forked from pybamm-team/PyBaMM
-
Notifications
You must be signed in to change notification settings - Fork 0
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
pybamm-team#884 added integrated conductivity model
- Loading branch information
1 parent
17460e8
commit bf92330
Showing
2 changed files
with
163 additions
and
0 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
162 changes: 162 additions & 0 deletions
162
pybamm/models/submodels/electrolyte_conductivity/integrated_conductivity.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,162 @@ | ||
# | ||
# Composite electrolyte potential employing integrated Stefan-Maxwell | ||
# | ||
import pybamm | ||
from .base_electrolyte_conductivity import BaseElectrolyteConductivity | ||
|
||
|
||
class Integrated(BaseElectrolyteConductivity): | ||
"""Base class for conservation of charge in the electrolyte employing the | ||
Stefan-Maxwell constitutive equations. | ||
Parameters | ||
---------- | ||
param : parameter class | ||
The parameters to use for this submodel | ||
higher_order_terms : str | ||
What kind of higher-order terms to use ('composite' or 'first-order') | ||
domain : str, optional | ||
The domain in which the model holds | ||
**Extends:** :class:`pybamm.electrolyte_conductivity.BaseElectrolyteConductivity` | ||
""" | ||
|
||
def __init__(self, param, domain=None): | ||
super().__init__(param, domain) | ||
|
||
def _higher_order_macinnes_function(self, x): | ||
return pybamm.log(x) | ||
|
||
def get_coupled_variables(self, variables): | ||
c_e_av = variables["X-averaged electrolyte concentration"] | ||
|
||
i_boundary_cc_0 = variables["Leading-order current collector current density"] | ||
c_e_n = variables["Negative electrolyte concentration"] | ||
c_e_s = variables["Separator electrolyte concentration"] | ||
c_e_p = variables["Positive electrolyte concentration"] | ||
c_e_n0 = pybamm.boundary_value(c_e_n, "left") | ||
|
||
delta_phi_n_av = variables[ | ||
"X-averaged negative electrode surface potential difference" | ||
] | ||
phi_s_n_av = variables["X-averaged negative electrode potential"] | ||
|
||
tor_n = variables["Negative electrolyte tortuosity"] | ||
tor_s = variables["Separator tortuosity"] | ||
tor_p = variables["Positive electrolyte tortuosity"] | ||
|
||
T_av = variables["X-averaged cell temperature"] | ||
T_av_n = pybamm.PrimaryBroadcast(T_av, "negative electrode") | ||
T_av_s = pybamm.PrimaryBroadcast(T_av, "separator") | ||
T_av_p = pybamm.PrimaryBroadcast(T_av, "positive electrode") | ||
|
||
param = self.param | ||
l_n = param.l_n | ||
l_p = param.l_p | ||
x_n = pybamm.standard_spatial_vars.x_n | ||
x_s = pybamm.standard_spatial_vars.x_s | ||
x_p = pybamm.standard_spatial_vars.x_p | ||
x_n_edge = pybamm.standard_spatial_vars.x_n_edge | ||
# x_s_edge = pybamm.standard_spatial_vars.x_s_edge | ||
x_p_edge = pybamm.standard_spatial_vars.x_p_edge | ||
|
||
chi_av = param.chi(c_e_av) | ||
chi_av_n = pybamm.PrimaryBroadcast(chi_av, "negative electrode") | ||
chi_av_s = pybamm.PrimaryBroadcast(chi_av, "separator") | ||
chi_av_p = pybamm.PrimaryBroadcast(chi_av, "positive electrode") | ||
|
||
# electrolyte current | ||
i_e_n = i_boundary_cc_0 * x_n / l_n | ||
i_e_s = pybamm.PrimaryBroadcast(i_boundary_cc_0, "separator") | ||
i_e_p = i_boundary_cc_0 * (1 - x_p) / l_p | ||
i_e = pybamm.Concatenation(i_e_n, i_e_s, i_e_p) | ||
|
||
i_e_n_edge = i_boundary_cc_0 * x_n_edge / l_n | ||
i_e_s_edge = pybamm.PrimaryBroadcastToEdges(i_boundary_cc_0, "separator") | ||
i_e_p_edge = i_boundary_cc_0 * (1 - x_p_edge) / l_p | ||
# i_e_edge = pybamm.Concatenation(i_e_n_edge, i_e_s_edge, i_e_p_edge) | ||
|
||
# electrolyte potential | ||
indef_integral_n = pybamm.IndefiniteIntegral( | ||
i_e_n_edge / (param.kappa_e(c_e_n, T_av_n) * tor_n), x_n | ||
) * param.C_e / param.gamma_e | ||
indef_integral_s = pybamm.IndefiniteIntegral( | ||
i_e_s_edge / (param.kappa_e(c_e_s, T_av_s) * tor_s), x_s | ||
) * param.C_e / param.gamma_e | ||
indef_integral_p = pybamm.IndefiniteIntegral( | ||
i_e_p_edge / (param.kappa_e(c_e_p, T_av_p) * tor_p), x_p | ||
) * param.C_e / param.gamma_e | ||
|
||
integral_n = indef_integral_n - pybamm.boundary_value(indef_integral_n, "left") | ||
integral_s = ( | ||
indef_integral_s - pybamm.boundary_value(indef_integral_s, "left") | ||
+ pybamm.boundary_value(integral_n, "right") | ||
) | ||
integral_p = ( | ||
indef_integral_p - pybamm.boundary_value(indef_integral_p, "left") | ||
+ pybamm.boundary_value(integral_s, "right") | ||
) | ||
|
||
phi_e_const = ( | ||
-delta_phi_n_av | ||
+ phi_s_n_av | ||
- ( | ||
chi_av | ||
* (1 + param.Theta * T_av) | ||
* pybamm.x_average(self._higher_order_macinnes_function(c_e_n / c_e_n0)) | ||
) | ||
+ pybamm.x_average(integral_n) | ||
) | ||
|
||
phi_e_n = ( | ||
phi_e_const | ||
+ ( | ||
chi_av_n | ||
* (1 + param.Theta * T_av_n) | ||
* self._higher_order_macinnes_function(c_e_n / c_e_n0) | ||
) | ||
- integral_n | ||
) | ||
|
||
phi_e_s = ( | ||
phi_e_const | ||
+ ( | ||
chi_av_s | ||
* (1 + param.Theta * T_av_s) | ||
* self._higher_order_macinnes_function(c_e_s / c_e_n0) | ||
) | ||
- integral_s | ||
) | ||
|
||
phi_e_p = ( | ||
phi_e_const | ||
+ ( | ||
chi_av_p | ||
* (1 + param.Theta * T_av_p) | ||
* self._higher_order_macinnes_function(c_e_p / c_e_n0) | ||
) | ||
- integral_p | ||
) | ||
|
||
# concentration overpotential | ||
eta_c_av = ( | ||
chi_av | ||
* (1 + param.Theta * T_av) | ||
* ( | ||
pybamm.x_average(self._higher_order_macinnes_function(c_e_p / c_e_av)) | ||
- pybamm.x_average(self._higher_order_macinnes_function(c_e_n / c_e_av)) | ||
) | ||
) | ||
|
||
# average electrolyte ohmic losses | ||
delta_phi_e_av = - ( | ||
pybamm.x_average(integral_p) - pybamm.x_average(integral_n) | ||
) | ||
|
||
variables.update( | ||
self._get_standard_potential_variables(phi_e_n, phi_e_s, phi_e_p) | ||
) | ||
variables.update(self._get_standard_current_variables(i_e)) | ||
variables.update(self._get_split_overpotential(eta_c_av, delta_phi_e_av)) | ||
|
||
return variables |