锂电池无损检测技术研究进展与比较分析

doi:10.19595/j.cnki.1000-6753.tces.250943

摘要
图/表
参考文献
相关文章 (15)

全文: PDF (4089 KB)
输出: BibTeX | EndNote (RIS)

摘要

锂电池具有能量密度高、使用寿命长等优势,目前其已经被广泛应用于消费电子、交通、储能等领域。然而,锂电池内部结构损伤与功能退化问题频发,对锂电池安全、有效使用造成影响。上述问题催生了对高精度、非侵入式锂电池故障检测和状态监测技术的强烈需求。本文围绕锂电池无损检测技术的研究现状与发展趋势展开系统综述,重点涵盖X射线技术、超声波技术、磁共振与磁场成像、中子成像、拉曼散射、红外检测、光纤检测七类技术,比较了各技术的原理、适用场景、优劣势与代表性应用,并对锂电池无损检测技术的发展进行了展望。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	孔祥博
	彭丽莎
	蒋超凡
	李世松
	黄松岭

关键词 ：无损检测, 锂电池, 故障检测, 状态监测

Abstract：

Lithium batteries, with high energy density, long cycle life, and environmental compatibility, are widely applied in electric vehicles, portable electronics, and stationary energy storage. However, complex operating conditions often induce internal structural damage and functional degradation, leading to safety risks and performance loss. Conventional battery management systems (BMS), relying mainly on voltage, current, and surface temperature, cannot accurately capture early-stage internal defects such as electrode deformation, electrolyte anomalies, or lithium dendrite growth. This limitation has driven the development of high-precision, non-invasive non-destructive testing (NDT) technologies for structure and state monitoring.
This paper reviews seven major NDT techniques for lithium batteries: X-ray imaging, ultrasonic testing, magnetic resonance and magnetic field imaging, neutron imaging, Raman scattering, infrared detection, and fiber optic sensing. Their principles, applications, strengths, and weaknesses are compared, and future trends are outlined.
X-ray techniques use penetration and diffraction to achieve structural and chemical analysis. X-ray computed tomography (CT) provides multi-scale 3D/4D imaging of electrode morphology, lithium deposition, and crack propagation. X-ray diffraction (XRD) tracks crystalline phase transitions and lattice evolution, while X-ray absorption spectroscopy (XAS) and X-ray photoelectron spectroscopy (XPS) offer element-specific chemical state and interfacial reaction insights. Advantages include high resolution and combined structural-chemical information, but equipment cost and artefacts in dense materials limit applicability. Ultrasonic testing monitors acoustic time of flight, amplitude, and attenuation to infer density, modulus, and defects. Transmission, pulse-echo, and time-of-flight diffraction methods are used for state-of-charge (SOC) and state-of-health (SOH) estimation, and for detecting lithium plating, gas generation, electrolyte wetting issues, and early thermal runaway. It is low-cost, sensitive, and suitable for in-situ use, though results are affected by temperature and structural complexity. Magnetic resonance and magnetic field imaging include nuclear magnetic resonance (NMR) for local structural and ionic dynamics, magnetic resonance imaging (MRI) for 3D mapping of lithium distribution and electrolyte transport, and magnetic field imaging (MFI) for reconstructing internal current density. These provide element selectivity and dynamic visualization, but are limited by resolution, isotope abundance, and high equipment requirements. Neutron imaging offers high sensitivity to light elements and strong penetration through metal casings, enabling visualization of lithium distribution, electrolyte migration, gas evolution, and electrode ageing without disassembly. Integration with X-ray tomography enables correlative 4D imaging, but neutron source availability and cost restrict widespread use. Raman scattering uses inelastic light scattering to probe molecular structure and interfacial chemistry. It enables phase transition tracking, solid-electrolyte interphase (SEI) characterization, and dendrite detection. Enhanced methods such as surface-enhanced Raman spectroscopy (SERS) improve sensitivity, though penetration depth and signal strength remain constraints. Infrared detection comprises infrared thermography, for non-contact surface temperature field monitoring, and infrared spectroscopy, for molecular-level reaction tracking. Thermography detects thermal anomalies and degradation; Fourier transform infrared spectroscopy (FTIR) and related techniques reveal SEI formation and electrolyte decomposition pathways. These are contact-free and versatile, but affected by environmental factors and limited spatial resolution. Fiber optic sensing-including fiber Bragg grating (FBG) and Fabry-Perot interferometry-monitors temperature, strain, and mechanical-electrochemical coupling with high sensitivity and electromagnetic immunity. Applications include SOC/SOH estimation, early failure warning, and stress analysis. While adaptable, these systems require careful integration and long-term stability assurance. Comparative analysis shows X-ray and neutron imaging excel in structural resolution; ultrasound and fiber optics in real-time embedded monitoring; magnetic resonance and MFI in structural-dynamic correlation; and Raman/infrared spectroscopy in interfacial process analysis. Future NDT development will emphasize multi-modal integration, online inspection for manufacturing quality control, real-time in-operation diagnostics, and adaptability to extreme conditions. Key directions include portable X-ray CT, AI-enhanced image reconstruction, compact neutron sources, advanced optical signal enhancement, and machine-learning-based multi-sensor fusion.
By bridging laboratory diagnostics with deployment in production and operational environments, next-generation NDT will support safer, longer-lasting, and more efficient lithium battery systems, strengthening their role in sustainable energy applications.

Key words： Non-destructive testing lithium battery fault detection state monitoring

收稿日期: 2025-06-03

PACS:

TM912

基金资助:

国家自然科学基金资助项目（52477008,U23B20113）

通讯作者: 黄松岭男,1970年生,教授,研究方向为电磁测量与无损检测。E-mail：huangsling@tsinghua.edu.cn

作者简介: 孔祥博男,2002年生,博士研究生,研究方向为无损检测与结构监测。E-mail：kxb24@mails.tsinghua.edu.cn

引用本文:

孔祥博, 彭丽莎, 蒋超凡, 李世松, 黄松岭. 锂电池无损检测技术研究进展与比较分析[J]. 电工技术学报, 0, (): 20250943-20250943. Kong Xiangbo, Peng Lisha, Jiang Chaofan, Li Shisong, Huang Songling. Research Progress and Comparative Analysis of Non-Destructive Testing Technologies for Lithium Batteries. Transactions of China Electrotechnical Society, 0, (): 20250943-20250943.

链接本文:

https://dgjsxb.ces-transaction.com/CN/10.19595/j.cnki.1000-6753.tces.250943 https://dgjsxb.ces-transaction.com/CN/Y0/V/I/20250943

[1] 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(03):941-963.
Ma Jingxuan, Lai Yilin, Lv Nawei, et al.Intelligent sensing monitoring and early warning technology for lithium-ion batteries[J]. Transactions of China Electrotechnical Society, 2025, 40(3): 941-963.
[2] 李卓昊, 石琼林, 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, 20: 109-129. Li Zhuohao, Shi Qionglin, et al. Research status and outlook on health state estimation methods for lithium-ion batteries[J]. Electric Power Systems Automation, 2024, 20: 109-129. Wang Y, Lai X, Chen Q, et al. Progress and challenges in ultrasonic technology for state estimation and defect detection of lithium-ion batteries[J]. Energy Storage Materials, 2024, 69: 103430.
[3] 郭飞,雍培,刘欣宇,等.考虑状态相依老化特性的电池储能参与调峰投资效益评估[J].电工技术学报,2025,40(13):4330-4342.
Guo Fei, Yong Pei, Liu Xinyu, et al.Evaluating the investment benefits of battery energy storage participating in peak shaving considering the state-dependent aging characteristics[J]. Transactions of China Electrotechnical Society, 2025, 40(13): 4330-4342.
[4] Shang Y, Wang S, Tang N, et al.Research Progress in Fault Detection of Battery Systems: A Review[J]. Journal of Energy Storage, 2024, 98: 113079.
[5] Alfraheed M I.A Review of Measurement Methods for Lithium-Based Battery Defect and Degradation Analysis[J]. International Journal of Modelling and Simulation,2025.DOI:10.1080/02286203.2025.2479667
[6] Gou Y, Yan Y, Lyu Y, et al.Advances in Acoustic Techniques for Evaluating Defects and Properties in Lithium-Ion Batteries: A Review[J]. Ultrasonics, 2024, 142: 107400.
[7] Jin Yang, Zhao Zhixing, Miao Shan, et al.Explosion Hazards Study of Grid-Scale Lithium-Ion Battery Energy Storage Station[J]. Journal of Energy Storage [J]. Journal of Energy Storage, 2021, 42: 102987.
[8] Kim T, Song W, Son D Y, et al.Lithium-Ion Batteries: Outlook on Present, Future, and Hybridized Technologies[J]. Journal of materials chemistry A, 2019, 7(7): 2942-2964.
[9] Liu B, Zhang J G, Xu W.Advancing Lithium Metal Batteries[J]. Joule, 2018, 2(5): 833-845.
[10] Sun C, Liu J, Gong Y, et al.Recent Advances in All-Solid-State Rechargeable Lithium Batteries[J]. Nano Energy, 2017, 33: 363-386.
[11] Urbonaite S, Poux T, Novák P.Progress Towards Commercially Viable Li-S Battery Cells[J]. Advanced Energy Materials, 2015, 5(16): 1500118.
[12] Gabbar H A, Othman A M, Abdussami M R.Review of Battery Management Systems (BMS) Development and Industrial Standards[J]. Technologies, 2021, 9(2): 28.
[13] 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 C, Yang H, Liu SZ, et al. Research on over-discharge-induced internal short circuit identification of lithium-ion battery based on impedance online measurement[J]. Transactions of China Electrotechnical Society, 2024, 39(6): 1656-1670.
[14] 张闯, 王泽山, 刘素贞, 等. 基于电化学阻抗谱的锂离子电池过放电诱发内短路的检测方法[J]. 电工技术学报, 2023, 38(23): 6278-6291.
Zhang C, Wang ZS, Liu SZ, et al. Detection method of overdischarge-induced internal short circuit in lithium-ion batteries based on electrochemical impedance spectroscopy[J]. Transactions of China Electrotechnical Society, 2023, 38(23): 6278-6291.
[15] 袁奥特, 蔡涛, 刘政辰, 等. 基于电化学阻抗谱的锂离子电池电滥用失效预警研究[J]. 电工技术学报, 2025, 40(7): 2306-2321.
Yuan Aote, Cai Tao, Liu Zhengchen, et al.Study on early warning of electrical abuse failure of lithium-ion batteries based on electrochemical impedance spectroscopy[J]. Transactions of China Electrotechnical Society, 2025, 40(7): 2306-2321.
[16] 方斯顿,刘龙真,孔赖强,等.基于双向长短期记忆网络含间接健康指标的锂电池SOH估计[J].电力系统自动化,2024,48(04):160-168.
Fang S, Liu L, Kong L, Niu T, Chen G, Liao R.State-of-health estimation for lithium-ion batteries incorporating indirect health indicators based on bi-directional long short-term memory networks[J]. Automation of Electric Power Systems, 2024, 48(4): 160-168.
[17] Rahimi-Eichi H, Ojha U, Baronti F, et al.Battery Management System: An Overview of Its Application in the Smart Grid and Electric Vehicles[J]. IEEE Industrial Electronics Magazine, 2013, 7(2): 4-16.
[18] Lawder M T, Suthar B, Northrop P W C, et al. Battery Energy Storage System (BESS) and Battery Management System (BMS) for Grid-Scale Applications[J]. Proceedings of the IEEE, 2014, 102(6): 1014-1030.
[19] Wan X, Xu X, Li F, et al.Application of Nondestructive Testing Technology in Device-Scale for Lithium-Ion Batteries[J]. Small Structures, 2024, 5(3): 2300196.
[20] Hao S, Bailey J J, Iacoviello F, et al.3D Imaging of Lithium Protrusions in Solid-State Lithium Batteries Using X-Ray Computed Tomography[J]. Advanced Functional Materials, 2021, 31(10): 2007564.
[21] Cai Z, Pan T, Jiang H, et al.State-of-Charge Estimation of Lithium-Ion Batteries Based on Ultrasonic Detection[J]. Journal of Energy Storage, 2023, 65: 107264.
[22] Sanders K J, Ciezki A A, Berno A, et al.Quantitative Operando 7Li NMR Investigations of Silicon Anode Evolution During Fast Charging and Extended Cycling[J]. Journal of the American Chemical Society, 2023, 145(39): 21502-21513.
[23] Romanenko K, Jerschow A.Numerical Modeling of Surface-Scan MRI Experiments for Improved Diagnostics of Commercial Battery Cells[J]. Journal of Magnetic Resonance Open, 2022, 10: 100061.
[24] Brauchle F, Grimsmann F, von Kessel O, et al. Defect Detection in Lithium Ion Cells by Magnetic Field Imaging and Current Reconstruction[J]. Journal of Power Sources, 2023, 558: 232587.
[25] Gajan A, Lecourt C, Torres Bautista B E, et al. Solid Electrolyte Interphase Instability in Operating Lithium-Ion Batteries Unraveled by Enhanced-Raman Spectroscopy[J]. ACS Energy Letters, 2021, 6(5): 1757-1763.
[26] Conder J, Bouchet R, Trabesinger S, et al.Direct Observation of Lithium Polysulfides in Lithium-Sulfur Batteries Using Operando X-Ray Diffraction[J]. Nature Energy, 2017, 2(6): 1-7.
[27] Gao A, Jiang P, Duan M, et al.Interphase Design Enabling Stable Cycling of All-Solid-State Lithium Metal Batteries by In-Situ X-Ray Photoelectron Spectroscopy Lithium Metal Sputtering[J]. Journal of Power Sources, 2024, 602: 234299.
[28] Ogley M J W, Menon A S, Pandey G C, et al. Metal-Ligand Redox in Layered Oxide Cathodes for Li-Ion Batteries[J]. Joule, 2025, 9(1): 101775.
[29] Robinson J B, Owen R E, Kok M D R, et al. Identifying Defects in Li-Ion Cells Using Ultrasound Acoustic Measurements[J]. Journal of The Electrochemical Society, 2020, 167(12): 120530.
[30] Merazi-Meksen T, Kemmouche A, Boudraa M, et al.Sparse Representations to Replace TOFD Images in Non-Destructive Testing of Materials[J]. Journal of Nondestructive Evaluation, 2017, 36: 1-7.
[31] Nazer N S, Strobl M, Kaestner A, et al.Operando Neutron Imaging Study of a Commercial Li-Ion Battery at Variable Charge-Discharge Current Densities[J]. Electrochimica Acta, 2022, 427: 140793.
[32] Sheng S, Li H, Zhang Y, et al.Early Detection of Lithium Battery Leakage Using a Highly Sensitive In Situ ZIF-8 Membrane-Coated Micro-Nano Optical Fibre[J]. Light: Advanced Manufacturing, 2025, 6(1): 130-141.
[33] Bai W, Bu C, Chen P, et al.Study on Multimodal Excitation Infrared Thermography for Surface Damage Detection of Lithium Battery Pole Piece[J]. Nondestructive Testing and Evaluation, 2025. DOI: 10.1080/10589759.2025.2508427.
[34] Bak S M, Shadike Z, Lin R, et al.In Situ/Operando Synchrotron-Based X-Ray Techniques for Lithium-Ion Battery Research[J]. NPG Asia Materials, 2018, 10(7): 563-580.
[35] Pietsch P, Wood V.X-Ray Tomography for Lithium Ion Battery Research: A Practical Guide[J]. Annual Review of Materials Research, 2017, 47(1): 451-479.
[36] Llewellyn A V, Matruglio A, Brett D J L, et al. Using In-Situ Laboratory and Synchrotron-Based X-Ray Diffraction for Lithium-Ion Batteries Characterization: A Review on Recent Developments[J]. Condensed Matter, 2020, 5(4): 75.
[37] Shojaei M J, Sivarajah A, Safdar T, et al.Advanced Battery Cathode Microstructure Analysis Through Operando Synchrotron X-Ray Tomography and Super-Resolution Deep Learning[J]. Solid State Ionics, 2025, 422: 116818.
[38] Yusuf M, LaManna J M, Paul P P, et al. Simultaneous Neutron and X-Ray Tomography for Visualization of Graphite Electrode Degradation in Fast-Charged Lithium-Ion Batteries[J]. Cell Reports Physical Science, 2022, 3(11), 101145.
[39] Xu C, Märker K, Lee J, et al.Bulk Fatigue Induced by Surface Reconstruction in Layered Ni-Rich Cathodes for Li-Ion Batteries[J]. Nature materials, 2021, 20(1): 84-92.
[40] Li X, Ren Z, Norouzi Banis M, et al.Unravelling the Chemistry and Microstructure Evolution of a Cathodic Interface in Sulfide-Based All-Solid-State Li-Ion Batteries[J]. ACS Energy Letters, 2019, 4(10): 2480-2488.
[41] Louisia S, Koper M T M, Mom R V. Prospects for Electrochemical X-Ray Photoelectron Spectroscopy as a Powerful Electrochemical Interface Characterization Technique[J]. Current Opinion in Electrochemistry, 2024, 45: 101462.
[42] Galiounas E, Tranter T G, Owen R E, et al.Battery State-of-Charge Estimation Using Machine Learning Analysis of Ultrasonic Signatures[J]. Energy and AI, 2022, 10: 100188.
[43] Liu K, Fang J, Zhao S, et al.Battery State-of-Health Estimation: An Ultrasonic Detection Method with Explainable AI[J]. Energy, 2025, 319: 134923.
[44] Xu Z, Chen X, Liu S, et al.Online Detection and In-Situ Characterization of Lithium Plating in Lithium-Ion Batteries Based on Ultrasonic Signals[J]. Journal of Energy Storage, 2025, 116: 116041.
[45] Xu W, Yang Y, Shi F, et al.Ultrasonic Phased Array Imaging of Gas Evolution in a Lithium-Ion Battery[J]. Cell Reports Physical Science, 2023, 4(9): 101579.
[46] Deng Z, Huang Z, Shen Y, et al.Ultrasonic Scanning to Observe Wetting and “Unwetting” in Li-Ion Pouch Cells[J]. Joule, 2020, 4(9): 2017-2029.
[47] McGee T M, Neath B, Matthews S, et al. Ultrasonic Inspection of Lithium-Ion Pouch Cells Subjected to Localized Thermal Abuse[J]. Journal of Power Sources, 2023, 583: 233542.
[48] Zhao K, Wan X, Lin Y, et al.Magnetic Field‐Based Non‐Destructive Testing Techniques for Battery Diagnostics[J]. Advanced Energy Materials, 2025, 15(10): 2404295.
[49] Baek J, Kim S, Kim H T, et al.Postmortem 7Li NMR Analysis for Assessing the Reversibility of Lithium Metal Electrodes in Lithium Metal Batteries[J]. Journal of Energy Chemistry, 2024, 94: 430-440.
[50] Ilott A J, Mohammadi M, Schauerman C M, et al.Rechargeable Lithium-Ion Cell State of Charge and Defect Detection by In-Situ Inside-Out Magnetic Resonance Imaging[J]. Nature communications, 2018, 9(1): 1776.
[51] Ziesche R F, Kardjilov N, Kockelmann W, et al.Neutron Imaging of Lithium Batteries[J]. Joule, 2022, 6(1): 35-52.
[52] Gao L, Han S, Ni H, et al. Application of Neutron Imaging in Observing Various States of Matter Inside Lithium Batteries [J]. National Science Review, 2023, 10(11): nwad238.
[53] Baddour-Hadjean R, Pereira-Ramos J P. Raman Microspectrometry Applied to the Study of Electrode Materials for Lithium Batteries[J]. Chemical reviews, 2010, 110(3): 1278-1319.
[54] Jehnichen P, Korte C.Operando Raman Spectroscopy Measurements of a High-Voltage Cathode Material for Lithium-Ion Batteries[J]. Analytical chemistry, 2019, 91(13): 8054-8061.
[55] Weiling M, Pfeiffer F, Baghernejad M.Vibrational Spectroscopy Insight into the Electrode | Electrolyte Interface/Interphase in Lithium Batteries[J]. Advanced energy materials, 2022, 12(46): 2202504.
[56] Cheng Q, Wei L, Liu Z, et al.Operando and Three-Dimensional Visualization of Anion Depletion and Lithium Growth by Stimulated Raman Scattering Microscopy[J]. Nature communications, 2018, 9(1): 2942.
[57] Amaral M M, Real C G, Yukuhiro V Y, et al.In Situ and Operando Infrared Spectroscopy of Battery Systems: Progress and Opportunities[J]. Journal of Energy Chemistry, 2023, 81: 472-491.
[58] Ni S, Lama S, Lee Y J, et al.Early Detection of Secondary Battery Degradation by Infrared Technology: An Experimental Study[J]. Arabian Journal for Science and Engineering, 2025, 50(4): 2527-2540.
[59] Dileep H, Jha K K, Mahapatra P S, et al.Thermal Characterization of Pouch Cell Using Infrared Thermography and Electrochemical Modelling for the Design of Effective Battery Thermal Management System[J]. Applied Energy, 2024, 376: 124301.
[60] Yang J, Solomatin N, Kraytsberg A, et al.In-Situ Spectro-Electrochemical Insight Revealing Distinctive Silicon Anode Solid Electrolyte Interphase Formation in a Lithium-Ion Battery[J]. ChemistrySelect, 2016, 1(3): 572-576.
[61] Norberg N S, Kostecki R.Interfacial Phenomena at a Composite LiMnPO₄ Cathode[J]. Journal of The Electrochemical Society, 2012, 159(7): A1091.
[62] Zhang Y, Katayama Y, Tatara R, et al.Revealing Electrolyte Oxidation via Carbonate Dehydrogenation on Ni-Based Oxides in Li-Ion Batteries by In Situ Fourier Transform Infrared Spectroscopy[J]. Energy & Environmental Science, 2020, 13(1): 183-199.
[63] Wahl M S, Spitthoff L, Muri H I, et al.The Importance of Optical Fibres for Internal Temperature Sensing in Lithium-Ion Batteries During Operation[J]. Energies, 2021, 14(12): 3617.
[64] Xia X, Wu W, Li Z, et al.State of Charge Estimation for Commercial Li-Ion Battery Based on Simultaneously Strain and Temperature Monitoring Over Optical Fiber Sensors[J]. IEEE Transactions on Instrumentation and Measurement, 2024, 73: 2516411.
[65] Li Y, Li K, Liu X, et al.A Hybrid Machine Learning Framework for Joint SOC and SOH Estimation of Lithium-Ion Batteries Assisted with Fiber Sensor Measurements[J]. Applied Energy, 2022, 325: 119787.
[66] Liu Y, Liu Z, Mei W, et al.Operando Monitoring Lithium-Ion Battery Temperature via Implanting Femtosecond-Laser-Inscribed Optical Fiber Sensors[J]. Measurement, 2022, 203: 111961.
[67] Withers P J, Bouman C, Carmignato S, et al.X-Ray Computed Tomography[J]. Nature Reviews Methods Primers, 2021, 1(1): 18.
[68] Zhao C, Wada T, De Andrade V, et al.Imaging of 3D Morphological Evolution of Nanoporous Silicon Anode in Lithium Ion Battery by X-Ray Nano-Tomography[J]. Nano energy, 2018, 52: 381-390.
[69] Tang F, Li D, Liu X, et al.Exploring Optimal Li Composite Electrode Anodes for Lithium Metal Batteries Through In Situ X-Ray Computed Tomography[J]. Energy Storage Materials, 2024, 72: 103746.
[70] Lu X, Bertei A, Finegan D P, et al.3D Microstructure Design of Lithium-Ion Battery Electrodes Assisted by X-Ray Nano-Computed Tomography and Modelling[J]. Nature communications, 2020, 11(1): 2079.
[71] Kodama M, Ohashi A, Adachi H, et al.Three-Dimensional Structural Measurement and Material Identification of an All-Solid-State Lithium-Ion Battery by X-Ray Nanotomography and Deep Learning[J]. Journal of Power Sources Advances, 2021, 8: 100048.
[72] Boyce A M, Martínez-Pañeda E, Wade A, et al.Cracking Predictions of Lithium-Ion Battery Electrodes by X-Ray Computed Tomography and Modelling[J]. Journal of Power Sources, 2022, 526: 231119.
[73] Hou J, Wang H, Qi L, et al.Material Parameter Analysis of Lithium-Ion Battery Based on Laboratory X-Ray Computed Tomography[J]. Journal of Power Sources, 2022, 549: 232131.
[74] Zhang Y, Gao K, Ma T, et al.Intelligent Recognition of Structural Health State of EV Lithium-Ion Battery Using Transfer Learning Based on X-Ray Computed Tomography[J]. Reliability Engineering & System Safety, 2024, 251: 110374.
[75] Rahe C, Kelly S T, Rad M N, et al.Nanoscale X-Ray Imaging of Ageing in Automotive Lithium-Ion Battery Cells[J]. Journal of power sources, 2019, 433: 126631.
[76] Sterkens W, Diaz-Romero D, Goedemé T, et al.Detection and Recognition of Batteries on X-Ray Images of Waste Electrical and Electronic Equipment Using Deep Learning[J]. Resources, Conservation and Recycling, 2021, 168: 105246.
[77] Li Y, Zhang X.Relation-Aware Graph Convolutional Network for Waste Battery Inspection Based on X-Ray Images[J]. Sustainable Energy Technologies and Assessments, 2024, 63: 103651.
[78] Heenan T M M, Finegan D P, Tjaden B, et al. 4D Nano-Tomography of Electrochemical Energy Devices Using Lab-Based X-Ray Imaging[J]. Nano Energy, 2018, 47: 556-565.
[79] Tan C, Heenan T M M, Ziesche R F, et al. Four-Dimensional Studies of Morphology Evolution in Lithium-Sulfur Batteries[J]. ACS Applied Energy Materials, 2018, 1(9): 5090-5100.
[80] Ziesche R F, Arlt T, Finegan D P, et al.4D Imaging of Lithium-Batteries Using Correlative Neutron and X-Ray Tomography With a Virtual Unrolling Technique[J]. Nature communications, 2020, 11(1): 777.
[81] Meng J, Xu L, Ma Q, et al.Modulating Crystal and Interfacial Properties by W‐Gradient Doping for Highly Stable and Long Life Li‐Rich Layered Cathodes[J]. Advanced Functional Materials, 2022, 32(19): 2113013.
[82] Zhang Y, Yin C, Qiu B, et al.Revealing Li-Ion Diffusion Kinetic Limitations in Micron-Sized Li-Rich Layered Oxides[J]. Energy Storage Materials, 2022, 53: 763-773.
[83] Lee J A, Kang H, Kim S, et al.Unveiling Degradation Mechanisms of Anode-Free Li-Metal Batteries[J]. Energy Storage Materials, 2024, 73: 103826.
[84] Khan H, Yerramilli A S, D'Oliveira A, et al. Experimental Methods in Chemical Engineering: X‐Ray Diffraction Spectroscopy—XRD[J]. The Canadian journal of chemical engineering, 2020, 98(6): 1255-1266.
[85] Liu H, Allan P K, Borkiewicz O J, et al.A Radially Accessible Tubular in Situ X-Ray Cell for Spatially Resolved Operando Scattering and Spectroscopic Studies of Electrochemical Energy Storage Devices[J]. Applied Crystallography, 2016, 49(5): 1665-1673.
[86] Borkiewicz O J, Shyam B, Wiaderek K M, et al.The AMPIX Electrochemical Cell: A Versatile Apparatus for In Situ X-Ray Scattering and Spectroscopic Measurements[J]. Applied Crystallography, 2012, 45(6): 1261-1269.
[87] Finegan D P, Vamvakeros A, Tan C, et al.Spatial Quantification of Dynamic Inter and Intra Particle Crystallographic Heterogeneities Within Lithium Ion Electrodes[J]. Nature communications, 2020, 11(1): 631.
[88] Sato K, Tamai A, Ohara K, et al.Non-Destructive Observation of Plated Lithium Distribution in a Large-Scale Automobile Li-Ion Battery Using Synchrotron X-Ray Diffraction[J]. Journal of Power Sources, 2022, 535: 231399.
[89] Liu H, Liu H, Lapidus S H, et al.Sensitivity and Limitations of Structures From X-Ray and Neutron-Based Diffraction Analyses of Transition Metal Oxide Lithium-Battery Electrodes[J]. Journal of The Electrochemical Society, 2017, 164(9): A1802.
[90] Kong X, Ren R, Zhu H, et al.Recent Advances in X-Ray Absorption Spectroscopy for Battery Applications[J]. The Journal of Physical Chemistry C, 2025.129(8): 3993-4009
[91] Gao X, Zheng X, Tsao Y, et al.All-Solid-State Lithium-Sulfur Batteries Enhanced by Redox Mediators[J]. Journal of the American Chemical Society, 2021, 143(43): 18188-18195.
[92] Xu W, Lang S, Wang K, et al. Fundamental Mechanistic Insights into the Catalytic Reactions of Li-S Redox by Co Single-Atom Electrocatalysts via Operando Methods [J]. Science Advances, 2023, 9(33): eadi5108.
[93] Jo S, Kim H, Kim S, et al.Nanoscale Projection Hard X‐ray Microscope for Operando Statistical Analysis of Chemical Heterogeneity in Lithium‐Ion Battery Cathodes[J]. Small Methods, 2025, 9(3): 2401087.
[94] Shutthanandan V, Nandasiri M, Zheng J, et al.Applications of XPS in the Characterization of Battery Materials[J]. Journal of Electron Spectroscopy and Related Phenomena, 2019, 231: 2-10.
[95] Zhong W, Tao J, Chen Y, et al.Unraveling the Evolution of Cathode-Solid Electrolyte Interface Using Operando X-Ray Photoelectron Spectroscopy[J]. Advanced Powder Materials, 2024, 3(3): 100184.
[96] Breuer O, Gofer Y, Elias Y, et al.Misuse of XPS in Analyzing Solid Polymer Electrolytes for Lithium Batteries[J]. Journal of the Electrochemical Society, 2024, 171(3): 030510.
[97] Oyakhire S T, Gong H, Cui Y, et al.An X-Ray Photoelectron Spectroscopy Primer for Solid Electrolyte Interphase Characterization in Lithium Metal Anodes[J]. ACS Energy Letters, 2022, 7(8): 2540-2546.
[98] 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.
[99] Ladpli P, Kopsaftopoulos F, Chang F K.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.
[100] 刘素贞, 陈永博, 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, 2024, 39(2): 607-616.
Liu Suzhen, Chen Yunlong, Zhang Chuang, et al.State-of-charge estimation of lithium-ion batteries based on multi-dimensional ultrasonic time-frequency features[J]. Transactions of China Electrotechnical Society, 2024, 39(2): 607-616.
[101] 张闯, 高浪涛, 刘素贞, 等. 基于超声的锂离子电池微过充循环老化特性[J]. 电工技术学报, 2024, 39(24): 7965-7978.
Zhang Chuang, Gao Langtao, Liu Suzhen, et al.Micro-overcharge cycling aging characteristics of lithium-ion batteries based on ultrasonic measurement[J]. Transactions of China Electrotechnical Society, 2024, 39(24): 7965-7978.
[102] Ke Q, Jiang S, Li W, et al.Potential of Ultrasonic Time-of-Flight and Amplitude as the Measurement for State of Charge and Physical Changings of Lithium-Ion Batteries[J]. Journal of Power Sources, 2022, 549: 232031.
[103] Liu B, Tong W, Cao Y, et al.SOC Estimation Method Based on the Ultrasonic Guided Waves Considering the Significant Effect of Charge/Discharge Rate[J]. Journal of Energy Storage, 2024, 87: 111434.
[104] Xu M, Zhang E, Wang S, et al.Dynamic Ultrasonic Response Modeling and Accurate State of Charge Estimation for Lithium Ion Batteries under Various Load Profiles and Temperatures[J]. Applied Energy, 2024, 355: 122210.
[105] Tian Y, Yang S, State of Charge Estimation of Lithium-Ion Batteries Based on Ultrasonic Guided Waves by Chirped Signal Excitation[J]. Journal of Energy Storage, 2024, 84: 110897.
[106] Wu Y, Wang Y, Yung W K C, et al. Ultrasonic Health Monitoring of Lithium-Ion Batteries[J]. Electronics, 2019, 8(7): 751.
[107] Xia J, Xie T, Guo Y, et al.Battery Status Monitoring Based on Advanced Ultrasonic Technology[C]//2024 IEEE Ultrasonics, Ferroelectrics, and Frequency Control Joint Symposium (UFFC-JS). IEEE, 2024: 1-4.
[108] Owen R E, Robinson J B, Weaving J S, et al.Operando Ultrasonic Monitoring of Lithium-Ion Battery Temperature and Behaviour at Different Cycling Rates and under Drive Cycle Conditions[J]. Journal of The Electrochemical Society, 2022, 169(4): 040563.
[109] Lin X, Khosravinia K, Hu X, et al.Lithium Plating Mechanism, Detection, and Mitigation in Lithium-Ion Batteries[J]. Progress in Energy and Combustion Science, 2021, 87: 100953.
[110] Liu Q, Du C, Shen B, et al.Understanding Undesirable Anode Lithium Plating Issues in Lithium-Ion Batteries[J]. RSC advances, 2016, 6(91): 88683-88700.
[111] Xu W, Li L, Shi F, et al.Ultrasonic Spectroscopy for In Situ Early Detection and Dynamic Monitoring of Lithium Plating in Lithium-Ion Batteries[J]. Cell Reports Physical Science, 2025, 6(4): 102507.
[112] Xie Y, Wang S, Li R, et al.Inhomogeneous Degradation Induced by Lithium Plating in a Large-Format Lithium-Ion Battery[J]. Journal of Power Sources, 2022, 542: 231753.
[113] Rowden B, Garcia-Araez N.A Review of Gas Evolution in Lithium Ion Batteries[J]. Energy Reports, 2020, 6: 10-18.
[114] Liu P, Yang L, Xiao B, et al.Revealing Lithium Battery Gas Generation for Safer Practical Applications[J]. Advanced Functional Materials, 2022, 32(47): 2208586.
[115] Liu X, Lyu Y, Gao J, et al.Non-Destructive Estimation of Internal State for Lithium-Ion Batteries by Ultrasonic Phased Array Scanning and Imaging Technologies[J]. Journal of Energy Storage, 2025, 117: 116155.
[116] Tang D, Xu C, Xu G, et al.Non-Contact Laser Ultrasound Detection of Internal Gas Defects in Lithium-Ion Batteries[J]. Sensors, 2025, 25(7): 2033.
[117] Kaden N, Schlimbach R, Rohde Garcia A, et al.A Systematic Literature Analysis on Electrolyte Filling and Wetting in Lithium-Ion Battery Production[J]. Batteries, 2023, 9(3): 164.
[118] Feiler S, Johann J, Gold L, et al.Investigating Wetting and Formation Behavior of Consumer Format Pouch Cells Utilizing Ultrasound[J]. Journal of Power Sources, 2025, 643: 236988.
[119] Hou S, Yi M, Jiang F, et al.Ultrasonic Testing-Based Method for Segmental Calibration and Quantitative Estimation of the Electrolyte Content in Lithium-Ion Batteries[J]. Measurement, 2023, 217: 113101.
[120] Wang Q, Ping P, Zhao X, et al.Thermal Runaway Caused Fire And Explosion Of Lithium Ion Battery[J]. Journal of power sources, 2012, 208: 210-224.
[121] Kong D, Lv H, Ping P, et al.A Review Of Early Warning Methods Of Thermal Runaway Of Lithium Ion Batteries[J]. Journal of Energy Storage, 2023, 64: 107073.
[122] Cheng Y, Zhao S, Shen G, et al.Real-Time Temperature Monitoring Of Lithium Batteries Based On Ultrasonic Technology[J]. ACS omega, 2024, 9(17): 19517-19524.
[123] Owen R E, Wiśniewska E, Braglia M, et al.Operando Ultrasonic Monitoring Of The Internal Temperature Of Lithium-Ion Batteries For The Detection And Prevention Of Thermal Runaway[J]. Journal of The Electrochemical Society, 2024, 171(4): 040525.
[124] Shen Y, Zou B, Zhang Z, et al.In Situ Detection Of Lithium-Ion Batteries By Ultrasonic Technologies[J]. Energy Storage Materials, 2023, 62: 102915.
[125] Grey C P, Dupré N.NMR Studies Of Cathode Materials For Lithium-Ion Rechargeable Batteries[J]. Chemical reviews, 2004, 104(10): 4493-4512.
[126] Lin H, Jin Y, Tao M, et al.Magnetic Resonance Imaging Techniques For Lithium-Ion Batteries: Principles And Applications: Dedicated To The Special Issue “Magnetic Resonance Of Electrochemical Energy Storage Materials”[J]. Magnetic Resonance Letters, 2024,4(2): 200113.
[127] Liu X, Liang Z, Xiang Y, et al.Solid‐State NMR And MRI Spectroscopy For Li/Na Batteries: Materials, Interface, And In Situ Characterization[J]. Advanced Materials, 2021, 33(50): 2005878.
[128] Svirinovsky-Arbeli A, Juelsholt M, May R, et al.Using NMR Spectroscopy to Link Structure To Function At The Li Solid Electrolyte Interphase[J]. Joule, 2024, 8(7): 1921.
[129] Lin X, Shen Y, Yu Y, et al.In Situ NMR Verification for Stacking Pressure‐Induced Lithium Deposition and Dead Lithium in Anode‐Free Lithium Metal Batteries[J]. Advanced Energy Materials, 2024, 14(14): 2303918.
[130] Mönich C, Andersson R, Hernández G, et al. Seeing the Unseen: Mg2+, Na+, and K+ Transference Numbers in Post-Li Battery Electrolytes by Electrophoretic Nuclear Magnetic Resonance[J]. Journal of the American Chemical Society, 2024, 146(16): 11105-11114.
[131] Wang E, Jónsson E, Grey C P.NMR Methodology for Measuring Dissolved O2 and Transport in Lithium-Air Batteries[J]. The Journal of Physical Chemistry C, 2023, 127(21): 10001-10011.
[132] Allen J P, O’Keefe C A, Grey C P. Quantifying Dissolved Transition Metals in Battery Electrolyte Solutions with NMR Paramagnetic Relaxation Enhancement[J]. The Journal of Physical Chemistry C, 2023, 127(20): 9509-9521.
[133] Marker K, Reeves P J, Xu C, et al.Evolution of Structure and Lithium Dynamics in LiNi_0.8Mn_0.1Co0.1O₂ (NMC811) Cathodes During Electrochemical Cycling[J]. Chemistry of Materials, 2019, 31(7): 2545-2554.
[134] Krachkovskiy S A, Foster J M, Bazak J D, et al.Operando Mapping of Li Concentration Profiles and Phase Transformations in Graphite Electrodes by Magnetic Resonance Imaging and Nuclear Magnetic Resonance Spectroscopy[J]. The Journal of Physical Chemistry C, 2018, 122(38): 21784-21791.
[135] Bazak J D, Allen J P, Krachkovskiy S A, et al.Mapping of Lithium-Ion Battery Electrolyte Transport Properties and Limiting Currents with In Situ MRI[J]. Journal of The Electrochemical Society, 2020, 167(14): 140518.
[136] Chien P H, Feng X, Tang M, et al.Li Distribution Heterogeneity in Solid Electrolyte Li₁₀GeP₂S₁₂ Upon Electrochemical Cycling Probed by ⁷Li MRI[J]. The journal of physical chemistry letters, 2018, 9(8): 1990-1998.
[137] Ilott A J, Mohammadi M, Chang H J, et al.Real-Time 3D Imaging of Microstructure Growth in Battery Cells Using Indirect MRI[J]. Proceedings of the National Academy of Sciences, 2016, 113(39): 10779-10784.
[138] Bason M G, Coussens T, Withers M, et al.Non-Invasive Current Density Imaging of Lithium-Ion Batteries[J]. Journal of Power Sources, 2022, 533: 231312.
[139] Brauchle F, Grimsmann F, von Kessel O, et al. Direct Measurement of Current Distribution in Lithium-Ion Cells by Magnetic Field Imaging[J]. Journal of Power Sources, 2021, 507: 230292.
[140] Hu Y, Iwata G Z, Mohammadi M, et al.Sensitive Magnetometry Reveals Inhomogeneities in Charge Storage and Weak Transient Internal Currents in Li-Ion Cells[J]. Proceedings of the National Academy of Sciences, 2020, 117(20): 10667-10672.
[141] Green J E, Stone D A, Foster M P, et al.Spatially Resolved Measurements of Magnetic Fields Applied to Current Distribution Problems in Batteries[J]. IEEE Transactions on Instrumentation and measurement, 2014, 64(4): 951-958.
[142] Wang H, Dai L, Mao L, et al.In Situ Detection of Lithium‐Ion Battery Pack Capacity Inconsistency Using Magnetic Field Scanning Imaging[J]. Small Methods, 2022, 6(3): 2101358.
[143] Bai X, Peng D, Chen Y, et al.Three-Dimensional Electrochemical-Magnetic-Thermal Coupling Model for Lithium-Ion Batteries and Its Application in Battery Health Monitoring and Fault Diagnosis[J]. Scientific Reports, 2024, 14(1): 10802.
[144] Tan D, Meng F, Hai C, et al.A Novel Method for Enhancing the Image Quality of Neutron Projection Image[J]. Journal of Nondestructive Evaluation, 2024, 43(2): 53.
[145] Carreon Ruiz E R, Lee J, Strobl M, et al. Revealing the Impact of Temperature in Battery Electrolytes via Wavelength-Resolved Neutron Imaging [J]. Science Advances, 2023, 9(39): eadi0586.
[146] Senyshyn A, Baran V, Mühlbauer M J, et al. Uniformity of Flat Li-Ion Batteries Studied by Diffraction and Imaging of X-Rays and Neutrons[J]. ACS applied energy materials, 2021, 4(4): 3110-3117.
[147] Heber M, Hofmann K, Hess C.Raman Diagnostics of Cathode Materials for Li-Ion Batteries Using Multi-Wavelength Excitation[J]. Batteries, 2022, 8(2): 10.
[148] Li G, Li H, Mo Y, et al.Further Identification to the SEI Film on Ag Electrode in Lithium Batteries by Surface Enhanced Raman Scattering (SERS)[J]. Journal of power sources, 2002, 104(2): 190-194.
[149] Li H, Mo Y, Pei N, et al.Surface-Enhanced Raman Scattering Study on Passivating Films of Ag Electrodes in Lithium Batteries[J]. The Journal of Physical Chemistry B, 2000, 104(35): 8477-8480.
[150] Flores E, Novák P, Berg E J.In Situ and Operando Raman Spectroscopy of Layered Transition Metal Oxides for Li-Ion Battery Cathodes[J]. Frontiers in Energy Research, 2018, 6: 82.
[151] Nonaka T, Kawaura H, Makimura Y, et al.In Situ X-Ray Raman Scattering Spectroscopy of a Graphite Electrode for Lithium-Ion Batteries[J]. Journal of Power Sources, 2019, 419: 203-207.
[152] Bagavathiappan S, Lahiri B B, Saravanan T, et al.Infrared Thermography for Condition Monitoring-A Review[J]. Infrared Physics & Technology, 2013, 60: 35-55.
[153] Stoynova A, Bonev B, Rizanov S, et al.Utilization of Infrared Thermography for Battery Performance Inspection[C]//2023 XXXII International Scientific Conference Electronics (ET). IEEE, 2023: 1-5.
[154] Liu Y, Xu S, Wang Y, et al.Non-Contact Steady-State Thermal Characterization of Lithium-Ion Battery Plates Using Infrared Thermography[J]. International Journal of Thermophysics, 2022, 43(9): 131.
[155] Giammichele L, D’Alessandro V, Falone M, et al. Thermal Behaviour Assessment and Electrical Characterisation of a Cylindrical Lithium-Ion Battery Using Infrared Thermography[J]. Applied Thermal Engineering, 2022, 205: 117974.
[156] Kim H J, Lee J H, Baek D H, et al.A Study on Thermal Performance of Batteries Using Thermal Imaging and Infrared Radiation[J]. Journal of Industrial and Engineering Chemistry, 2017, 45: 360-365.
[157] Shi F, Ross P N, Somorjai G A, et al.The Chemistry of Electrolyte Reduction on Silicon Electrodes Revealed by In Situ ATR-FTIR Spectroscopy[J]. The Journal of Physical Chemistry C, 2017, 121(27): 14476-14483.
[158] Dalla Corte D A, Gouget-Laemmel A C, Lahlil K, et al. Molecular Grafting on Silico-Electrolyte Interphase and Surface Stabilization [J]. Electrochimica Acta, 2016, 201: 70-77.
[159] Haregewoin A M, Shie T D, Lin S D, et al. An Effective In Situ DRIFTS Analysis of the Solid Electrolyte Interface in Lithium-Ion Battery [J]. ECS Transactions, 2013, 53(36): 23.
[160] Tan K, Liu H, Dai X, et al. In Situ Monitoring of Cycling Characteristics in Lithium-Ion Battery Based on a Two-Cavity Cascade Fiber-Optic Fabry-Perot Interferometer [J]. Measurement: Energy, 2024, 3: 100011.
[161] Ge X, Zhang Y, Du R, Revealing the Electrochemical-Mechanical Correspondence Between Electrode Films and 20 Ah Prismatic Li-Ion Batteries via Optical Fiber Monitoring [J]. Chemical Engineering Journal, 2024, 488: 150895.
[162] Xi J, Li J, Sun H, et al. In-Situ Monitoring of Internal Temperature and Strain of Solid-State Battery Based on Optical Fiber Sensors [J]. Sensors and Actuators A: Physical, 2022, 347: 113888.
[163] Huang J, Blanquer L A, Gervillié C, et al. Distributed Fiber Optic Sensing to Assess In-Live Temperature Imaging Inside Batteries: Rayleigh and FBGs [J]. Journal of The Electrochemical Society, 2021, 168(6): 060520.
[164] Miao Z, Li Y, Xiao X, et al. Direct Optical Fiber Monitor on Stress Evolution of the Sulfur-Based Cathodes for Lithium–Sulfur Batteries [J]. Energy & Environmental Science, 2022, 15(5): 2029-2038.
[165] Wang R, Zhang H, Liu Q, et al. Operando Monitoring of Ion Activities in Aqueous Batteries with Plasmonic Fiber-Optic Sensors [J]. Nature communications, 2022, 13(1): 547.