Hi everyone!
I’m using PyBaMM to study the impact of a fixed charging strategy under long-term degradation. From my understanding, degradation increases the interfacial resistance, which should lead to higher voltage and temperature. However, the effects I observe are not very pronounced. My current settings are as follows:
options = {
"thermal": "lumped",
"SEI": "solvent-diffusion limited",
"lithium plating": "irreversible",
}
self.param.update(
{
"Outer SEI solvent diffusivity [m2.s-1]": 2.5e-22,
"Lithium plating kinetic rate constant [m.s-1]": 1e-11
}
)
I would like to ask whether I should try increasing the outer SEI solvent diffusivity, or if there are other parameters that would be more effective to modify.
Thank you very much for your advice!
Over the past few days, I have conducted several experiments, including changing the SEI mechanism and some related parameters. My goal was to obtain a coupled degradation mechanism that can reflect how risk factors such as overpotential affect the battery degradation rate. However, the results are still unsatisfactory. I found that even after switching degradation mechanisms, the capacity fade curves change very little, and it appears that lithium plating dominates the degradation process, while the expected impact of these risk factors is not clearly reflected. With this setup, I can observe that the voltage rises more easily, but it does not result in a noticeably faster degradation rate.
Therefore, I would like to ask for advice on how to better design the degradation mechanisms and the selection of related parameters.
options = {
"thermal": "lumped",
"SEI": "reaction limited",
"lithium plating": "irreversible",
}
self.param = pybamm.ParameterValues("OKane2022")
self.param.update(
{
"Outer SEI solvent diffusivity [m2.s-1]": 2.5e-22,
"Lithium plating kinetic rate constant [m.s-1]": 2e-11,
"SEI resistivity [Ohm.m]": 1e6,
"SEI kinetic rate constant [m.s-1]": 1e-11
}
)