The Transactions of the Korean Institute of Power Electronics (전력전자학회논문지)

The Korean Institute of Power Electronics (전력전자학회)
권호 표지
DOI QR코드

DOI QR Code

Z-score Based Abnormal Detection for Stable Operation of the Series/Parallel-cell Configured Battery Pack

직병렬조합 배터리팩의 안전운용을 위한 Z-score 기반 이상 동작 검출 방법

  • Kang, Deokhun (Dept. of Electrical Engineering, Chungnam National University) ;
  • Lee, Pyeong-Yeon (Dept. of Electrical Engineering, Chungnam National University) ;
  • Kim, Deokhan (Dept. of Electrical Engineering, Chungnam National University) ;
  • Kim, Seung-Keun (Plant Engineering Team, Production Development Division, Automotive, Hyundai Motor Group) ;
  • Kim, Jonghoon (Dept. of Electrical Engineering, Chungnam National University)
  • Received : 2021.05.03
  • Accepted : 2021.08.05
  • Published : 2021.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

Lithium-ion batteries have been designed and used as battery packs with series and parallel combinations that are suitable for use. However, due to its internal electrochemical properties, producing the battery's condition at the same value is impossible for individual cells. In addition, the management of characteristic deviations between individual cells is essential for the safe and efficient use of batteries as aging progresses with the use of batteries. In this work, we propose a method to manage deviation properties and detect abnormal behavior in the configuration of a combined battery pack of these multiple battery cells. The proposed method can separate and detect probabilistic low-frequency information according to statistical information based on Z-score. The verification of the proposed algorithm was validated using experimental results from 10S3P battery packs, and the implemented algorithm based on Z-score was validated as a way to effectively manage multiple individual cell information.

Keywords

Acknowledgement

본 연구는 산업통상자원부(MOTIE)와 산업기술평가관리원(KEIT) 지원을 받아 수행한 연구과제(No. 20011626) 및 한국전력공사 연구비(R21XO01-3) 지원을 받아 수행한 연구 결과입니다.

References

  1. Y. Wang, B. Liu, Q. Li, S. Cartmell, S. Ferrara, Z. D. Deng, and J. Xiao, "Lithium and lithiumion batteries for applications in microelectronic devices: A review," Journal of Power Sources, Vol. 286, pp. 330-345, 2015. https://doi.org/10.1016/j.jpowsour.2015.03.164
  2. Z. Liao, S. Zhang, K. Li, G. Zhang, and T. G. Habetler, "A survey of methods for monitoring and detecting thermal runaway of lithium-ion batteries," Journal of Power Sources, Vol. 436, 226879, 2019. https://doi.org/10.1016/j.jpowsour.2019.226879
  3. S. Wang, L. Shang, Z. Li, H. Deng, and J. Li, "Online dynamic equalization adjustment of high-power lithium-ion battery packs based on the state of balance estimation," Applied Energy, Vol. 166, pp. 44-58, 2016. https://doi.org/10.1016/j.apenergy.2016.01.013
  4. H. Heimes, A. Kampker, C. Lienemann, M. Locke, and C. Offermanns, "Lithium-ion battery cell production process," VDMA Battery Production, 2019.
  5. R. Xiong, L. Li, and J. Tian, "Towards a smarter battery management system: A critical review on battery state of health monitoring methods," Journal of Power Sources, Vol. 405, pp. 18-29, 2018. https://doi.org/10.1016/j.jpowsour.2018.10.019
  6. S. Wang, C. Fernandez, C. Zou, C. Yu, L. Chen, and L. Zhang, "A comprehensive working state monitoring method for power battery packs considering state of balance and aging correction," Energy, Vol. 171, pp. 444-455, 2019. https://doi.org/10.1016/j.energy.2019.01.020
  7. U. K. Das, P. Shrivastava, K. S. Tey, M. Y. I. B. Idris, S. Mekhilef, E. Jamei, M. Seyedmahmoudian, and A. Stojcevski, "Advancement of lithium-ion battery cells voltage equalization techniques: A review," Renewable and Sustainable Energy Reviews, Vol. 134, 110227, 2020. https://doi.org/10.1016/j.rser.2020.110227
  8. K. Liu, K. Li, Q. Peng, and C. Zhang, "Abrief review on key technologies in the battery management system of electric vehicles," Frontiers of Mechanical Engineering, Vol. 14, pp. 47-64, 2019. https://doi.org/10.1007/s11465-018-0516-8
  9. X. Hu, F. Feng, K. Liu, L. Zhang, J. Xie, and B. Liu, "State estimation for advanced battery management: Key challenges and future trends," Renewable and Sustainable Energy Reviews, Vol. 114, 109334, 2019. https://doi.org/10.1016/j.rser.2019.109334
  10. N. Williard, W. He, C. Hendricks, and M. Pecht, "Lessons learned from the 787 dreamliner issue on lithium-ion battery reliability," Energies, Vol. 6, pp. 4682-4695, 2013. https://doi.org/10.3390/en6094682
  11. S. Abada, G. Marlair, A. Lecocq, M. Petit, V. Sauvant-Moynot, and F. Huet, "Safety focused modeling of lithium-ion batteries: A review," Journal of Power Sources, Vol. 306, pp. 178-192, 2016. https://doi.org/10.1016/j.jpowsour.2015.11.100
  12. L. Kong, C. Li, J. Jiang, and M. G. Pecht, "Li-ion battery fire hazards and safety strategies," Energies, Vol. 11, 2191, 2018. https://doi.org/10.3390/en11092191
  13. Q. Wang, B. Mao, S. I. Stoliarov, and J. Sun, "A review of lithium ion battery failure mechanisms and fire prevention strategies," Progress in Energy and Combustion Science, Vol. 73, pp. 95-131, 2019. https://doi.org/10.1016/j.pecs.2019.03.002
  14. Z. Liao, S. Zhang, K. Li, G. Zhang, and T. G. Habetler, "A survey of methods for monitoring and detecting thermal runaway of lithium-ion batteries," Journal of Power Sources, Vol. 436, 226879, 2019. https://doi.org/10.1016/j.jpowsour.2019.226879
  15. X. Feng, S. Zheng, D. Ren, X. He, L. Wang, H. Cui, X. Liu, C. Jin, F. Zhang, C. Xu, H. Hsu, S. Gao, T. Chen, Y. Li, T. Wang, H. Wang, M. Li, and M. Ouyang, "Investigating the thermal runaway mechanisms of lithium-ion batteries based on thermal analysis database," Applied Energy, Vol. 246, pp. 53-64, 2019. https://doi.org/10.1016/j.apenergy.2019.04.009
  16. X. Feng, D. Ren, X. He, and M. Ouyang, "Mitigating thermal runaway of lithium-ion batteries," Joule, Vol. 4, pp. 743-770, 2020. https://doi.org/10.1016/j.joule.2020.02.010
  17. Y. Kang, B. Duan, Z. Zhou, Y. Shangb, and C. Zhang, "A multi-fault diagnostic method based on an interleaved voltage measurement topology for series connected battery packs," Journal of Power Sources, Vol. 417, pp. 132-144, 2019. https://doi.org/10.1016/j.jpowsour.2019.01.058
  18. X. Lai, C. Jin, W. Yi, X. Han, X. Feng, Y. Zheng, and M. Ouyang, "Mechanism, modeling, detection, and prevention of the internal short circuit in lithium-ion batteries: Recent advances and perspectives," Energy Storage Materials, Vol. 35, pp. 470-499, 2021. https://doi.org/10.1016/j.ensm.2020.11.026
  19. S. Dey, Z. A. Biron, S. Tatipamula, N. Das, S. Mohon, B. Ayalew, and P. Pisu, "Model-based real-time thermal fault diagnosis of Lithium-ion batteries," Control Engineering Practice, Vol. 56, pp. 37-48, 2016. https://doi.org/10.1016/j.conengprac.2016.08.002
  20. Z. Chen, K. Xu, J. Wei, and G. Dong, "Voltage fault detection for lithium-ion battery pack using local outlier factor," Measurement, Vol. 146, pp. 554-556, 2019.
  21. A. Naha, A. Khandelwal, S. Agarwal, P. Tagade, K. S. Hariharan, A. Kaushik, A. Yadu, S. M. Kolake, S. Han, B. Oh, "Internal short circuit detection in Li-ion batteries using supervised machine learning," Scientific Reports, Vol. 10, 1301, 2020. https://doi.org/10.1038/s41598-020-58021-7
  22. Y. Kang, B. Duan, Z. Zhou, Y. Shang, and C. Zhang, "Online multi-fault detection and diagnosis for battery packs in electric vehicles," Applied Energy, Vol. 259, 114170, 2020. https://doi.org/10.1016/j.apenergy.2019.114170
  23. X. Hu, K. Zhang, K. Liu, X. Lin, S. Dey, and S. Onori, "Advanced fault diagnosis for lithium-ion battery systems: A review of fault mechanisms, fault features, and diagnosis procedures," IEEE Industrial Electronics Magazine, Vol. 14, pp. 65-91, 2020. https://doi.org/10.1109/mie.2020.2964814
  24. Y. Shang, G. Lu, Y. Kang, Z. Zhou, B. Duan, and C. Zhang, "A multi-fault diagnosis method based on modified sample entropy for lithium-ion battery strings," Journal of Power Sources, Vol. 446, 227275, 2019.