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@INPROCEEDINGS{Raijmakers:1053939,
      author       = {Raijmakers, Luc and Ali, Haider Adel and Tempel, Hermann
                      and Notten, Peter H. L. and Eichel, Rüdiger-A.},
      title        = {{I}mproving the accuracy of physics-based battery model
                      simulations: {D}etermination of solid-phase diffusion
                      coefficients and reaction-rate constants},
      reportid     = {FZJ-2026-01616},
      year         = {2025},
      abstract     = {Physics-based models are important tools for simulating and
                      optimizing the performance of Li-ion batteries, with the
                      Doyle-Fuller-Newman (DFN) model being the most widely
                      adopted [1]. However, the accuracy of this model depends
                      heavily on its parameters. Two of the most critical
                      parameters for the model are the solid-phase diffusion
                      coefficient $(D_s)$ and the reaction-rate coefficient
                      $(k_0)$ [2]. These parameters are critical because $D_s$
                      controls the diffusion overpotential, while $k_0$ governs
                      the charge-transfer overpotential. Together, these two
                      overpotentials account for more than half of the total
                      overpotential in a battery. Therefore, precise determination
                      of $D_s$ and $k_0$ will enhance battery state-estimation,
                      improve fast-charging protocols, and provide deeper insights
                      into battery degradation mechanisms, leading to more
                      efficient and reliable Li-ion battery applications.Since
                      $D_s$ and $k_0$ cannot be directly measured, they must be
                      estimated – a process that can be quite complex. A review
                      of the literature reveals that many studies have
                      inaccurately determined these parameters. In this work, we
                      have re-evaluated the estimation methods to address these
                      inaccuracies and improve the reliability of the estimation
                      process. This work uses galvanostatic and potentiostatic
                      intermittent titration techniques (GITT and PITT,
                      respectively) to estimate these key parameters using
                      half-cells with Li(Ni0.4Co0.6)O2 electrodes. The two
                      compared estimation methods are the widely used analytical
                      approach based on Weppner and Huggins's work [3] and a
                      physics-based approach with the DFN model.Figure 1 shows DFN
                      model simulation results under dynamic current-loading
                      conditions with $D_s$ and $k_0$ determined from various
                      measurement and estimation techniques. The combination of
                      GITT measurements with a newly proposed physics-based
                      protocol for determining $D_s$ and $k_0$ gives the highest
                      simulation accuracy, achieving an average root mean square
                      error (RMSE) of 5.5 mV, as shown in Figure 1a. In contrast,
                      the analytical method in combination with GITT measurements
                      for determining $D_s$ and $k_0,$ which is the most used in
                      literature, shows the least accuracy, with an RMSE of 24.2
                      mV, as shown in Figure 1b. This higher error is attributed
                      to the limitations inherent in the analytical approach's
                      core assumptions.This study introduces a novel protocol for
                      optimizing $D_s$ and $k_0$ as a function of lithiation
                      degree from a single measurement, eliminating the need for
                      expensive and complex techniques such as electrochemical
                      impedance spectroscopy (EIS).References:[1] M. Doyle, T.F.
                      Fuller, J. Newman, Modeling of Galvanostatic Charge and
                      Discharge of the Lithium/Polymer/Insertion Cell, J.
                      Electrochem. Soc. 140 (1993) 1526.
                      https://doi.org/10.1149/1.2221597.[2] H.A.A. Ali, L.H.J.
                      Raijmakers, K. Chayambuka, D.L. Danilov, P.H.L. Notten,
                      R.-A. Eichel, A comparison between physics-based Li-ion
                      battery models, Electrochimica Acta (2024) 144360.
                      https://doi.org/10.1016/j.electacta.2024.144360.[3] W.
                      Weppner, R.A. Huggins, Determination of the Kinetic
                      Parameters of Mixed‐Conducting Electrodes and Application
                      to the System Li3Sb, J. Electrochem. Soc. 124 (1977) 1569.
                      https://doi.org/10.1149/1.2133112.},
      month         = {Apr},
      date          = {2025-04-02},
      organization  = {Advanced Battery Power Conference,
                       Aachen (Germany), 2 Apr 2025 - 3 Apr
                       2025},
      subtyp        = {After Call},
      cin          = {IET-1},
      cid          = {I:(DE-Juel1)IET-1-20110218},
      pnm          = {1223 - Batteries in Application (POF4-122)},
      pid          = {G:(DE-HGF)POF4-1223},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/1053939},
}