Coupling lumped thermal model with degradation models

[Akila1993]

Hello Everyone,

I am trying to obtain EIS from the degradation models coupled with the lumped thermal model according to the code below. Are there any specific parameters I need to add additionally I am using Chen 2020 and OKane 2022 parameter sets.

Appreciate your comments.

Thank you.

# Initial conditions and parameter update

import pybamm
import matplotlib.pyplot as plt
import pbeis
import numpy as np
import matplotlib.pyplot as plt
import time as timer
from scipy.fft import fft

parameter_values = pybamm.ParameterValues("Chen2020")

pp = pybamm.ParameterValues("OKane2022")

model = pybamm.lithium_ion.DFN(
    {   
        "thermal": "lumped", #lumped thermal submodel 
        "surface form": "differential", #Adding capacitance to the model 
        #"SEI": "solvent-diffusion limited",
        #"SEI porosity change": "true",
        #"lithium plating": "partially reversible",
        #"lithium plating porosity change": "true",  # alias for "SEI porosity change"
        #"particle mechanics":"swelling only",
        #"SEI on cracks": "true",
        #"loss of active material": "stress-driven",
        
    }
)
var_pts = {
    "x_n": 5,  # negative electrode
    "x_s": 5,  # separator
    "x_p": 5,  # positive electrode
    "r_n": 30,  # negative particle
    "r_p": 30,  # positive particle
}


def get_chen2020_parameters():
    parameter_values = pybamm.ParameterValues("Chen2020")
    parameters = parameter_values
    return parameters

def get_okane2022_degradation_parameters():

 degradation_parameters = {
 'Dead lithium decay constant [s-1]': 1e-06,
 'Dead lithium decay rate [s-1]':pp["Dead lithium decay rate [s-1]"],
 'Initial plated lithium concentration [mol.m-3]': 0.0,
 'Lithium metal partial molar volume [m3.mol-1]': 1.3e-05,
 'Lithium plating kinetic rate constant [m.s-1]': 1e-09,
 'Lithium plating transfer coefficient': 0.65,
 'Negative electrode LAM constant exponential term': 2.0,
 'Negative electrode LAM constant proportional term [s-1]': 2.7778e-07,
 "Negative electrode Paris' law constant b": 1.12,
 "Negative electrode Paris' law constant m": 2.2,
 "Negative electrode Poisson's ratio": 0.3,
 "Negative electrode Young's modulus [Pa]": 15000000000.0,
 'Negative electrode cracking rate':pp["Negative electrode cracking rate"],
 'Negative electrode critical stress [Pa]': 60000000.0,
 'Negative electrode initial crack length [m]': 2e-08,
 'Negative electrode initial crack width [m]': 1.5e-08,
 'Negative electrode number of cracks per unit area [m-2]': 3180000000000000.0,
 'Negative electrode partial molar volume [m3.mol-1]': 3.1e-06,
 'Negative electrode reference concentration for free of deformation [mol.m-3]': 0.0,
 'Negative electrode volume change':pp["Negative electrode volume change"],
 'Positive electrode LAM constant exponential term': 2.0,
 'Positive electrode LAM constant proportional term [s-1]': 2.7778e-07,
 'Positive electrode OCP entropic change [V.K-1]': 0.0,
 "Positive electrode Paris' law constant b": 1.12,
 "Positive electrode Paris' law constant m": 2.2,
 "Positive electrode Poisson's ratio": 0.2,
 "Positive electrode Young's modulus [Pa]": 375000000000.0,
 'Positive electrode active material volume fraction': 0.665,
 'Positive electrode cracking rate':pp["Positive electrode cracking rate"],
 'Positive electrode critical stress [Pa]': 375000000.0,
 'Positive electrode initial crack length [m]': 2e-08,
 'Positive electrode initial crack width [m]': 1.5e-08,
 'Positive electrode number of cracks per unit area [m-2]': 3180000000000000.0,
 'Positive electrode partial molar volume [m3.mol-1]': 1.25e-05,
 'Positive electrode reference concentration for free of deformation [mol.m-3]': 0.0,
 'Positive electrode volume change':pp["Positive electrode volume change"],
 'Typical plated lithium concentration [mol.m-3]': 1000.0,
 'Exchange-current density for stripping [A.m-2]':pp["Exchange-current density for stripping [A.m-2]"],
 'Exchange-current density for plating [A.m-2]':pp["Exchange-current density for plating [A.m-2]"],
      
    }
 return degradation_parameters

def update_parameters():
    # Load Chen2020 parameters
    chen2020_params = get_chen2020_parameters()

    # Load OKane2022 degradation parameters
    okane2022_degradation_params = get_okane2022_degradation_parameters()

    # Update Chen2020 parameters with OKane2022 degradation parameters
    chen2020_params.update(okane2022_degradation_params, check_already_exists=False)

    return chen2020_params

updated_parameters = update_parameters()


# Set up experiment

cycle_number = 10

exp = pybamm.Experiment(
["Hold at 4.2 V until C/100",
"Rest for 4 hours",
"Discharge at 0.1C until 2.5 V", # initial capacity check
"Charge at 0.3C until 4.2 V",
"Hold at 4.2 V until C/100",]
+ [("Discharge at 1C until 2.5 V", # ageing cycles
"Charge at 0.3C until 4.2 V",
"Hold at 4.2 V until C/100",)] * cycle_number
+ ["Discharge at 0.1C until 2.5 V"],
)



start_time = timer.time()


sim = pybamm.Simulation(model, parameter_values=updated_parameters,experiment=exp,solver=pybamm.CasadiSolver(mode='safe without grid'),var_pts=var_pts)



solution = sim.solve()


# Set initial conditions of aged_model from the solution and EIS Running 

aged_model = model.set_initial_conditions_from(solution)

#frequency range
frequencies = np.logspace(-4, 2, 30)

#amplitude of the current for EIS 
I = 1 * 1e-3

number_of_periods = 20
samples_per_period = 20

#Current function 
def current_function(t):
    #return I * pybamm.sin(2 * np.pi * F * t)
    return I * pybamm.sin(2 * np.pi * pybamm.InputParameter("Frequency [Hz]") * t)

updated_parameters["Current function [A]"] = current_function

sim_aged = pybamm.Simulation(aged_model, parameter_values=updated_parameters,solver=pybamm.CasadiSolver(mode='safe without grid'),var_pts=var_pts)


impedances_time = []

for frequency in frequencies:
    # Solve
    period = 1 / frequency
    dt = period / samples_per_period
    t_eval = np.array(range(0, 1 + samples_per_period * number_of_periods)) * dt
    sol = sim_aged.solve(t_eval, inputs={"Frequency [Hz]": frequency},initial_soc=0.9)
    # Extract final two periods of the solution
    time = sol["Time [s]"].entries[-3 * samples_per_period - 1 :]
    current = sol["Current [A]"].entries[-3 * samples_per_period - 1 :]
    voltage = sol["Terminal voltage [V]"].entries[-3 * samples_per_period - 1 :]
    # FFT
    current_fft = fft(current)
    voltage_fft = fft(voltage)
    # Get index of first harmonic
    idx = np.argmax(np.abs(current_fft))
    impedance = -voltage_fft[idx] / current_fft[idx]
    impedances_time.append(impedance)`

[brosaplanella]

If you add additional physics there will be parameters missing. If you try to run, PyBaMM will crash and let you know the parameter that is missing (unfortunately it will only tell you one parameter at a time).