth of the solid electrolyte interface (SEI) and the degradation of the graphite electrode structure during the aging process of LiFePO₄ batteries lead to a reduction in Young's modulus of the battery and an increase in electrode density. Through ultrasonic characterization, the parameter signal amplitude (SA) gradually decreases, while the time of flight (ToF) progressively increases, both trends decelerate as the aging process deepens. Among these parameters, SA exhibits higher sensitivity to battery aging, providing a more intuitive reflection of changes in battery health status. The root-mean-square error (RMSE) between the aging simulation and experimental results for lithium-ion batteries is 0.053 1 mV, indicating that the battery aging state can be effectively characterized using the electrochemical-acoustic coupling model. This method provides a fresh perspective for analyzing the aging mechanisms of lithium-ion batteries and enabling non-destructive detection of battery health status.

Key words： LiFePO₄ battery electrochemical-acoustic coupling model cyclic aging ultrasonic characterization structural evolution

Received: 22 December 2024

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	Liu Suzhen
	Meng Weixu
	Yuan Luhang
	Xu Zhicheng
	Jin Liang

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Liu Suzhen,Meng Weixu,Yuan Luhang等. Aging State Characterization of Lithium Iron Phosphate Battery Based on Electrochemical-Acoustic Coupling Model[J]. Transactions of China Electrotechnical Society, 2026, 41(1): 329-342.

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[1] 李英顺, 阚宏达, 郭占男, 等. 基于数据预处理和VMD-LSTM-GPR的锂离子电池剩余寿命预测[J]. 电工技术学报, 2024, 39(10): 3244-3258.
Li Yingshun, Kan Hongda, Guo Zhannan, et al.Prediction of remaining useful life of lithium-ion battery based on data preprocessing and VMD-LSTM- GPR[J]. Transactions of China Electrotechnical Society, 2024, 39(10): 3244-3258.
[2] 赵英杰, 张闯, 刘素贞, 等. 基于电极等效电路模型的锂离子电池无析锂快充策略优化研究[J]. 电工技术学报, 2024, 39(18): 5868-5882.
Zhao Yingjie, Zhang Chuang, Liu Suzhen, et al.Optimization of fast charging strategy for lithium-ion batteries without deposition based on electrode equivalent circuit model[J]. Transactions of China Electrotechnical Society, 2024, 39(18): 5868-5882.
[3] 李卓昊, 石琼林, 王康丽, 等. 锂离子电池健康状态估计方法研究现状与展望[J]. 电力系统自动化, 2024, 48(20): 109-129.
Li Zhuohao, Shi Qionglin, Wang Kangli, et al.Research status and prospects of state of health estimation methods for lithium-ion batteries[J]. Automa- tion of Electric Power Systems, 2024, 48(20): 109-129.
[4] 张闯, 杨浩, 刘素贞, 等. 基于阻抗在线测量的锂离子电池过放电诱发内短路识别研究[J]. 电工技术学报, 2024, 39(6): 1656-1670.
Zhang Chuang, Yang Hao, Liu Suzhen, et al.Research on overdischarge-induced internal short circuit iden- tification of lithium-ion battery based on impedance online measurement[J]. Transactions of China Electro- technical Society, 2024, 39(6): 1656-1670.
[5] 马敬轩, 赖铱麟, 吕娜伟, 等. 锂离子电池智能传感监测及预警技术[J]. 电工技术学报, 2025, 40(3): 941-963.
Ma Jingxuan, Lai Yilin, Lü Nawei, et al.Lithium-ion battery intelligent sensing monitoring and early warning technology[J]. Transactions of China Electro- technical Society, 2025, 40(3): 941-963.
[6] Zeng Jing, Liu Sifeng.Research on aging mechanism and state of health prediction in lithium batteries[J]. Journal of Energy Storage, 2023, 72: 108274.
[7] Dayani S, Markötter H, Schmidt A, et al.Multi-level X-ray computed tomography (XCT) investigations of commercial lithium-ion batteries from cell to particle level[J]. Journal of Energy Storage, 2023, 66: 107453.
[8] Luo Yuxi, Gao Xiaoyu, Dong Mingjie, et al.Exploring the structural properties of cathode and anode materials in Li-ion battery via neutron diffraction technique[J]. Chinese Journal of Structural Chemistry, 2023, 42(5): 100032.
[9] 孙丙香, 王家驹, 苏晓佳, 等. 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, et al.Study on online identification method of low frequency electrochemical impedance spectroscopy for lithium- ion battery based on step wave[J]. Transactions of China Electrotechnical Society, 2023, 38(11): 3064-3072.
[10] Copley R J, Dwyer-Joyce R S. Prediction of the internal structure of a lithium-ion battery using a single ultrasound wave response[J]. Journal of Energy Storage, 2023, 72: 108778.
[11] Sood B, Osterman M, Pecht M.Health monitoring of lithium-ion batteries[C]//2013 IEEE Symposium on Product Compliance Engineering (ISPCE), Austin, TX, USA, 2013: 1-6.
[12] Hsieh A G, Bhadra S, Hertzberg B J, et al.Electrochemical-acoustic time of flight: in operando correlation of physical dynamics with battery charge and health[J]. Energy & Environmental Science, 2015, 8(5): 1569-1577.
[13] Knehr K W, Hodson T, Bommier C, et al.Understanding full-cell evolution and non-chemical electrode crosstalk of Li-ion batteries[J]. Joule, 2018, 2(6): 1146-1159.
[14] Robinson J B, Maier M, Alster G, et al.Spatially resolved ultrasound diagnostics of Li-ion battery electrodes[J]. Physical Chemistry Chemical Physics, 2019, 21(12): 6354-6361.
[15] Chang W, Mohr R, Kim A, et al.Measuring effective stiffness of Li-ion batteries via acoustic signal processing[J]. Journal of Materials Chemistry A, 2020, 8(32): 16624-16635.
[16] Ladpli P, Kopsaftopoulos F, Chang Fukuo.Estimating state of charge and health of lithium-ion batteries with guided waves using built-in piezoelectric sensors/ actuators[J]. Journal of Power Sources, 2018, 384: 342-354.
[17] Deng Zhe, Huang Zhenyu, Shen Yue, et al.Ultrasonic scanning to observe wetting and “unwetting” in Li-ion pouch cells[J]. Joule, 2020, 4(9): 2017-2029.
[18] Huang Ming, Kirkaldy N, Zhao Yan, et al.Quantitative characterisation of the layered structure within lithium-ion batteries using ultrasonic resonance[J]. Journal of Energy Storage, 2022, 50: 104585.
[19] Li Honggang, Zhou Zhenggan.Numerical simulation and experimental study of fluid-solid coupling-based air-coupled ultrasonic detection of stomata defect of lithium-ion battery[J]. Sensors, 2019, 19(10): 2391.
[20] Copley R J, Cumming D, Wu Y, et al.Measurements and modelling of the response of an ultrasonic pulse to a lithium-ion battery as a precursor for state of charge estimation[J]. Journal of Energy Storage, 2021, 36: 102406.
[21] Song Guorong, Li Yaoqian, Lü Yan, et al.Estimating state of charge of lithium-ion batteries using ultrasonic reflection and transmission coefficients by Legendre orthogonal polynomial method[C]//2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI), Changsha, China, 2019: 1256-1261.
[22] Wang Xiangling, Lyu Yan, Song Guorong, et al.Theoretical analysis of ultrasonic reflection/trasmis- sion characteristics of lithium-ion battery[C]// 2020 15th Symposium on Piezoelectrcity, Acoustic Waves and Device Applications (SPAWDA), Zhengzhou, China, 2021: 292-296.
[23] Song Guorong, Li Yaoqian, Lyu Yan, et al.Ultrasonic reflection characteristics of lithium-ion battery based on Legendre orthogonal polynomial method[J]. Ultrasonics, 2022, 124: 106736.
[24] 吕炎, 耿亮, 宋国荣, 等. 多层多孔锂离子电池结构的导波频散特征及其应用[J]. 声学学报, 2022, 47(6): 748-756.
Lü Yan, Geng Liang, Song Guorong, et al.Guided wave dispersion characteristics of multi-layered porous lithium-ion batteries and their application[J]. Acta Acustica, 2022, 47(6): 748-756.
[25] Zhang Binpeng, Lyu Yan, Gao Jie, et al.Ultrasonic characterization of multi-layered porous lithium-ion battery structure for state of charge[J]. Ultrasonics, 2023, 134: 107060.
[26] Gao Jie, Zhang Liangheng, Lyu Yan, et al.Ultrasonic guided wave measurement and modeling analysis of the state of charge for lithium-ion battery[J]. Journal of Energy Storage, 2023, 72: 108384.
[27] Li Xiaoyu, Yu Xintong, Zheng Shanpi, et al.Study on ultrasonic transmission characteristics and failure modes of a lithium-ion battery[C]//The Proceedings of the 5th International Conference on Energy Storage and Intelligent Vehicles (ICEIV 2022), online, 2022: 850-856.
[28] Sun Bo, Zhang Chuang, Xu Zhicheng, et al.Ultrasonic diagnosis of the nonlinear aging charac- teristics of lithium-ion battery under high-rate discharge conditions[J]. Journal of Power Sources, 2023, 567: 232921.
[29] Xu Wuke, Yang Yuewang, Shi Fan, et al.Ultrasonic phased array imaging of gas evolution in a lithium-ion battery[J]. Cell Reports Physical Science, 2023, 4(9): 101579.
[30] Gao Jie, Zhang Yifan, Lü Yan, et al.A novel ultrasonic transmission coefficient spectrums approach to detecting lithium deposition of lithium-ion batteries[J]. Journal of Power Sources, 2025, 636: 236555.
[31] McGee T, Neath B, Matthews S B, et al. A model- driven approach to ultrasonic detection of state of charge in lithium-ion batteries[J]. The Journal of the Acoustical Society of America, 2022, 152(S4): A283.
[32] Fu Rujian, Xiao Meng, Choe S Y.Modeling, validation and analysis of mechanical stress genera-tion and dimension changes of a pouch type high power Li-ion battery[J]. Journal of Power Sources, 2013, 224: 211-224.
[33] Laresgoiti I, Käbitz S, Ecker M, et al.Modeling mechanical degradation in lithium ion batteries during cycling: solid electrolyte interphase fracture[J]. Jour- nal of Power Sources, 2015, 300: 112-122.
[34] Deshpande R D, Bernardi D M.Modeling solid- electrolyte interphase (SEI) fracture: coupled mechanical/chemical degradation of the lithium ion battery[J]. Journal of the Electrochemical Society, 2017, 164(2): A461-A474.
[35] Verma M K S, Basu Suman, Hariharan K S, et al. A strain-diffusion coupled electrochemical model for lithium-ion battery[J]. Journal of the Electrochemical Society, 2017, 164(13): A3426-A3439.
[36] Zhang Weijun.Structure and performance of LiFePO₄ cathode materials: a review[J]. Journal of Power Sources, 2011, 196(6): 2962-2970.
[37] Zhang Binpeng, Lyu Yan, Gao Jie, et al.Ultrasonic reflection/transmission characteristics for state of charge of li-ion battery[J]. Applied Acoustics, 2023, 214: 109687.
[38] 刘素贞, 陈云龙, 张闯, 等. 融合多维超声时频域特征的锂离子电池荷电状态估计[J]. 电工技术学报, 2023, 38(17): 4539-4550, 4563.
Liu Suzhen, Chen Yunlong, Zhang Chuang, et al.State of charge estimation of lithium-ion batteries fused with multi-dimensional ultrasonic time-frequency domain features[J]. Transactions of China Electro- technical Society, 2023, 38(17): 4539-4550, 4563.
[39] Schulitz F T, Lu Yichi, Wadley H N G. Ultrasonic propagation in metal powder-viscous liquid suspen- sions[J]. The Journal of the Acoustical Society of America, 1998, 103(3): 1361-1369.