To verify the improvement in simulations accounting for the parameter-dependencies and thermal behaviour for the M50, the simulations were compared to a C-rate discharge that the parameters were not tuned to. The diffusivity needs tuning due to underestimation in the solid-state coefficient during GITT, and in this case we have tuned to 1C for both the Chen et al. parameter set and those outlined in this paper, they both provide good agreement for this C-rate, see Figure . However, if these simulations are used to observe cell behave under various C-rates then it is not possible to tune to each C-rate, to observe how these parameters compare to the experimental data for those C-rates not specifically tuned for we repeat the simulations at C/2 and compare to the experimental data. For this case the new parameter set reduces the RMSE (root mean square error) by 27% (RMSE is 0.14 for Chen2020 parameter set and 0.10 for ORegan2021 parameter set). This demonstrates that including these parameter dependencies improves the prediction under conditions that could not be specifically tuned to. This relaxation can also be captured better in the simulation by capturing particle size distributions in the simulations. Reducing the number of parameters needed to be tuned and reducing the magnitude of tuning needed by including non-constant values.