IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v262y2020ics0306261920300301.html
   My bibliography  Save this article

Multiphysical field measurement and fusion for battery electric-thermal-contour performance analysis

Author

Listed:
  • Li, Xiaoyu
  • Zhang, Zuguang
  • Wang, Wenhui
  • Tian, Yong
  • Li, Dong
  • Tian, Jindong

Abstract

A battery often exhibits a coupling change in electric, thermal and battery surface topography during operation, especially under abuse conditions. Analysis of the coupling relationship among the multiphysical field parameters is necessary for battery physical structure optimization, failure mechanism analysis and fault prognostics method design. However, there are few multiphysical data acquisition and analysis systems for batteries at present. In this context, a novel battery multiphysical field measurement system with a data fusion model for battery performance analysis is proposed in this paper. The measurement system consists of a three-dimensional scanner, an infrared thermal imager, and an integrated battery charger and discharger. In order to accurately acquire the relationship between the battery surface topography and the battery surface temperature, a data fusion model is proposed, and a joint calibration method is accordingly introduced for the parameter identification of the data fusion model. The results show that the multiphysical measurement system can achieve the position matching deviation of 0.19 mm with high resolution and high data acquisition speed. The functionality of the multiphysical measurement system and the data fusion model are verified by the experimental results of different tests, including a 1 C rate charging/discharging test, a high rate charging/discharging test, and two battery abuse operation tests. It will provide key tools for battery thermal runaway mechanism analysis and battery fault diagnosis method design.

Suggested Citation

  • Li, Xiaoyu & Zhang, Zuguang & Wang, Wenhui & Tian, Yong & Li, Dong & Tian, Jindong, 2020. "Multiphysical field measurement and fusion for battery electric-thermal-contour performance analysis," Applied Energy, Elsevier, vol. 262(C).
    • Handle: RePEc:eee:appene:v:262:y:2020:i:c:s0306261920300301
    DOI: 10.1016/j.apenergy.2020.114518
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261920300301
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2020.114518?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Li, Xiaoyu & Wang, Zhenpo & Zhang, Lei, 2019. "Co-estimation of capacity and state-of-charge for lithium-ion batteries in electric vehicles," Energy, Elsevier, vol. 174(C), pages 33-44.
    2. Chen, Zeyu & Xiong, Rui & Lu, Jiahuan & Li, Xinggang, 2018. "Temperature rise prediction of lithium-ion battery suffering external short circuit for all-climate electric vehicles application," Applied Energy, Elsevier, vol. 213(C), pages 375-383.
    3. Li, Junqiu & Sun, Danni & Jin, Xin & Shi, Wentong & Sun, Chao, 2019. "Lithium-ion battery overcharging thermal characteristics analysis and an impedance-based electro-thermal coupled model simulation," Applied Energy, Elsevier, vol. 254(C).
    4. Feng, Xuning & He, Xiangming & Ouyang, Minggao & Lu, Languang & Wu, Peng & Kulp, Christian & Prasser, Stefan, 2015. "Thermal runaway propagation model for designing a safer battery pack with 25Ah LiNixCoyMnzO2 large format lithium ion battery," Applied Energy, Elsevier, vol. 154(C), pages 74-91.
    5. Noelle, Daniel J. & Wang, Meng & Le, Anh V. & Shi, Yang & Qiao, Yu, 2018. "Internal resistance and polarization dynamics of lithium-ion batteries upon internal shorting," Applied Energy, Elsevier, vol. 212(C), pages 796-808.
    6. Tang, Xiaopeng & Zou, Changfu & Yao, Ke & Lu, Jingyi & Xia, Yongxiao & Gao, Furong, 2019. "Aging trajectory prediction for lithium-ion batteries via model migration and Bayesian Monte Carlo method," Applied Energy, Elsevier, vol. 254(C).
    7. Zhu, Xiaoqing & Wang, Zhenpo & Wang, Yituo & Wang, Hsin & Wang, Cong & Tong, Lei & Yi, Mi, 2019. "Overcharge investigation of large format lithium-ion pouch cells with Li(Ni0.6Co0.2Mn0.2)O2 cathode for electric vehicles: Thermal runaway features and safety management method," Energy, Elsevier, vol. 169(C), pages 868-880.
    8. Liu, Binghe & Yin, Sha & Xu, Jun, 2016. "Integrated computation model of lithium-ion battery subject to nail penetration," Applied Energy, Elsevier, vol. 183(C), pages 278-289.
    9. Lin, Cheng & Mu, Hao & Xiong, Rui & Cao, Jiayi, 2017. "Multi-model probabilities based state fusion estimation method of lithium-ion battery for electric vehicles: State-of-energy," Applied Energy, Elsevier, vol. 194(C), pages 560-568.
    10. Saw, L.H. & Ye, Y. & Tay, A.A.O., 2014. "Electro-thermal analysis and integration issues of lithium ion battery for electric vehicles," Applied Energy, Elsevier, vol. 131(C), pages 97-107.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li, Xiaoyu & Huang, Zhijia & Tian, Jindong & Tian, Yong, 2021. "State-of-charge estimation tolerant of battery aging based on a physics-based model and an adaptive cubature Kalman filter," Energy, Elsevier, vol. 220(C).
    2. Huang, Zhiliang & Wang, Huaixing & Yang, Tongguang & Chen, Zeye & Li, Hangyang & Chen, Jie & Wu, Shengben, 2023. "An efficient multi-state evaluation approach for lithium-ion pouch cells under dynamic conditions in pressure/current/temperature," Applied Energy, Elsevier, vol. 340(C).
    3. Chen, Haosen & Fan, Jinbao & Zhang, Mingliang & Feng, Xiaolong & Zhong, Ximing & He, Jianchao & Ai, Shigang, 2023. "Mechanism of inhomogeneous deformation and equal-stiffness design of large-format prismatic lithium-ion batteries," Applied Energy, Elsevier, vol. 332(C).
    4. Xia, Quan & Ren, Yi & Wang, Zili & Yang, Dezhen & Yan, Peiyu & Wu, Zeyu & Sun, Bo & Feng, Qiang & Qian, Cheng, 2023. "Safety risk assessment method for thermal abuse of lithium-ion battery pack based on multiphysics simulation and improved bisection method," Energy, Elsevier, vol. 264(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ren, Dongsheng & Liu, Xiang & Feng, Xuning & Lu, Languang & Ouyang, Minggao & Li, Jianqiu & He, Xiangming, 2018. "Model-based thermal runaway prediction of lithium-ion batteries from kinetics analysis of cell components," Applied Energy, Elsevier, vol. 228(C), pages 633-644.
    2. Li, Junqiu & Sun, Danni & Jin, Xin & Shi, Wentong & Sun, Chao, 2019. "Lithium-ion battery overcharging thermal characteristics analysis and an impedance-based electro-thermal coupled model simulation," Applied Energy, Elsevier, vol. 254(C).
    3. Hong, Jichao & Wang, Zhenpo & Qu, Changhui & Zhou, Yangjie & Shan, Tongxin & Zhang, Jinghan & Hou, Yankai, 2022. "Investigation on overcharge-caused thermal runaway of lithium-ion batteries in real-world electric vehicles," Applied Energy, Elsevier, vol. 321(C).
    4. Chen, Zeyu & Zhang, Bo & Xiong, Rui & Shen, Weixiang & Yu, Quanqing, 2021. "Electro-thermal coupling model of lithium-ion batteries under external short circuit," Applied Energy, Elsevier, vol. 293(C).
    5. An, Zhoujian & Zhao, Yabing & Du, Xiaoze & Shi, Tianlu & Zhang, Dong, 2023. "Experimental research on thermal-electrical behavior and mechanism during external short circuit for LiFePO4 Li-ion battery," Applied Energy, Elsevier, vol. 332(C).
    6. Zhang, Liwen & Zhao, Peng & Xu, Meng & Wang, Xia, 2020. "Computational identification of the safety regime of Li-ion battery thermal runaway," Applied Energy, Elsevier, vol. 261(C).
    7. Liu, Lishuo & Feng, Xuning & Zhang, Mingxuan & Lu, Languang & Han, Xuebing & He, Xiangming & Ouyang, Minggao, 2020. "Comparative study on substitute triggering approaches for internal short circuit in lithium-ion batteries," Applied Energy, Elsevier, vol. 259(C).
    8. Xu, Dongxin & Pan, Yongjun & Zhang, Xiaoxi & Dai, Wei & Liu, Binghe & Shuai, Qi, 2024. "Data-driven modelling and evaluation of a battery-pack system’s mechanical safety against bottom cone impact," Energy, Elsevier, vol. 290(C).
    9. Ren, Dongsheng & Feng, Xuning & Lu, Languang & He, Xiangming & Ouyang, Minggao, 2019. "Overcharge behaviors and failure mechanism of lithium-ion batteries under different test conditions," Applied Energy, Elsevier, vol. 250(C), pages 323-332.
    10. Huang, Zonghou & Zhao, Chunpeng & Li, Huang & Peng, Wen & Zhang, Zheng & Wang, Qingsong, 2020. "Experimental study on thermal runaway and its propagation in the large format lithium ion battery module with two electrical connection modes," Energy, Elsevier, vol. 205(C).
    11. Huang, Zhiliang & Wang, Huaixing & Yang, Tongguang & Chen, Zeye & Li, Hangyang & Chen, Jie & Wu, Shengben, 2023. "An efficient multi-state evaluation approach for lithium-ion pouch cells under dynamic conditions in pressure/current/temperature," Applied Energy, Elsevier, vol. 340(C).
    12. Chen, Haodong & Kalamaras, Evangelos & Abaza, Ahmed & Tripathy, Yashraj & Page, Jason & Barai, Anup, 2023. "Comprehensive analysis of thermal runaway and rupture of lithium-ion batteries under mechanical abuse conditions," Applied Energy, Elsevier, vol. 349(C).
    13. Charles Mohamed Hamisi & Pius Victor Chombo & Yossapong Laoonual & Somchai Wongwises, 2022. "An Electrothermal Model to Predict Thermal Characteristics of Lithium-Ion Battery under Overcharge Condition," Energies, MDPI, vol. 15(6), pages 1-16, March.
    14. Gandoman, Foad H. & Jaguemont, Joris & Goutam, Shovon & Gopalakrishnan, Rahul & Firouz, Yousef & Kalogiannis, Theodoros & Omar, Noshin & Van Mierlo, Joeri, 2019. "Concept of reliability and safety assessment of lithium-ion batteries in electric vehicles: Basics, progress, and challenges," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    15. Hong, Jichao & Wang, Zhenpo & Chen, Wen & Yao, Yongtao, 2019. "Synchronous multi-parameter prediction of battery systems on electric vehicles using long short-term memory networks," Applied Energy, Elsevier, vol. 254(C).
    16. Kurucan, Mehmet & Özbaltan, Mete & Yetgin, Zeki & Alkaya, Alkan, 2024. "Applications of artificial neural network based battery management systems: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    17. Liu, Fen & Wang, Jianfeng & Yang, Na & Wang, Fuqiang & Chen, Yaping & Lu, Dongchen & Liu, Hui & Du, Qian & Ren, Xutong & Shi, Mengyu, 2022. "Experimental study on the alleviation of thermal runaway propagation from an overcharged lithium-ion battery module using different thermal insulation layers," Energy, Elsevier, vol. 257(C).
    18. Zhang, Lei & Huang, Lvwei & Zhang, Zhaosheng & Wang, Zhenpo & Dorrell, David D., 2022. "Degradation characteristics investigation for lithium-ion cells with NCA cathode during overcharging," Applied Energy, Elsevier, vol. 327(C).
    19. Huang, Zonghou & Liu, Jialong & Zhai, Hongju & Wang, Qingsong, 2021. "Experimental investigation on the characteristics of thermal runaway and its propagation of large-format lithium ion batteries under overcharging and overheating conditions," Energy, Elsevier, vol. 233(C).
    20. Feng, Xuning & Zheng, Siqi & Ren, Dongsheng & He, Xiangming & Wang, Li & Cui, Hao & Liu, Xiang & Jin, Changyong & Zhang, Fangshu & Xu, Chengshan & Hsu, Hungjen & Gao, Shang & Chen, Tianyu & Li, Yalun , 2019. "Investigating the thermal runaway mechanisms of lithium-ion batteries based on thermal analysis database," Applied Energy, Elsevier, vol. 246(C), pages 53-64.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:262:y:2020:i:c:s0306261920300301. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.