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退役动力锂离子电池分选方法研究综述

泰然健康网
2026-03-06 02:04

摘要:

随着电动汽车产业的迅速发展，大规模动力电池退役潮引发了广泛关注。如果无法有效地处理这些退役电池，可能会导致严重的环境污染和资源浪费。梯次利用技术可以最大化利用电池的全生命周期价值，并且可以极大地减轻回收电池所带来的环境压力。因此，在国家“30·60碳达峰-碳中和”战略背景下，推进电池梯次利用技术的发展具有重要意义。首先从电池老化机理入手，分析电池阳极和阴极老化带来的容量衰减以及内阻增加等问题；其次，介绍退役电池的处理方法，并着重对退役电池分选和重组聚类方法进行全面综述，明确它们的优缺点、适用性和评价指标；最后，针对电池梯次利用标准不完善和产业链体系商业化程度低等问题，提出相应的对策和建议。

Abstract:

With the rapid development of the electric vehicle industry, the large-scale retirement of power batteries has attracted widespread attention. Failure to effectively handle these retired batteries may lead to serious environmental pollution and resource waste. Cascade utilization technology can maximize the full life cycle value of batteries and greatly alleviate the environmental pressure caused by battery recycling. Against the background of the national "30·60 Carbon Peak-Carbon Neutrality" strategy, promoting the development of battery cascade utilization technology is of great significance. Starting with the aging mechanism of batteries, the problems of capacity decay and increased internal resistance caused by anode and cathode aging are analyzed. Secondly, the methods for handling retired batteries are introduced, with a focus on a comprehensive review of retired battery sorting and recombination clustering methods, clarifying their advantages, disadvantages, applicability, and evaluation criteria. Finally, addressing issues such as incomplete standards for battery cascade utilization and low commercialization of the industrial chain system, corresponding countermeasures and suggestions are proposed.

[1]

MARTINEZ-LASERNA E, SARASKETA-ZABALA E, SARRIA I V, et al. Technical viability of battery second life: A study from the ageing perspective[J]. IEEE Transactions on Industry Applications, 2018, 54(3): 2703-2713. doi: 10.1109/TIA.2018.2801262

[2]

HAN Xuebing, LU Languang, FENG Xuning, et al. A review on the key issues of the lithium ion battery degradation among the whole life cycle[J]. eTransportation, 2019(4): 1-8, 38.

[3]

HU X S, DENG X C, WANG F, et al. A review of second-life lithium-ion batteries for stationary energy storage applications[J]. Proceedings of the IEEE, 2022, 110(6): 735-753. doi: 10.1109/JPROC.2022.3175614

[4] 于会群, 胡哲豪, 彭道刚, 等. 退役动力电池回收及其在储能系统中梯次利用关键技术[J]. 储能科学与技术, 2023, 12(5): 1675-1685.

YU Huiqun, HU Zhehao, PENG Daogang, et al. Key technologies for retired power battery recovery and its cascade utilization in energy storage systems[J]. Energy Storage Science and Technology, 2023, 12(5): 1675-1685.

[5]

JIANG X, CHEN Y, MENG X, et al. The impact of electrode with carbon materials on safety performance of lithium-ion batteries: A review[J]. Carbon, 2022, 191: 448-470. doi: 10.1016/j.carbon.2022.02.011

[6]

AGUBRA V, JEFFREY F. Lithium-ion battery anode aging mechanisms[J]. Materials, 2013, 6(4): 1310-1325. doi: 10.3390/ma6041310

[7]

PALLAVI V, MAIRE P, NOVÁK P. A review of the features and analyses of the solid electrolyte interphase in Li-ion batteries[J]. Electrochimica Acta, 2010, 55(22): 6332-6341. doi: 10.1016/j.electacta.2010.05.072

[8]

ARORA P, WHITE R E, DOYLE M. Capacity fade mechanisms and side reactions in lithium-ion batteries[J]. Journal of the Electrochemical Society, 1998, 145(10): 3647. doi: 10.1149/1.1838857

[9]

CHRISTENSEN J, NEWMAN J. Effect of anode film resistance on the charge/discharge capacity of a lithium-ion battery[J]. Journal of the Electrochemical Society, 2003, 150(11): A1416. doi: 10.1149/1.1612501

[10]

MA R, HE J, DENG Y. Investigation and comparison of the electrochemical impedance spectroscopy and internal resistance indicators for early-stage internal short circuit detection through battery aging[J]. Journal of Energy Storage, 2022, 54: 105346. doi: 10.1016/j.est.2022.105346

[11]

LIN N, JIA Z, WANG Z, et al. Understanding the crack formation of graphite particles in cycled commercial lithium-ion batteries by focused ion beam-scanning electron microscopy[J]. Journal of Power Sources, 2017, 365: 235-239. doi: 10.1016/j.jpowsour.2017.08.045

[12] 闵越明, 张闯, 刘文杰, 等. 锂离子电池微过充循环老化特性与失效机理研究[J]. 储能科学与技术, 2024, 13(10): 3343-3356.

MIN Yueming, ZHANG Chuang, LIU Wenjie, et al. Study on aging characteristics and failure mechanism of lithium-ion battery under slight-overcharge cycling[J]. Energy Storage Science and Technology, 2024, 13(10): 3343-3356.

[13]

XIONG R, MA S, LI H, et al. Toward a safer battery management system: A critical review on diagnosis and prognosis of battery short circuit[J]. iScience, 2020, 23(4): 101010. doi: 10.1016/j.isci.2020.101010

[14]

WOHLFAHRT-MEHRENS M, VOGLER C, GARCHE J. Aging mechanisms of lithium cathode materials[J]. Journal of Power Sources, 2004, 127(1-2): 58-64. doi: 10.1016/j.jpowsour.2003.09.034

[15] 张齐. 锂离子动力电池在时频域下的电化学建模及老化诊断[D]. 哈尔滨: 哈尔滨工业大学, 2023.

ZHANG Qi. Electrochemical modeling at time domain and frequency domain and aging diagnosis for the lithium-ion power battery[D]. Harbin: Harbin Institute of Technology, 2023.

[16]

SATO N, HIRAO K, HAYASHI E, et al. Characterization of electrode materials during degradation process of Li-ion batteries[J]. Nippon Kagaku Kaishi, 2002(2): 189-194. doi: 10.1246/nikkashi.2002.189

[17]

BALAKRISHNAN P G, RAMESH R, KUMAR T P. Safety mechanisms in lithium-ion batteries[J]. Journal of Power Sources, 2006, 155(2): 401-414. doi: 10.1016/j.jpowsour.2005.12.002

[18]

LIAO Q, MU M, ZHAO S, et al. Performance assessment and classification of retired lithium ion battery from electric vehicles for energy storage[J]. International Journal of Hydrogen Energy, 2017, 42(30): 18817-18823. doi: 10.1016/j.ijhydene.2017.06.043

[19]

TIAN G, YUAN G, ALEKSANDROV A, et al. Recycling of spent lithium-ion batteries: A comprehensive review for identification of main challenges and future research trends[J]. Sustainable Energy Technologies and Assessments, 2022, 53: 102447. doi: 10.1016/j.seta.2022.102447

[20] 苑玮琦, 郭绍陶. 圆柱型覆膜锂电池圆周面凹坑检测方法研究[J]. 仪器仪表学报, 2020, 41(2): 146-156.

YUAN Weiqi, GUO Shaotao. Research on the detection method of pit on the cylindrical surface of cylindrical coated lithium battery[J]. Chinese Journal of Scientific Instrument, 2020, 41(2): 146-156.

[21]

ZHOU L, GARG A, ZHENG J, et al. Battery pack recycling challenges for the year 2030: Recommended solutions based on intelligent robotics for safe and efficient disassembly, residual energy detection, and secondary utilization[J]. Energy Storage, 2021, 3(3): e190. doi: 10.1002/est2.190

[22]

ZHANG S, TANG G. Detection of the wounds of the battery cathode based on machine vision[C]//2014 Seventh International Symposium on Computational Intelligence and Design, December 13-14, 2014, Hangzhou. IEEE, 2014, 2: 216-219.

[23]

LIU F, CHEN J, QIN D, et al. Research on appearance detection, sorting, and regrouping technology of retired batteries for electric vehicles[J]. Sustainability, 2023, 15(21): 15523. doi: 10.3390/su152115523

[24] 谭文, 文青, 段峰, 等. 基于HV & VHS的圆柱形电池曲表面缺陷视觉检测[J]. 控制工程, 2019, 26(1): 17-22.

TAN Wen, WEN Qing, DUAN Feng, et al. Research on on-line surface defect inspection of HV & VHS-based batteries[J]. Control Engineering of China, 2019, 26(1): 17-22.

[25] 赵萌, 李娜, 苑津莎, 等. 梯次利用锂电池内阻一致性评估指标[J]. 中外能源, 2018, 23(8): 86-92.

ZHAO Meng, LI Na, YUAN Jinsha, et al. Evaluation indicators for consistency of internal resistance of lithium batteries in cascade utilization[J]. Sino-Global Energy, 2018, 23(8): 86-92.

[26] 吴伟静. 电动汽车锂动力电池分选及成组技术研究[D]. 长春: 吉林大学, 2015.

WU Weijing. Research on sorting and grouping technology of lithium power batteries for electric vehicles[D]. Changchun: Jilin University, 2015.

[27] 李扬, 王军. 退役锂离子电池筛选分类方法设计与分析[J]. 电池, 2020, 50(4): 403-407.

LI Yang, WANG Jun. Design and analysis of screening and classification methods for retired Li-ion battery[J]. Battery Bimonthly, 2020, 50(4): 403-407.

[28] 李建林, 王哲, 李欣, 等. 退役动力电池梯级利用分选技术研究[J]. 太阳能学报, 2023, 44(1): 418-425.

LI Jianlin, WANG Zhe, LI Xin, et al. Research on cascade utilization and sorting technology for retired power batteries[J]. Acta Energiae Solaris Sinica, 2023, 44(1): 418-425.

[29] 巩亚栋. 锂离子电池的健康状态估计及退役分选方法研究[D]. 长沙: 中南大学, 2022.

GONG Yadong. Research on health status estimation and retirement sorting methods of lithium ion batteries[D]. Changsha: Central South University, 2022.

[30] 段双明, 王恩吉, 朱微, 等. 基于锂电池电压片段的退役电池快速筛选重组[J]. 电网技术, 2024, 48(10): 4264-4274.

DUAN Shuangming, WANG Enji, ZHU Wei, et al. Rapid screening and recombination of retired batteries based on voltage segments of lithium[J]. Power System Technology, 2024, 48(10): 4264-4274.

[31]

LI C, WANG N, LI W, et al. Regrouping and echelon utilization of retired lithium-ion batteries based on a novel support vector clustering approach[J]. IEEE Transactions on Transportation Electrification, 2022, 8(3): 3648-3658. doi: 10.1109/TTE.2022.3169208

[32] 曹学彬. 退役电池快速分选与综合评价方法研究[D]. 济南: 山东大学, 2022.

CAO Xuebin. Research on rapid sorting and comprehensive evaluation methods for retired batteries[D]. Jinan: Shandong University, 2022.

[33] 杨超, 刘征宇, 朱华炳, 等. 基于放电平台期的Wkmeans退役锂离子电池分选方法[J]. 电源技术, 2022, 46(2): 177-181.

YANG Chao, LIU Zhengyu, ZHU Huabing, et al. Wkmeans clustering method of retired lithium-ion battery based on discharge plateau period[J]. Chinese Journal of Power Sources, 2022, 46(2): 177-181.

[34]

LIN M, WU J, MENG J, et al. Screening of retired batteries with Gramian angular difference fields and ConvNeXt[J]. Engineering Applications of Artificial Intelligence, 2023, 123: 106397. doi: 10.1016/j.engappai.2023.106397

[35] 马速良, 李建林, 李雅欣, 等. 面向电池梯次利用筛选需求的定制化聚类优化方法[J]. 中国电机工程学报, 2022, 42(17): 6208-6220.

MA Suliang, LI Jianlin, LI Yaxin, et al. Customized clustering optimization method for battery reutilization screening requirements[J]. Proceedings of the CSEE, 2022, 42(17): 6208-6220.

[36]

ZHANG Y, ZHOU Z, KANG Y, et al. A quick screening approach based on fuzzy C-means algorithm for the second usage of retired lithium-ion batteries[J]. IEEE Transactions on Transportation Electrification, 2020, 7(2): 474-484.

[37]

CHEN Z, DENG Y, LI H, et al. A sorting method of retired lithium-ion batteries using the improved k-means algorithm based on the incremental capacity curve[C]//2022 IEEE Vehicle Power and Propulsion Conference(VPPC), November 1-4, 2022, Merced. IEEE, 2022: 1-6.

[38] 骆凡, 黄海宏, 王海欣. 基于短时脉冲放电与电化学阻抗谱的退役动力电池快速分选与重组方法[J]. 仪器仪表学报, 2022, 43(1): 229-238.

LUO Fan, HUANG Haihong, WANG Haixin. A fast screening and recombinant method based on short-time pulse discharge and electrochemical impedance spectroscopy for decommissioned power batteries[J]. Chinese Journal of Scientific Instrument, 2022, 43(1): 229-238.

[39]

WANG Y, HUANG H, WANG H. Rapid-regroup strategy for retired batteries based on short-time dynamic voltage and electrochemical impedance spectroscopy[J]. Journal of Energy Storage, 2023, 63: 107102. doi: 10.1016/j.est.2023.107102

[40]

LAI X, DENG C, TANG X, et al. Soft clustering of retired lithium-ion batteries for the secondary utilization using Gaussian mixture model based on electrochemical impedance spectroscopy[J]. Journal of Cleaner Production, 2022, 339: 130786. doi: 10.1016/j.jclepro.2022.130786

[41] 刘征宇, 郭乐凯, 孟辉, 等. 基于改进DBSCAN的退役动力电池分选方法[J]. 电工技术学报, 2023, 38(11): 3073-3083.

LIU Zhengyu, GUO Lekai, MENG Hui, et al. Retired power battery sorting method based on improved DBSCAN[J]. Transactions of China Electrotechnical Society, 2023, 38(11): 3073-3083.

[42]

JIANG T, SUN J, WANG T, et al. Sorting and grouping optimization method for second-use batteries considering aging mechanism[J]. Journal of Energy Storage, 2021, 44: 103264. doi: 10.1016/j.est.2021.103264

[43]

YIN H, LI Y, KANG Y, et al. A two-stage sorting method combining static and dynamic characteristics for retired lithium-ion battery echelon utilization[J]. Journal of Energy Storage, 2023, 64: 107178. doi: 10.1016/j.est.2023.107178

[44]

LAI X, HUANG Y, DENG C, et al. Sorting, regrouping, and echelon utilization of the large-scale retired lithium batteries: A critical review[J]. Renewable and Sustainable Energy Reviews, 2021, 146: 111162. doi: 10.1016/j.rser.2021.111162

[45]

MACQUEEN J. Some methods for classification and analysis of multivariate observations[C]//Proceedings of 5-th Berkeley Symposium on Mathematical Statistics and Probability/University of California Press, 1967: 281-297.

[46] 王森, 刘琛, 邢帅杰. K-means聚类算法研究综述[J]. 华东交通大学学报, 2022, 39(5): 119-126.

WANG Sen, LIU Shen, XING Shuaijie. Review on K-means clustering algorithm[J]. Journal of East China Jiaotong University, 2022, 39(5): 119-126.

[47]

GANESH A, MAGGS B M, PANIGRAHI D. Universal algorithms for clustering problems[J]. ACM Transactions on Algorithms, 2023, 19(2): 1-46.

[48] 杜辉, 王宇平, 钟俊坤, 等. 基于多层次聚类的纹理图像分割算法[J]. 华中科技大学学报, 2017, 45(9): 39-45.

DU Hui, WANG Yuping, ZHONG Junkun, et al. Texture image segmentation based on multi-level clustering[J]. Journal of Huazhong University of Science and Technology, 2017, 45(9): 39-45.

[49]

ZHANG T, RAMAKRISHNAN R, LIVNY M. BIRCH: An efficient data clustering method for very large databases[J]. ACM Sigmod Record, 1996, 25(2): 103-114. doi: 10.1145/235968.233324

[50]

GUHA S, RASTOGI R, SHIM K, et al. CURE: An efficient clustering algorithm for large databases[J]. Information Systems, 1998, 26(1): 35-58.

[51]

JOHNSON S C. Hierarchical clustering schemes[J]. Psychometrika, 1967, 32(3): 241-254. doi: 10.1007/BF02289588

[52]

ESTER M, KRIEGEL H-P, SANDER J, et al. A density-based algorithm for discovering clusters in large spatial databases with noise[C]//Proceedings of the Knowledge Discovery and Data Mining, AAAI Press, 1996, 96(34): 226-231.

[53] 王鲁, 王峰, 徐竞, 等. 基于SOM+SVM的退役锂离子电池分选[J]. 储能科学与技术, 2022, 11(11): 3623-3630.

WANG Lu, WANG Feng, XU Jing, et al. Sorting of retired lithium-ion batteries based on SOM+SVM[J]. Energy Storage Science and Technology, 2022, 11(11): 3623-3630.

[54] 郭乐凯. 基于高斯混合模型的动力电池梯次利用分选方法研究[D]. 合肥: 合肥工业大学, 2023.

GUO Lekai. Research on echelon utilization and sorting method of power battery based on Gaussian mixture model[D]. Hefei: Hefei University of Technology, 2023.

[55]

WANG N, GARG A, SU S, et al. Echelon utilization of retired power lithium-ion batteries: Challenges and prospects[J]. Batteries, 2022, 8(8): 96. doi: 10.3390/batteries8080096

[56] 杨续来, 袁帅帅, 杨文静, 等. 锂离子动力电池能量密度特性研究进展[J]. 机械工程学报, 2023, 59(6): 239-254.

YANG Xulai, YUAN Shuaishuai, YANG Wenjing, et al. Research progress on energy density of Li-ion batteries for EVs[J]. Journal of Mechanical Engineering, 2023, 59(6): 239-254.

[57] 李建林, 李雅欣, 吕超, 等. 退役动力电池梯次利用关键技术及现状分析[J]. 电力系统自动化, 2020, 44(13): 172-183.

LI Jianlin, LI Yaxin, LÜ Chao, et al. Key technologies and current situation analysis of cascade utilization of retired power batteries[J]. Automation of Electric Power Systems, 2020, 44(13): 172-183.

[58] 张大禹, 王震坡, 刘鹏, 等. 新能源汽车动力电池衰退机制与健康状态估计研究概述[J]. 机械工程学报, 2024, 60(22): 241-256.

ZHANG Dayu, WANG Zhenpo, LIU Peng, et al. Overview of research on degradation mechanism and state of health estimation for traction battery in new energy vehicles[J]. Journal of Mechanical Engineering, 2024, 60(22): 241-256.

[59] 白恺, 李娜, 范茂松, 等. 大容量梯次利用电池储能系统工程技术路线研究[J]. 华北电力技术, 2017(3): 39-45.

BAI Kai, LI Na, FAN Maosong, et al. Research on engineering technology route of large capacity cascade utilization battery energy storage system[J]. North China Electric Power, 2017(3): 39-45.

[60] 杨光, 张鹏, 钟岸, 等. 废旧锂离子动力电池的回收研究进展[J]. 广东化工, 2018, 45(5): 139-141.

YANG Guang, ZHANG Peng, ZHONG An, et al. Recovery of the technologies of recycling spent lithium-ion batteries[J]. Guangdong Chemical Industry, 2018, 45(5): 139-141.

[61] 高桂兰, 贺欣, 李亚光, 等. 废旧车用动力锂离子电池的回收利用现状[J]. 环境工程, 2017, 35(10): 135-140.

GAO Guilan, HE Xin, LI Yaguang, et al. Current status of recycling technology of spent automotive lithium-ion batteries[J]. Environmental Engineering, 2017, 35(10): 135-140.

[62] 刘倩. 欧盟动力电池梯次利用的现状和发展趋势[J]. 汽车维护与修理, 2022(7): 15-19.

LIU Qian. The current status and development trends of cascade utilization of power batteries in the European Union[J]. Auto Maintenance & Repair, 2022(7): 15-19.

[63]

ZHAO S, MA C. Research on the coordination of the power battery echelon utilization supply chain considering recycling outsourcing[J]. Journal of Cleaner Production, 2022, 358: 131922. doi: 10.1016/j.jclepro.2022.131922

[64] 戴国洪, 张道涵, 彭思敏, 等. 人工智能在动力电池健康状态预估中的研究综述[J]. 机械工程学报, 2024, 60(4): 391-408.

DAI Guohong, ZHANG Daohan, PENG Simin, et al. Overview of artificial intelligence in health prediction of power battery[J]. Journal of Mechanical Engineering, 2024, 60(4): 391-408.

[65] 周媛, 信天, 王鑫, 等. 动力电池梯次利用标准化现状探讨[J]. 电池, 2021, 51(5): 534-537.

ZHOU Yuan, XIN Tian, WANG Xin, et al. Discussion on current situation of power battery echelon utilization standardization[J]. Battery Bimonthly, 2021, 51(5): 534-537.