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Cited by 57Advanced Battery Technologies ResearchExtraction and Separation ProcessesAdvancements in Battery Materials

A degradation-based sorting method for lithium-ion battery reuse

Open access
Chen, Hao, Shen, Julia·2017·PLOS ONE
DOI 10.1371/journal.pone.0185922PMC PMC5638292
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Abstract

In a world where millions of people are dependent on batteries to provide them with convenient and portable energy, battery recycling is of the utmost importance. In this paper, we developed a new method to sort 18650 Lithium-ion batteries in large quantities and in real time for harvesting used cells with enough capacity for battery reuse. Internal resistance and capacity tests were conducted as a basis for comparison with a novel degradation-based method based on X-ray radiographic scanning and digital image contrast computation. The test results indicate that the sorting accuracy of the test cells is about 79% and the execution time of our algorithm is at a level of 200 milliseconds, making our method a potential real-time solution for reusing the remaining capacity in good used cells.

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References 31 · Cited by 57

Research works printed but not linked: 24

  1. [1]Pillot, C. Battery market development for consumer electronics, automotive, and industrial: materials requirements and trends. 5th Israeli Power Sources Conference. May 21st, Herzelia, Israel, 2015; 1–40.
  2. [2]Solutions UR. Going green with Umicore—a global metals and materials company that adopts a dedicated professional approach to battery recycling with its VAL'EAS process. Batteries International. 2004; 60: 42– 44.
  3. [3]Castillo S, Ansart F, Laberty-Robert C, Portal J. Advances in the recovering of spent lithium batery compounds. Journal of Power Sources. 2002; 112(1): 247– 254.
  4. [4]Contestabile M, Panero S, Scrosati B. A laboratory-scale lithium-ion battery recycling process. Journal of Power Sources. 2001; 92(1–2): 65– 69.
  5. [5]Nan J, Han D, Zuo X. Recovery of metal values from spent lithium-ion batteries with chemical deposition and solvent extraction. Journal of Power Sources. 2005; 152: 278– 284.
  6. [6]Wang R, Lin Y, Wu S. A novel recovery process of metal values from the cathode active materials of the lithium-ion secondary batteries. Hydrometallurgy. 2009; 99(3–4): 194– 201.
  7. [7]Lain MJ. Recycling of Lithium ion cells and batteries. Journal of Power Sources. 2001; 97: 736– 738.
  8. [9]Saha, B., Poll, S., Goebel, K., and Christophersen, J. An integrated approach to battery health monitoring using Bayesian regression and state estimation. IEEE Autotestcon. 2007; 646–653.
  9. [10]Liu D, Luo Y, Liu J, Peng Y, Guo L, Pecht M. Lithium-ion battery remaining useful life estimation based on fusion nonlinear degradation AR model and RPF algorithm. Neural Computing and Applications. 2014; 25(3): 557– 572.
  10. [11]Liu B, Yin S, Xu J. Integrated computation mmodel of lithium-ion battery subject to nail peneration. Applied Energy. 2016; 183(2016): 278– 289.
  11. [12]Xu J, Liu B, Hu D. State of charge dependent mechanical integrity behavior of 18650 Lithium-ion batteries. Scientific Reports. 2016; 6(2016): 21829. 26911922 PMC4766446
  12. [13]Kenderian S, Djordjevic BB, Green RE. Point and line source laser generation of ultrasound for inspection of internal and surface flaws in rail and structural materials. Research in Nondestructive Evaluation. 2001; 13(4): 189– 200.
  13. [14]Dang C, Schmerr LW, Sedov A. Modeling and measuring all the elements of an ultrasonic nondestructive evaluation system I: modeling foundations. Research in Nondestructive Evaluation. 2002; 14(3): 141– 176.
  14. [15]Wooh SC, Wang JY. Nondestructive characterization of planar defects using laser-generated ultrasonic shear waves. Research in Nondestructive Evaluation. 2001; 13(4): 215– 230.
  15. [16]Kim BH, Heedai K, Taehyo P. Nondestructive damage evaluation of plates using the multi-resolution analysis of two-dimensional Haar wavelet. Journal of Sound and Vibration. 2006; 292(1–2): 82– 104.
  16. [17]Lemaitre J. A Course on Damage Mechanics. Springer: 1996.
  17. [18]Chen H, Shi X, He Q, Mao JH, Liu Y, Kang H, Shen J. A multiresolution investigataion of fatigue damage of aluminum alloys at micrometer level. International Journal of Damage Mechanics. 2017; 26(2): 192– 209.
  18. [19]Shen J, Mao Y, Reyes G, Chow CL, Boileau J, Su J, et al A multiresolution transformation rule of material defects. International Journal of Damage Mechanics. 2009; 18(8): 739– 758.
  19. [20]Shen J, Boileau J, Mao J, Chow CL. Material Damage Estimated via Linking Micro/Macroscale Defects to Macroscopic Mechanical Properties. International Journal of Damage Mechanics. 2014; 23(4): 537– 566.
  20. [21]Shen J, Vela D, Song K, Singh A, LaFreniere B, Chen H. GPU/CPU Parallel Computation of Material Damage. Engineering with Computers. 2014; 31(3): 647– 660.
  21. [28]Peli E. Contrast in complex images. Journal of the Optical Society of America. 1990; 7(10): 2032– 2040. 2231113
  22. [29]Singal AG, Mukherjee A, Elmunzer BJ, Higins PDR, Lok AS, Zhu J, et al Machine learning algorithms outperform conventional regression models in predicting development of hepatocellular carclinoma. The American Journal of Gastroenterology. 2013; 108: 1723– 1730. doi: 10.1038/ajg.2013.332 24169273 PMC4610387 · DOI
  23. [30]Apte C, Damerau F, Weiss SM. Automated learning of decision rules for text categorization. ACM Transactions on Information Systems. 1994; 12(3): 233– 251.
  24. [31]Cortes C, Vapnik V. Support-vector networks. Machine Learning. 1995; 20(3): 273– 297.

Authors
Chen, H., & Shen, J.
Affiliations
Shanghai University of Engineering Science (CN)
Corresponding author
Shen, Julia
ORCID
Venue
PLOS ONE
Publisher
Public Library of Science (PLoS)
Published
2017-10-12
Volume
12
Issue
10
Pages
e0185922
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0185922
PMC
PMC5638292
OpenAlex
W2762383420
Cited by
57
References
31
Citations by year
2026: 4 · 2025: 2 · 2024: 8 · 2023: 12 · 2022: 7 · 2021: 9 · 2020: 10 · 2019: 4 · 2018: 1
FWCI
2.60
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
National Science Foundation (Division of Industrial Innovation and Partnerships(IIP)-1445355)
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
  • Physical Sciences › Engineering › Mechanical Engineering › Extraction and Separation Processes
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
Keywords
battery sorting, battery degradation, internal resistance, battery capacity, 18650 cells, battery recycling, real-time sorting
MeSH terms
Lithium, Electric Power Supplies, Recycling

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