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面向智能化管理的数字孪生电池构建方法

杨世春 李强伟 周思达 张正杰 马源 陈飞

杨世春, 李强伟, 周思达, 等 . 面向智能化管理的数字孪生电池构建方法[J]. 北京航空航天大学学报, 2022, 48(9): 1734-1744. doi: 10.13700/j.bh.1001-5965.2022.0593
引用本文: 杨世春, 李强伟, 周思达, 等 . 面向智能化管理的数字孪生电池构建方法[J]. 北京航空航天大学学报, 2022, 48(9): 1734-1744. doi: 10.13700/j.bh.1001-5965.2022.0593
YANG Shichun, LI Qiangwei, ZHOU Sida, et al. Construction of digital twin model of lithium-ion battery for intelligent management[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(9): 1734-1744. doi: 10.13700/j.bh.1001-5965.2022.0593(in Chinese)
Citation: YANG Shichun, LI Qiangwei, ZHOU Sida, et al. Construction of digital twin model of lithium-ion battery for intelligent management[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(9): 1734-1744. doi: 10.13700/j.bh.1001-5965.2022.0593(in Chinese)

面向智能化管理的数字孪生电池构建方法

doi: 10.13700/j.bh.1001-5965.2022.0593
基金项目: 

国家自然科学基金 U1864213

详细信息
    通讯作者:

    陈飞, E-mail: cf2020@buaa.edu.cn

  • 中图分类号: U469

Construction of digital twin model of lithium-ion battery for intelligent management

Funds: 

National Natural Science Foundation of China U1864213

More Information
  • 摘要:

    动力电池在长时宽温域运行时,其使用性能、寿命和安全性随时间动态演变,存在单体性能不一致、系统容量快速衰减或内部缺陷诱发的电池热失控等问题,需要全气候、全生命周期电池精准管理技术。突破智能化管理的数字孪生技术、构建数字孪生电池为提升电池管理能力带来了新的解决方案,已逐步成为行业发展趋势之一。围绕动力电池精细化管理技术发展趋势,针对数字孪生动力电池构建需求,从系统建模与管控需求等方面分析了数字孪生电池建模的基本准则,系统性阐述多维度、多尺度、多物理场融合的数字孪生电池的构建方法,并结合团队前期研究分析了某电池数字孪生的实践案例,探索了数字孪生电池在生产设计、全生命周期管理等场景下的应用可能性,为电池管理技术发展提供思路与参考。

     

  • 图 1  数字孪生电池三大特征

    Figure 1.  Three main features of digital twin cell

    图 2  动力电池内部复杂副反应过程

    Figure 2.  Complex side reaction processes within power cell

    图 3  数字孪生模型构建6项基本准则

    Figure 3.  Six basic guidelines for digital twin model construction

    图 4  数字孪生模型五大步骤

    Figure 4.  Five steps of digital twin model

    图 5  以电化学模型为基础的数字孪生电池

    Figure 5.  Digital twin cell based on electrochemical model

    图 6  数字孪生与智能化电池管理应用

    Figure 6.  Digital twin and intelligent battery management applications

  • [1] 王亚楠, 韩雪冰, 卢兰光, 等. 电动汽车动力电池研究展望: 智能电池、智能管理与智慧能源[J]. 汽车工程, 2022, 44(4): 617-637. https://www.cnki.com.cn/Article/CJFDTOTAL-QCGC202204017.htm

    WANG Y N, HAN X B, LU L G, et al. Prospects of research on traction batteries for electric vehicles: Intelligent battery, wise management, and smart energy[J]. Automotive Engineering, 2022, 44(4): 617-637(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-QCGC202204017.htm
    [2] ZALOSH R, GANDHI P, BAROWY A. Lithium-ion energy storage battery explosion incidents[J]. Journal of Loss Prevention in the Process Industries, 2021, 72: 104560. doi: 10.1016/j.jlp.2021.104560
    [3] LI J, QIAO Z, BAO J, et al. An activity theory-based analysis approach for end-of-life management of electric vehicle batteries[J]. Resources, Conservation and Recycling, 2020, 162: 105040. doi: 10.1016/j.resconrec.2020.105040
    [4] ZHANG J, JIANG Q, PAN A Q, et al. An optimal dispatching strategy for charging and discharging of electric vehicles based on cloud-edge collaboration[C]//2021 3rd Asia Energy and Electrical Engineering Symposium (AEEES). Piscataway: IEEE Press, 2021: 827-832.
    [5] YANG S C, HE R, ZHANG Z J, et al. CHAIN: Cyber hierarchy and interactional network enabling digital solution for battery full-lifespan management[J]. Matter, 2020, 3(1): 27-41. doi: 10.1016/j.matt.2020.04.015
    [6] 陶飞, 张辰源, 张贺, 等. 未来装备探索: 数字孪生装备[J]. 计算机集成制造系统, 2022, 28(1): 1-16. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ202201001.htm

    TAO F, ZHANG C Y, ZHANG H, et al. Future equipment exploration: Digital twin equipment[J]. Computer Integrated Manufacturing Systems, 2022, 28(1): 1-16(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ202201001.htm
    [7] 张辰源, 陶飞. 数字孪生模型评价指标体系[J]. 计算机集成制造系统, 2021, 27(8): 2171-2186. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ202108001.htm

    ZHANG C Y, TAO F. Evaluation index system for digital twin model[J]. Computer Integrated Manufacturing Systems, 2021, 27(8): 2171-2186(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ202108001.htm
    [8] 朱凯, 陈健, 吕桃林, 等. 空间电源数字孪生系统[J]. 上海航天(中英文), 2021, 38(3): 197-206. https://www.cnki.com.cn/Article/CJFDTOTAL-SHHT202103022.htm

    ZHU K, CHEN J, LYU T L, et al. Digital twin system for space power-sources[J]. Aerospace Shanghai (Chinese & English), 2021, 38(3): 197-206(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-SHHT202103022.htm
    [9] 刘蔚然, 陶飞, 程江峰, 等. 数字孪生卫星: 概念、关键技术及应用[J]. 计算机集成制造系统, 2020, 26(3): 565-588. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ202003001.htm

    LIU W R, TAO F, CHENG J F, et al. Digital twin satellite: Concept, key technologies and applications[J]. Computer Integrated Manufacturing Systems, 2020, 26(3): 565-588(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ202003001.htm
    [10] 陶飞, 张贺, 戚庆林, 等. 数字孪生十问: 分析与思考[J]. 计算机集成制造系统, 2020, 26(1): 1-17. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ202001001.htm

    TAO F, ZHANG H, QI Q L, et al. Ten questions towards digital twin: Analysis and thinking[J]. Computer Integrated Manufacturing Systems, 2020, 26(1): 1-17(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ202001001.htm
    [11] 陶飞, 马昕, 胡天亮, 等. 数字孪生标准体系[J]. 计算机集成制造系统, 2019, 25(10): 2405-2418. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ201910001.htm

    TAO F, MA X, HU T L, et al. Research on digital twin standard system[J]. Computer Integrated Manufacturing Systems, 2019, 25(10): 2405-2418(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ201910001.htm
    [12] 陶飞, 刘蔚然, 张萌, 等. 数字孪生五维模型及十大领域应用[J]. 计算机集成制造系统, 2019, 25(1): 1-18. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ201901001.htm

    TAO F, LIU W R, ZHANG M, et al. Five-dimension digital twin model and its ten applications[J]. Computer Integrated Manufacturing Systems, 2019, 25(1): 1-18(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ201901001.htm
    [13] KHAYYAM H, ABAWAJY J, JAVADI B, et al. Intelligent battery energy management and control for vehicle-to-grid via cloud computing network[J]. Applied Energy, 2013, 111: 971-981.
    [14] LI W H, CUI H, NEMETH T, et al. Cloud-based health-conscious energy management of hybrid battery systems in electric vehicles with deep reinforcement learning[J]. Applied Energy, 2021, 293: 116977.
    [15] SASAKI T, UKYO Y, NOVÁK P. Memory effect in a lithium-ion battery[J]. Nature Materials, 2013, 12(6): 569-575.
    [16] LIPU M S H, HANNAN M A, KARIM T F, et al. Intelligent algorithms and control strategies for battery management system in electric vehicles: Progress, challenges and future outlook[J]. Journal of Cleaner Production, 2021, 292: 126044.
    [17] ZHANG Y, LIU H P, ZHANG Z G, et al. Cloud computing-based real-time global optimization of battery aging and energy consumption for plug-in hybrid electric vehicles[J]. Journal of Power Sources, 2020, 479: 229069.
    [18] DENG J, BAE C, MARCICKI J, et al. Safety modelling and testing of lithium-ion batteries in electrified vehicles[J]. Nature Energy, 2018, 3(4): 261-266.
    [19] HARPER G, SOMMERVILLE R, KENDRICK E, et al. Recycling lithium-ion batteries from electric vehicles[J]. Nature, 2019, 575(7781): 75-86.
    [20] SEVERSON K A, ATTIA P M, JIN N, et al. Data-driven prediction of battery cycle life before capacity degradation[J]. Nature Energy, 2019, 4(5): 383-391.
    [21] 陶飞, 张贺, 戚庆林, 等. 数字孪生模型构建理论及应用[J]. 计算机集成制造系统, 2021, 27(1): 1-15. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ202101001.htm

    TAO F, ZHANG H, QI Q L, et al. Theory of digital twin modeling and its application[J]. Computer Integrated Manufacturing Systems, 2021, 27(1): 1-15(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JSJJ202101001.htm
    [22] 卢锦玲, 颜禄涵, 腊志源, 等. 基于数字孪生与动态能效模型的综合能源系统实时优化调度策略[J/OL]. 电网技术, 2022(2022-05-06)[2022-07-06]. https://doi.org/10.13335/j.1000-3673.pst.2022.0044.

    LU J L, YAN L H, LA Z Y, et al. Real-time optimal scheduling strategy for integrated energy system based on digital twins and dynamic energy efficiency model[J]. Power System Technology, 2022(2022-05-06)[2022-07-06]. https://doi.org/10.13335/j.1000-3673.pst.2022.0044(in Chinese).
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出版历程
  • 收稿日期:  2022-07-07
  • 录用日期:  2022-08-05
  • 刊出日期:  2022-08-12

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