Deviation between the half cell model and full DFN #2067
thuwangming
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Something looks wrong with the thickness of the layer which is too small for half cell and interfacial current is therefore higher and capacity lower than expected |
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You are not passing the parameter values to the simulation, so in the first instance it uses the default for a full-cell model (Marquis2019), and in the second it uses the default for a half-cell model (Xu2019) for the geometry. Try with |
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Hello,
I am trying to compare the half-cell model and the full DFN model, and I get some weird results.
I use the same parameter set to build a half-cell model and a full model, respectively. And some parameters for lithium plating are manually added from parameter set "Xu2019". When I run the models, I find that the terminal voltage of the half cell always dropped quickly below the cut-off voltage, but the full model looks normal. I have tested two parameter sets: "Marquis2019" and "Chen2020". The results and source codes are attached below.
How can I fix the problem? Thanks!
Full cell for "Chen2020"

Half cell for "Chen2020"

Full cell for "Marquis2019"

Half cell for "Marquis2019"

`# coding: utf-8
import pybamm
import numpy as np
from pybamm.input.parameters.lithium_ion.negative_electrodes.li_metal_Xu2019.li_metal_electrolyte_exchange_current_density_Xu2019 import li_metal_electrolyte_exchange_current_density_Xu2019
pybamm.set_logging_level("INFO")
isHalfCell = False
parameter_set = "Marquis2019"
C_rate = 1
if isHalfCell:
#Half Cell
model = pybamm.lithium_ion.DFN({"working electrode": "positive"})
else:
#Full DFN
model = pybamm.lithium_ion.DFN()
geometry = model.default_geometry
param = pybamm.ParameterValues(parameter_set)
param.export_csv(parameter_set+".csv")
param.update({"Exchange-current density for plating [A.m-2]":li_metal_electrolyte_exchange_current_density_Xu2019}, check_already_exists=False)
param.update({"Typical plated lithium concentration [mol.m-3]":76900}, check_already_exists=False)
param['Current function [A]'] = C_rate * param['Current function [A]']
#param.process_geometry(geometry)
param.process_model(model)
solve model
solver = pybamm.CasadiSolver(mode="safe", rtol=1e-6, atol=1e-6, dt_max=0.005, extra_options_setup={"max_num_steps": 50000})
t_eval = np.linspace(0, 3600, 100)
sim = pybamm.Simulation(model, solver=solver)
sim.solve(t_eval)
plot
pybamm.dynamic_plot(sim, output_variables=[
"Positive particle concentration [mol.m-3]",
"Electrolyte concentration [mol.m-3]",
"Interfacial current density [A.m-2]",
"Electrolyte potential [V]",
"Positive electrode potential [V]",
"Terminal voltage [V]",
"X-averaged positive electrode interfacial current density [A.m-2]",
"Sum of x-averaged positive electrode interfacial current densities",
"Positive particle surface concentration [mol.m-3]"
])
`
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