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@PHDTHESIS{Ali:1053944,
      author       = {Ali, Haider Adel},
      title        = {{P}hysics-based {E}lectrochemical {M}odelling of {L}i-ion
                      {B}atteries},
      school       = {RWTH Aachen},
      type         = {Dissertation},
      reportid     = {FZJ-2026-01621},
      pages        = {162},
      year         = {2026},
      note         = {Dissertation, RWTH Aachen, 2026},
      abstract     = {Physics-based battery models with the Doyle-Fuller-Newman
                      (DFN) model has been regarding as the very powerful model to
                      simulate the Li-ion batteries behaviour with good accuracy.
                      However, the high computational demand and parameterization
                      are the two main challenges have been the main obstacle for
                      the model have limited it use in applications. In this
                      thesis, a comparison of various simplifications of the DFN
                      model has been conducted to compared to improve the
                      simulation speed while maintaining good accuracy, the thesis
                      also propose a guideline on how the select the optimum model
                      simplification. Furthermore, in this thesis, the
                      multiple-particle DFN (MP-DFN) model is introduced, which
                      incorporates particle size distributions for improving
                      simulation accuracy while maintaining low computational
                      demand.A full parameterization framework have been
                      developed, including full cell teardown. In addition,
                      comparison and analysis are introduced on how to determine
                      the solid-phase diffusion coefficient $(D_"s"$ ) and the
                      reaction-rate constant $(k_"0"$ ). The result shows that the
                      combination of the galvanostatic intermittent titration
                      techniques (GITT) combined with DFN model is the most
                      accuracy approach. Furthermore, a parameterization of the
                      cell without cell tear-down is conducted by collecting data
                      from the electric vehicles, while charging and driving. The
                      combination of sensitivity analysis and optimization shows
                      that RMSE below 8 mV is achieved.Finally, simulation are
                      conducted to improve the charging speed in the EV, compared
                      with conventional constant current-constant voltage (CC-CV)
                      protocol. A control-based charging protocol that employs
                      physics-based models proposed in the thesis, demonstrates a
                      32 $\%$ faster charging speed compared to the standard CC-CV
                      protocol from a state of charge (SoC) of 5 $\%$ to 80 $\%,$
                      while keeping the anode potential within safe limits to
                      prevent Li-plating},
      cin          = {IET-1},
      cid          = {I:(DE-Juel1)IET-1-20110218},
      pnm          = {1223 - Batteries in Application (POF4-122) / HITEC -
                      Helmholtz Interdisciplinary Doctoral Training in Energy and
                      Climate Research (HITEC) (HITEC-20170406)},
      pid          = {G:(DE-HGF)POF4-1223 / G:(DE-Juel1)HITEC-20170406},
      typ          = {PUB:(DE-HGF)11},
      url          = {https://juser.fz-juelich.de/record/1053944},
}