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@ARTICLE{Yang:1024565,
      author       = {Yang, Sijia and Zhang, Caiping and Jiang, Jiuchun and
                      Zhang, Weige and Chen, Haoze and Jiang, Yan and Sauer, Dirk
                      Uwe and Li, Weihan},
      title        = {{F}ast screening of lithium-ion batteries for second use
                      with pack-level testing and machine learning},
      journal      = {eTransportation},
      volume       = {17},
      issn         = {2590-1168},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier},
      reportid     = {FZJ-2024-02241},
      pages        = {100255 -},
      year         = {2023},
      abstract     = {Fast and accurate screening of retired lithium-ion
                      batteries is critical to an efficient and reliable second
                      use with improved performance consistency, contributing to
                      the sustainability of renewable energy sources. However,
                      time-consuming testing, representative criteria extraction,
                      and large module-to-module inconsistencies at the end of
                      first life all pose great challenges for fast screening.
                      This paper proposes a fast screening approach with
                      pack-level testing and machine learning to evaluate and
                      classify module-level aging, where disassembly of the
                      battery pack and individual testing of modules are not
                      required. Dynamic characteristic-based criteria are designed
                      to extract the comprehensive performance of the retired
                      modules, making the approach applicable for battery packs
                      with module state-of-charge inconsistencies up to $30\%.$
                      Adaptive affinity propagation clustering is utilized to
                      classify the modules and further accelerate the screening
                      progress. The proposed approach is implemented and validated
                      by conducting pack-level and module-level experiments with a
                      retired battery pack consisting of 95 modules connected in
                      series. The screening time is reduced by at least $50\%$
                      compared with approaches that require module-level testing.
                      Reasonable static performance consistency and better dynamic
                      performance consistency, as well as higher screening
                      stability, are achieved, with average overall performance
                      improvements of $18.94\%,$ $4.83\%$ and $34.41\%$ compared
                      with the three benchmarks, respectively. Its adaptability to
                      a larger current rate shows promise for large-scale
                      applications in second-use screening.},
      cin          = {IEK-12},
      ddc          = {400},
      cid          = {I:(DE-Juel1)IEK-12-20141217},
      pnm          = {1223 - Batteries in Application (POF4-122) / BMBF 03XP0334
                      - Model2Life- Modellbasierte Systemauslegung für
                      2nd-Life-Nutzungsszenarien von mobilen Batteriesystemen
                      (03XP0334)},
      pid          = {G:(DE-HGF)POF4-1223 / G:(BMBF)03XP0334},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001014614600001},
      doi          = {10.1016/j.etran.2023.100255},
      url          = {https://juser.fz-juelich.de/record/1024565},
}