电工技术学报2026，Vol.41Issue(1)：329-342,14.DOI:10.19595/j.cnki.1000-6753.tces.242325
基于电化学-声学耦合模型的磷酸铁锂电池老化状态表征
Aging State Characterization of Lithium Iron Phosphate Battery Based on Electrochemical-Acoustic Coupling Model
摘要
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.关键词
磷酸铁锂电池/电化学-声学耦合模型/循环老化/超声特性/结构演变Key words
LiFePO4 battery/electrochemical-acoustic coupling model/cyclic aging/ultrasonic characterization/structural evolution分类
信息技术与安全科学引用本文复制引用
Liu Suzhen,Meng Weixu,Yuan Luhang,Xu Zhicheng,Jin Liang..基于电化学-声学耦合模型的磷酸铁锂电池老化状态表征[J].电工技术学报,2026,41(1):329-342,14.基金项目
国家自然科学基金(52577230,52307238)和河北省自然科学基金(E2024202010,E2024202231)资助项目. （52577230,52307238）
