Regarding Capacity degradation

[manjunathnilugal]

I am trying to simulate the lithium ion battery with my parameters.
I am plotting the Discharge capacity and capacity for the following configurations.

model = pybamm.lithium_ion.DFN({"particle":"Fickian diffusion",
                                "SEI": "ec reaction limited",
                                "SEI film resistance": "none",
                                "lithium plating":"none"})

The capacity is increasing initially and then decreasing.
I am not able to figure out why this is happening even though the discharge capacity is decreasing, but the plot_summary_variables capacity is showing different behaviour.

[brosaplanella]

Can you provide a minimum working example to reproduce this behaviour?

[manjunathnilugal]

I am trying to simulate the example code given for long experiments,
https://github.com/pybamm-team/PyBaMM/blob/0ab7c349efb4482d99f5532e31f30da40e3257a8/examples/notebooks/simulating-long-experiments.ipynb

import pybamm
import matplotlib.pyplot as plt
import numpy as np
parameter_values = pybamm.ParameterValues("Mohtat2020")
parameter_values.update({"SEI kinetic rate constant [m.s-1]": 1e-14})
spm = pybamm.lithium_ion.SPM({"SEI": "ec reaction limited"})
esoh_model = pybamm.lithium_ion.ElectrodeSOH()
esoh_sim = pybamm.Simulation(esoh_model, parameter_values=parameter_values)
param = spm.param

Vmin = 3.0
Vmax = 4.2
Cn = parameter_values.evaluate(param.C_n_init)
Cp = parameter_values.evaluate(param.C_p_init)
n_Li_init = parameter_values.evaluate(param.n_Li_particles_init)

esoh_sol = esoh_sim.solve(
    [0],
    inputs={"V_min": Vmin, "V_max": Vmax, "C_n": Cn, "C_p": Cp, "n_Li": n_Li_init},
)
print(f"Initial negative electrode SOC: {esoh_sol['x_100'].data[0]:.3f}")
print(f"Initial positive electrode SOC: {esoh_sol['y_100'].data[0]:.3f}")

# Update parameter values with initial conditions
c_n_max = parameter_values.evaluate(param.c_n_max)
c_p_max = parameter_values.evaluate(param.c_p_max)
parameter_values.update(
    {
        "Initial concentration in negative electrode [mol.m-3]": esoh_sol["x_100"].data[0] * c_n_max,
        "Initial concentration in positive electrode [mol.m-3]": esoh_sol["y_100"].data[0] * c_p_max,
    }
)

I am trying to run the above mentioned code in the local system with latest version of pybamm, but I am getting the error as mentioned below

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_22088\831465593.py in <module>
     11 Vmin = 3.0
     12 Vmax = 4.2
---> 13 Cn = parameter_values.evaluate(param.C_n_init)
     14 Cp = parameter_values.evaluate(param.C_p_init)
     15 n_Li_init = parameter_values.evaluate(param.n_Li_particles_init)

~\AppData\Roaming\Python\Python39\site-packages\pybamm\parameters\base_parameters.py in __getattribute__(self, name)
     38                             )
     39                         else:
---> 40                             raise e
     41                     else:
     42                         raise e

~\AppData\Roaming\Python\Python39\site-packages\pybamm\parameters\base_parameters.py in __getattribute__(self, name)
     16         """
     17         try:
---> 18             return super().__getattribute__(name)
     19         except AttributeError as e:
     20             for domain in ["n", "s", "p"]:

AttributeError: 'LithiumIonParameters' object has no attribute 'C_n_init'

[brosaplanella]

Which PyBaMM version are you using? You can print it by running the following commands:

import pybamm
print(pybamm.__version__)

[manjunathnilugal]

Sir, I am using 22.9 pybamm version

[brosaplanella]

This relates to a breaking change in v22.8 (this PR), where the domains in the parameters are now nested: param.c_n_max should now be param.n.prim.c_max, param.C_n_init should be param.n.cap_init, and so on...

[manjunathnilugal]

Thanks Sir, Now I am getting the initial SOC correctly.

[manjunathnilugal]

Regarding above mentioned issue, The Loss of capacity is increasing, but capacity is not decreasing.

import pybamm
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

model = pybamm.lithium_ion.DFN({"particle":"Fickian diffusion",
                                "SEI" : "reaction limited",
                                "SEI film resistance": "distributed",
                                "SEI porosity change": "false",
                                "lithium plating":"none"})

param = pybamm.ParameterValues("Ramadass2004")

param.update({
    "Inner SEI reaction proportion": 0.5,
    "SEI growth activation energy [J.mol-1]" : 0,
    "SEI reaction exchange current density [A.m-2]": 1.5e-6,
    "SEI resistivity [Ohm.m]": 200000,
    "Initial inner SEI thickness [m]": 2.5e-9,
    "Initial outer SEI thickness [m]": 2.5e-9,
    "Inner SEI partial molar volume [m3.mol-1]": 9.585e-5,
    "Outer SEI partial molar volume [m3.mol-1]": 9.585e-5,
    "Ratio of lithium moles to SEI moles": 2,
    "Lower voltage cut-off [V]" : 1.5,
}, check_already_exists=False)

experiment = pybamm.Experiment([
    (f"Discharge at 1C until 2V",
     f"Charge at 1C until 4.2V",
     f"Hold at 4.2V until 0.1C"
    )
]*500,
termination="80% capacity"
)

var_pts = {
    "x_n": 30,  # negative electrode
    "x_s": 30,  # separator
    "x_p": 30,  # positive electrode
    "r_n": 30,  # negative particle
    "r_p": 30,  # positive particle
}

safe_solver = pybamm.CasadiSolver(mode = "safe", rtol=1e-3, atol=1e-3, dt_max=0.5)
sim = pybamm.Simulation(model,parameter_values = param, solver = safe_solver, experiment = experiment, var_pts=var_pts)
solution = sim.solve()
pybamm.plot_summary_variables(solution)

Even though the loss of capacity is very less, it should reflect in the capacity loss, or I am missing something very important in including in degradation model.

[manjunathnilugal]

This issue is similar to the issue in #2472.