add temperature dependence to MSMR model (#3832)

* Bump to v23.9rc0 * Merge pull request #3412 from agriyakhetarpal/drop-i686-manylinux2014-support Drop support for i686 manylinux * Merge pull request #3413 from Saransh-cpp/improve-release-workflow Improve release workflow, add a note, bump version manually * Merge pull request #3436 from Saransh-cpp/fortnightly-wheels Build wheels on the 1st and 15th of every month * Merge pull request #3445 from pybamm-team/issue-3428-rename-exchange #3428 exchange-current density error * Merge pull request #3449 from pybamm-team/i3431-windows-wheels Fix failing windows wheel builds * Merge pull request #3456 from abillscmu/issue-3224-initial_soc make initial soc work with half cell models * Merge pull request #3467 from abillscmu/bugfix/initial_soh * Merge pull request #3423 from jsbrittain/jax_gpu JaxSolver fails when using GPU support with no input parameters * Fix changelog * Merge pull request #3475 from arjxn-py/fix-default-imports Resolve default imports for optional dependencies * Bump - `v23.9rc1` * Fix date in CHANGELOG * Bump version to v23.9 * Fix docs about Jax solver compatibility with Python versions (#3702) * Ensure correct Python versions for Jax solver compatibility * Simplify array of Python versions Co-authored-by: Eric G. Kratz <[email protected]> * Use different conjunction Co-authored-by: Eric G. Kratz <[email protected]> --------- Co-authored-by: Eric G. Kratz <[email protected]> * Merge pull request #3706 from agriyakhetarpal/fix-pybamm-install-odes Make `pybamm_install_odes` a bit more robust * #3690 fix issue with skipped steps (#3708) * #3690 fix issue with skipped steps * #3690 changelog * #3690 add test * #3611 use actual cell volume for average total heating (#3707) * #3611 use actual cell volume for average total heating * #3611 changelog * #3611 account for number of electrode pairs * #3611 update variable names * Improve the release workflow (#3737) * Try fixing the release workflow * Turn off safety * Fix CHANGELOG * Add OS * Use regex for better matches * Update instructions, add safety checks * checkout to the version branch for the final release * Bump to v24.1rc1 * #3630 fix interpolant shape error (#3761) * #3630 fix interpolant shape error * #3630 changelog * Bump to v24.1rc2 * Bump to v24.1 * Fix doctests failures in scheduled tests (#3784) Closes #3781 * Resolve broken `scikits.odes` installation on self-hosted M-series runner (#3785) * Try fixing M-series runner tests This is being done by adding SuiteSparse and SUNDIALS installations which might have been missing on the runner, which broke `scikits.odes`. * Don't use Homebrew SUNDIALS, use LD_LIBRARY_PATH * Don't use Homebrew to install SUNDIALS * Force remove pip cache for `scikits.odes` --------- Co-authored-by: Eric G. Kratz <[email protected]> * add temperature dependence to MSMR model * changelog * fix tests * fix example * rob comments * update notebook --------- Co-authored-by: Ferran Brosa Planella <[email protected]> Co-authored-by: Saransh Chopra <[email protected]> Co-authored-by: Martin Robinson <[email protected]> Co-authored-by: Agriya Khetarpal <[email protected]> Co-authored-by: Eric G. Kratz <[email protected]> Co-authored-by: Robert Timms <[email protected]> Co-authored-by: Saransh-cpp <[email protected]>
pybamm-team · May 16, 2024 · 33d9ea7 · 33d9ea7
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diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -10,6 +10,7 @@
 - Lithium plating now works on composite electrodes ([#3919](https://github.com/pybamm-team/PyBaMM/pull/3919))
 - Added lithium plating parameters to `Ecker2015` and `Ecker2015_graphite_halfcell` parameter sets ([#3919](https://github.com/pybamm-team/PyBaMM/pull/3919))
 - Added custom experiment steps ([#3835](https://github.com/pybamm-team/PyBaMM/pull/3835))
+- MSMR open-circuit voltage model now depends on the temperature ([#3832](https://github.com/pybamm-team/PyBaMM/pull/3832))
 - Added support for macOS arm64 (M-series) platforms. ([#3789](https://github.com/pybamm-team/PyBaMM/pull/3789))
 - Added the ability to specify a custom solver tolerance in `get_initial_stoichiometries` and related functions ([#3714](https://github.com/pybamm-team/PyBaMM/pull/3714))
 - Modified `step` function to take an array of time `t_eval` as an argument and deprecated use of `npts`. ([#3627](https://github.com/pybamm-team/PyBaMM/pull/3627))
@@ -67,7 +68,6 @@
 - Added a method, `insert_reference_electrode`, to `pybamm.lithium_ion.BaseModel` that insert a reference electrode to measure the electrolyte potential at a given position in space and adds new variables that mimic a 3E cell setup. ([#3573](https://github.com/pybamm-team/PyBaMM/pull/3573))
 - Serialisation added so models can be written to/read from JSON ([#3397](https://github.com/pybamm-team/PyBaMM/pull/3397))
 - Added a `get_parameter_info` method for models and modified "print_parameter_info" functionality to extract all parameters and their type in a tabular and readable format ([#3584](https://github.com/pybamm-team/PyBaMM/pull/3584))
-- Mechanical parameters are now a function of stoichiometry and temperature ([#3576](https://github.com/pybamm-team/PyBaMM/pull/3576))
 
 ## Bug fixes
 

diff --git a/docs/source/api/models/submodels/particle/msmr_diffusion.rst b/docs/source/api/models/submodels/particle/msmr_diffusion.rst
@@ -4,4 +4,7 @@ MSMR Diffusion
 .. autoclass:: pybamm.particle.MSMRDiffusion
     :members:
 
+.. autoclass:: pybamm.particle.MSMRStoichiometryVariables
+    :members:
+
 .. footbibliography::
diff --git a/docs/source/examples/notebooks/models/MSMR.ipynb b/docs/source/examples/notebooks/models/MSMR.ipynb
diff --git a/pybamm/__init__.py b/pybamm/__init__.py
@@ -196,8 +196,26 @@
 # Remove any imported modules, so we don't expose them as part of pybamm
 del sys
 
-__all__ = ['batch_study', 'callbacks', 'citations', 'discretisations',
-           'doc_utils', 'experiment', 'expression_tree', 'geometry', 'input',
-           'logger', 'meshes', 'models', 'parameters', 'plotting', 'settings',
-           'simulation', 'solvers', 'spatial_methods', 'type_definitions',
-           'util', 'version']
+__all__ = [
+    "batch_study",
+    "callbacks",
+    "citations",
+    "discretisations",
+    "doc_utils",
+    "experiment",
+    "expression_tree",
+    "geometry",
+    "input",
+    "logger",
+    "meshes",
+    "models",
+    "parameters",
+    "plotting",
+    "settings",
+    "simulation",
+    "solvers",
+    "spatial_methods",
+    "type_definitions",
+    "util",
+    "version",
+]
diff --git a/pybamm/models/full_battery_models/lithium_ion/dfn.py b/pybamm/models/full_battery_models/lithium_ion/dfn.py
@@ -69,6 +69,17 @@ def set_particle_submodel(self):
                     submod = pybamm.particle.MSMRDiffusion(
                         self.param, domain, self.options, phase=phase, x_average=False
                     )
+                    # also set the submodel for calculating stoichiometry from
+                    # potential
+                    self.submodels[f"{domain} {phase} stoichiometry"] = (
+                        pybamm.particle.MSMRStoichiometryVariables(
+                            self.param,
+                            domain,
+                            self.options,
+                            phase=phase,
+                            x_average=False,
+                        )
+                    )
                 self.submodels[f"{domain} {phase} particle"] = submod
                 self.submodels[f"{domain} {phase} total particle concentration"] = (
                     pybamm.particle.TotalConcentration(

diff --git a/pybamm/models/full_battery_models/lithium_ion/electrode_soh.py b/pybamm/models/full_battery_models/lithium_ion/electrode_soh.py
@@ -202,6 +202,7 @@ def __init__(
         x_n = param.n.prim.x
         x_p = param.p.prim.x
 
+        T = param.T_ref
         V_max = param.voltage_high_cut
         V_min = param.voltage_low_cut
         Q_n = pybamm.InputParameter("Q_n")
@@ -221,21 +222,21 @@ def __init__(
         if "Un_0" in solve_for:
             Un_0 = pybamm.Variable("Un(x_0)")
             Up_0 = V_min + Un_0
-            x_0 = x_n(Un_0)
-            y_0 = x_p(Up_0)
+            x_0 = x_n(Un_0, T)
+            y_0 = x_p(Up_0, T)
 
         # Define variables for 100% state of charge
         # TODO: thermal effects (include dU/dT)
         if "Un_100" in solve_for:
             Un_100 = pybamm.Variable("Un(x_100)")
             Up_100 = V_max + Un_100
-            x_100 = x_n(Un_100)
-            y_100 = x_p(Up_100)
+            x_100 = x_n(Un_100, T)
+            y_100 = x_p(Up_100, T)
         else:
             Un_100 = pybamm.InputParameter("Un(x_100)")
             Up_100 = pybamm.InputParameter("Up(y_100)")
-            x_100 = x_n(Un_100)
-            y_100 = x_p(Up_100)
+            x_100 = x_n(Un_100, T)
+            y_100 = x_p(Up_100, T)
 
         # Define equations for 100% state of charge
         if "Un_100" in solve_for:
@@ -682,20 +683,20 @@ def get_initial_stoichiometries(self, initial_value, tol=1e-6, inputs=None):
             soc = pybamm.Variable("soc")
             x = x_0 + soc * (x_100 - x_0)
             y = y_0 - soc * (y_0 - y_100)
+            T_ref = parameter_values["Reference temperature [K]"]
             if self.options["open-circuit potential"] == "MSMR":
                 xn = param.n.prim.x
                 xp = param.p.prim.x
                 Up = pybamm.Variable("Up")
                 Un = pybamm.Variable("Un")
-                soc_model.algebraic[Up] = x - xn(Un)
-                soc_model.algebraic[Un] = y - xp(Up)
+                soc_model.algebraic[Up] = x - xn(Un, T_ref)
+                soc_model.algebraic[Un] = y - xp(Up, T_ref)
                 soc_model.initial_conditions[Un] = 0
                 soc_model.initial_conditions[Up] = V_max
                 soc_model.algebraic[soc] = Up - Un - V_init
             else:
                 Up = param.p.prim.U
                 Un = param.n.prim.U
-                T_ref = parameter_values["Reference temperature [K]"]
                 soc_model.algebraic[soc] = Up(y, T_ref) - Un(x, T_ref) - V_init
             # initial guess for soc linearly interpolates between 0 and 1
             # based on V linearly interpolating between V_max and V_min
@@ -1051,14 +1052,15 @@ def _get_msmr_potential_model(parameter_values, param):
     V_min = param.voltage_low_cut
     x_n = param.n.prim.x
     x_p = param.p.prim.x
+    T = param.T_ref
     model = pybamm.BaseModel()
     Un = pybamm.Variable("Un")
     Up = pybamm.Variable("Up")
     x = pybamm.InputParameter("x")
     y = pybamm.InputParameter("y")
     model.algebraic = {
-        Un: x_n(Un) - x,
-        Up: x_p(Up) - y,
+        Un: x_n(Un, T) - x,
+        Up: x_p(Up, T) - y,
     }
     model.initial_conditions = {
         Un: 1 - x,

diff --git a/pybamm/models/full_battery_models/lithium_ion/newman_tobias.py b/pybamm/models/full_battery_models/lithium_ion/newman_tobias.py
@@ -52,6 +52,17 @@ def set_particle_submodel(self):
                     submod = pybamm.particle.MSMRDiffusion(
                         self.param, domain, self.options, phase=phase, x_average=True
                     )
+                    # also set the submodel for calculating stoichiometry from
+                    # potential
+                    self.submodels[f"{domain} {phase} stoichiometry"] = (
+                        pybamm.particle.MSMRStoichiometryVariables(
+                            self.param,
+                            domain,
+                            self.options,
+                            phase=phase,
+                            x_average=True,
+                        )
+                    )
                 self.submodels[f"{domain} {phase} particle"] = submod
                 self.submodels[f"{domain} {phase} total particle concentration"] = (
                     pybamm.particle.TotalConcentration(

diff --git a/pybamm/models/full_battery_models/lithium_ion/spm.py b/pybamm/models/full_battery_models/lithium_ion/spm.py
@@ -108,6 +108,17 @@ def set_particle_submodel(self):
                     submod = pybamm.particle.MSMRDiffusion(
                         self.param, domain, self.options, phase=phase, x_average=True
                     )
+                    # also set the submodel for calculating stoichiometry from
+                    # potential
+                    self.submodels[f"{domain} {phase} stoichiometry"] = (
+                        pybamm.particle.MSMRStoichiometryVariables(
+                            self.param,
+                            domain,
+                            self.options,
+                            phase=phase,
+                            x_average=True,
+                        )
+                    )
                 self.submodels[f"{domain} {phase} particle"] = submod
                 self.submodels[f"{domain} {phase} total particle concentration"] = (
                     pybamm.particle.TotalConcentration(

diff --git a/pybamm/models/submodels/interface/kinetics/msmr_butler_volmer.py b/pybamm/models/submodels/interface/kinetics/msmr_butler_volmer.py
@@ -117,7 +117,7 @@ def _get_standard_exchange_current_by_reaction_variables(self, j0, index):
         return variables
 
     def _get_kinetics_by_reaction(self, j0, ne, eta_r, T, u, index):
-        alpha = self.phase_param.alpha_bv_j(index)
+        alpha = self.phase_param.alpha_bv_j(T, index)
         Feta_RT = self.param.F * eta_r / (self.param.R * T)
         return (
             u

diff --git a/pybamm/models/submodels/particle/__init__.py b/pybamm/models/submodels/particle/__init__.py
@@ -3,8 +3,13 @@
 from .polynomial_profile import PolynomialProfile
 from .x_averaged_polynomial_profile import XAveragedPolynomialProfile
 from .total_particle_concentration import TotalConcentration
-from .msmr_diffusion import MSMRDiffusion
+from .msmr_diffusion import MSMRDiffusion, MSMRStoichiometryVariables
 
-__all__ = ['base_particle', 'fickian_diffusion', 'msmr_diffusion',
-           'polynomial_profile', 'total_particle_concentration',
-           'x_averaged_polynomial_profile']
+__all__ = [
+    "base_particle",
+    "fickian_diffusion",
+    "msmr_diffusion",
+    "polynomial_profile",
+    "total_particle_concentration",
+    "x_averaged_polynomial_profile",
+]