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@ARTICLE{Barbers:1023005,
      author       = {Barbers, Elias and Hust, Friedrich Emanuel and Hildenbrand,
                      Felix Emil Arthur and Frie, Fabian and Quade, Katharina
                      Lilith and Bihn, Stephan and Sauer, Dirk Uwe and Dechent,
                      Philipp},
      title        = {{E}xploring the effects of cell-to-cell variability on
                      battery aging through stochastic simulation techniques},
      journal      = {Journal of energy storage},
      volume       = {84},
      number       = {Part A},
      issn         = {2352-152X},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier},
      reportid     = {FZJ-2024-01591},
      pages        = {110851},
      year         = {2024},
      abstract     = {This work introduces a comprehensive modeling framework
                      designed to simulate the electrical, thermal, and aging
                      behavior of battery cells connected in various parallel and
                      series configurations. By utilizing Monte Carlo simulation
                      techniques, the framework is used to investigate the
                      inherent variability in cell attributes, including initial
                      capacity, aging rate, and application profiles. Besides the
                      estimation of expected battery life, this simulation
                      environment enables the detailed investigation of failure
                      distributions across different cell configurations and
                      intensities of parameter variations. Results obtained from
                      these simulations can be used, as an example, in the context
                      of the automotive industry, where the insights of simulation
                      in understanding the inherent variability of the aging
                      process are particularly vital. As electric vehicles become
                      more prevalent, understanding the performance and longevity
                      of battery packs under various conditions is essential for
                      effective design and management strategies, optimizing
                      vehicle range, safety, and cost-effectiveness also on a
                      fleet-level. Moreover, the ability to investigate failure
                      distributions provides invaluable information for improving
                      battery reliability and safety, key factors in the consumer
                      acceptance of electric vehicles. Ultimately, the simulation
                      environment provides a powerful tool for designing and
                      optimizing efficient and durable battery technologies, with
                      a focus on failure distribution analysis.},
      cin          = {IEK-12},
      ddc          = {333.7},
      cid          = {I:(DE-Juel1)IEK-12-20141217},
      pnm          = {1223 - Batteries in Application (POF4-122)},
      pid          = {G:(DE-HGF)POF4-1223},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001185163000001},
      doi          = {10.1016/j.est.2024.110851},
      url          = {https://juser.fz-juelich.de/record/1023005},
}