Issue 1112 ec sei params

CHANGELOG.md

@@ -2,6 +2,7 @@
 
 ## Features
 
+-   Added variables which track the total amount of lithium in the system ([#1136](https://github.com/pybamm-team/PyBaMM/pull/1136))
 -   Added `Upwind` and `Downwind` operators for convection ([#1134](https://github.com/pybamm-team/PyBaMM/pull/1134))
 -   Added Getting Started notebook on solver options and changing the mesh. Also added a notebook detailing the different thermal options, and a notebook explaining the steps that occur behind the scenes in the `Simulation` class ([#1131](https://github.com/pybamm-team/PyBaMM/pull/1131))
 -   Added particle submodel that use a polynomial approximation to the concentration within the electrode particles ([#1130](https://github.com/pybamm-team/PyBaMM/pull/1130))
@@ -18,6 +19,7 @@
 
 ## Bug fixes
 
+-   Fixed bug where some parameters were not being set by the `EcRectionLimited` SEI model ([#1136](https://github.com/pybamm-team/PyBaMM/pull/1136))
 -   Fixed bug on electrolyte potential for `BasicDFNHalfCell` ([#1133](https://github.com/pybamm-team/PyBaMM/pull/1133))
 -   Fixed `r_average` to work with `SecondaryBroadcast` ([#1118](https://github.com/pybamm-team/PyBaMM/pull/1118))
 -   Fixed finite volume discretisation of spherical integrals ([#1118](https://github.com/pybamm-team/PyBaMM/pull/1118))

examples/notebooks/Getting Started/Tutorial 6 - Managing simulation outputs.ipynb

@@ -31,7 +31,7 @@
     {
      "data": {
       "text/plain": [
-       "<pybamm.solvers.solution.Solution at 0x7f33921f46d8>"
+       "<pybamm.solvers.solution.Solution at 0x7f39e107d1d0>"
       ]
      },
      "execution_count": 1,
@@ -265,7 +265,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "dc5c33b364df4561acc98455a6ec6d9c",
+       "model_id": "7e116fdff90e40b28b3f13b79f3e7347",
        "version_major": 2,
        "version_minor": 0
       },
@@ -313,7 +313,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "c3c3296fe37e4bffba0dada58dc06afa",
+       "model_id": "cb9640519af3475b9b921b8523c01020",
        "version_major": 2,
        "version_minor": 0
       },
@@ -327,7 +327,7 @@
     {
      "data": {
       "text/plain": [
-       "<pybamm.plotting.quick_plot.QuickPlot at 0x7f338e87b2b0>"
+       "<pybamm.plotting.quick_plot.QuickPlot at 0x7f39dc81a0b8>"
       ]
      },
      "execution_count": 11,
@@ -380,6 +380,27 @@
     "In this notebook we have shown how to extract and store the outputs of PyBaMM's simulations. Next, in [Tutorial 7](./Tutorial%207%20-%20Model%20options.ipynb) we will show how to change the model options."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Before finishing we will remove the data files we saved so that we leave the directory as we found it"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "os.remove(\"SPMe.pkl\")\n",
+    "os.remove(\"SPMe_sol.pkl\")\n",
+    "os.remove(\"sol_data.pkl\")\n",
+    "os.remove(\"sol_data.csv\")\n",
+    "os.remove(\"sol_data.mat\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,

examples/scripts/SPMe_SOC.py

@@ -74,8 +74,8 @@
         # solve model
         t_eval = np.linspace(0, 3600, 100)
         sol = model.default_solver.solve(model, t_eval)
-        xpext = sol["Positive electrode average extent of lithiation"]
-        xnext = sol["Negative electrode average extent of lithiation"]
+        xpext = sol["X-averaged positive electrode extent of lithiation"]
+        xnext = sol["X-averaged negative electrode extent of lithiation"]
         xpsurf = sol["X-averaged positive particle surface concentration"]
         xnsurf = sol["X-averaged negative particle surface concentration"]
         time = sol["Time [h]"]

examples/scripts/custom_model.py

@@ -16,6 +16,7 @@
 )
 model.submodels["current collector"] = pybamm.current_collector.Uniform(model.param)
 model.submodels["thermal"] = pybamm.thermal.isothermal.Isothermal(model.param)
+model.submodels["porosity"] = pybamm.porosity.Constant(model.param)
 model.submodels["negative electrode"] = pybamm.electrode.ohm.LeadingOrder(
     model.param, "Negative"
 )

pybamm/models/submodels/electrolyte_diffusion/base_electrolyte_diffusion.py

@@ -105,6 +105,35 @@ def _get_standard_flux_variables(self, N_e):
 
         return variables
 
+    def _get_total_concentration_electrolyte(self, c_e, epsilon):
+        """
+        A private function to obtain the total ion concentration in the electrolyte.
+
+        Parameters
+        ----------
+        c_e : :class:`pybamm.Symbol`
+            The electrolyte concentration
+        epsilon : :class:`pybamm.Symbol`
+            The porosity
+
+        Returns
+        -------
+        variables : dict
+            The "Total concentration in electrolyte [mol]" variable.
+        """
+
+        c_e_typ = self.param.c_e_typ
+        L_x = self.param.L_x
+        A = self.param.A_cc
+
+        c_e_total = pybamm.x_average(epsilon * c_e)
+
+        variables = {
+            "Total concentration in electrolyte [mol]": c_e_typ * L_x * A * c_e_total
+        }
+
+        return variables
+
     def set_events(self, variables):
         c_e = variables["Electrolyte concentration"]
         self.events.append(

pybamm/models/submodels/electrolyte_diffusion/composite_diffusion.py

@@ -36,6 +36,7 @@ def get_fundamental_variables(self):
     def get_coupled_variables(self, variables):
 
         tor_0 = variables["Leading-order electrolyte tortuosity"]
+        eps = variables["Leading-order porosity"]
         c_e_0_av = variables["Leading-order x-averaged electrolyte concentration"]
         c_e = variables["Electrolyte concentration"]
         i_e = variables["Electrolyte current density"]
@@ -51,6 +52,7 @@ def get_coupled_variables(self, variables):
         N_e = N_e_diffusion + N_e_migration + N_e_convection
 
         variables.update(self._get_standard_flux_variables(N_e))
+        variables.update(self._get_total_concentration_electrolyte(c_e, eps))
 
         return variables
 

pybamm/models/submodels/electrolyte_diffusion/constant_concentration.py

@@ -38,3 +38,10 @@ def get_fundamental_variables(self):
 
         return variables
 
+    def get_coupled_variables(self, variables):
+        c_e = variables["Electrolyte concentration"]
+        eps = variables["Porosity"]
+
+        variables.update(self._get_total_concentration_electrolyte(c_e, eps))
+
+        return variables

pybamm/models/submodels/electrolyte_diffusion/first_order_diffusion.py

@@ -138,4 +138,13 @@ def get_coupled_variables(self, variables):
         )
         variables.update(self._get_standard_flux_variables(N_e))
 
+        c_e = pybamm.Concatenation(c_e_n, c_e_s, c_e_p)
+        eps = pybamm.Concatenation(
+            pybamm.PrimaryBroadcast(eps_n_0, "negative electrode"),
+            pybamm.PrimaryBroadcast(eps_s_0, "separator"),
+            pybamm.PrimaryBroadcast(eps_p_0, "positive electrode"),
+        )
+
+        variables.update(self._get_total_concentration_electrolyte(c_e, eps))
+
         return variables

pybamm/models/submodels/electrolyte_diffusion/full_diffusion.py

@@ -34,6 +34,7 @@ def get_fundamental_variables(self):
     def get_coupled_variables(self, variables):
 
         tor = variables["Electrolyte tortuosity"]
+        eps = variables["Porosity"]
         c_e = variables["Electrolyte concentration"]
         i_e = variables["Electrolyte current density"]
         v_box = variables["Volume-averaged velocity"]
@@ -48,6 +49,7 @@ def get_coupled_variables(self, variables):
         N_e = N_e_diffusion + N_e_migration + N_e_convection
 
         variables.update(self._get_standard_flux_variables(N_e))
+        variables.update(self._get_total_concentration_electrolyte(c_e, eps))
 
         return variables
 

pybamm/models/submodels/electrolyte_diffusion/leading_order_diffusion.py

@@ -42,6 +42,16 @@ def get_coupled_variables(self, variables):
 
         variables.update(self._get_standard_flux_variables(N_e))
 
+        c_e_av = pybamm.standard_variables.c_e_av
+        c_e = pybamm.Concatenation(
+            pybamm.PrimaryBroadcast(c_e_av, ["negative electrode"]),
+            pybamm.PrimaryBroadcast(c_e_av, ["separator"]),
+            pybamm.PrimaryBroadcast(c_e_av, ["positive electrode"]),
+        )
+        eps = variables["Porosity"]
+
+        variables.update(self._get_total_concentration_electrolyte(c_e, eps))
+
         return variables
 
     def set_rhs(self, variables):

pybamm/models/submodels/interface/sei/base_sei.py

@@ -44,37 +44,18 @@ def _get_standard_thickness_variables(self, L_inner, L_outer):
             The variables which can be derived from the SEI thicknesses.
         """
         param = self.param
+        domain = self.domain.lower() + " electrode"
 
-        # Set scales to one for the "no SEI" model so that they are not required
-        # by parameter values in general
+        # Set length scale to one for the "no SEI" model so that it is not
+        # required by parameter values in general
         if isinstance(self, pybamm.sei.NoSEI):
             L_scale = 1
-            n_scale = 1
-            n_outer_scale = 1
-            v_bar = 1
         else:
             L_scale = param.L_sei_0_dim
-            n_scale = param.L_sei_0_dim * param.a_n_dim / param.V_bar_inner_dimensional
-            n_outer_scale = (
-                param.L_sei_0_dim * param.a_n_dim / param.V_bar_outer_dimensional
-            )
-            v_bar = param.v_bar
 
         L_inner_av = pybamm.x_average(L_inner)
         L_outer_av = pybamm.x_average(L_outer)
 
-        n_inner = L_inner  # inner SEI concentration
-        n_outer = L_outer  # outer SEI concentration
-        n_inner_av = pybamm.x_average(L_inner)
-        n_outer_av = pybamm.x_average(L_outer)
-
-        n_SEI = n_inner + n_outer / v_bar  # SEI concentration
-        n_SEI_av = pybamm.x_average(n_SEI)
-
-        Q_sei = n_SEI_av * self.param.L_n * self.param.L_y * self.param.L_z
-
-        domain = self.domain.lower() + " electrode"
-
         variables = {
             "Inner " + domain + " sei thickness": L_inner,
             "Inner " + domain + " sei thickness [m]": L_inner * L_scale,
@@ -84,21 +65,10 @@ def _get_standard_thickness_variables(self, L_inner, L_outer):
             "Outer " + domain + " sei thickness [m]": L_outer * L_scale,
             "X-averaged outer " + domain + " sei thickness": L_outer_av,
             "X-averaged outer " + domain + " sei thickness [m]": L_outer_av * L_scale,
-            "Inner " + domain + " sei concentration [mol.m-3]": n_inner * n_scale,
-            "X-averaged inner "
-            + domain
-            + " sei concentration [mol.m-3]": n_inner_av * n_scale,
-            "Outer " + domain + " sei concentration [mol.m-3]": n_outer * n_outer_scale,
-            "X-averaged outer "
-            + domain
-            + " sei concentration [mol.m-3]": n_outer_av * n_outer_scale,
-            self.domain + " sei concentration [mol.m-3]": n_SEI * n_scale,
-            "X-averaged " + domain + " sei concentration [mol.m-3]": n_SEI_av * n_scale,
-            "Loss of lithium to " + domain + " sei [mol]": Q_sei * n_scale,
         }
 
+        # Get variables related to the total thickness
         L_sei = L_inner + L_outer
-
         variables.update(self._get_standard_total_thickness_variables(L_sei))
 
         return variables
@@ -125,6 +95,98 @@ def _get_standard_total_thickness_variables(self, L_sei):
         }
         return variables
 
+    def _get_standard_concentraion_variables(self, variables):
+        "Update variables related to the SEI concentration"
+        param = self.param
+        domain = self.domain.lower() + " electrode"
+
+        # Set scales to one for the "no SEI" model so that they are not required
+        # by parameter values in general
+        if isinstance(self, pybamm.sei.NoSEI):
+            n_scale = 1
+            n_outer_scale = 1
+            v_bar = 1
+        # Set scales for the "EC Reaction Limited" model
+        elif isinstance(self, pybamm.sei.EcReactionLimited):
+            n_scale = 1
+            n_outer_scale = self.param.c_ec_0_dim
+            v_bar = 1
+        else:
+            n_scale = param.L_sei_0_dim * param.a_n_dim / param.V_bar_inner_dimensional
+            n_outer_scale = (
+                param.L_sei_0_dim * param.a_n_dim / param.V_bar_outer_dimensional
+            )
+            v_bar = param.v_bar
+
+        L_inner = variables["Inner " + domain + " sei thickness"]
+        L_outer = variables["Outer " + domain + " sei thickness"]
+
+        # Set SEI concentration variables. Note these are defined differently for
+        # the "EC Reaction Limited" model
+        if isinstance(self, pybamm.sei.EcReactionLimited):
+            j_outer = variables["Outer " + domain + " sei interfacial current density"]
+            # concentration of EC on graphite surface, base case = 1
+            if self.domain == "Negative":
+                C_ec = self.param.C_ec_n
+
+            c_ec = pybamm.Scalar(1) + j_outer * L_outer * C_ec
+            c_ec_av = pybamm.x_average(c_ec)
+
+            n_inner = pybamm.FullBroadcast(
+                0, self.domain.lower() + " electrode", "current collector"
+            )  # inner SEI concentration
+            n_outer = j_outer * L_outer * C_ec  # outer SEI concentration
+        else:
+            n_inner = L_inner  # inner SEI concentration
+            n_outer = L_outer  # outer SEI concentration
+
+        n_inner_av = pybamm.x_average(L_inner)
+        n_outer_av = pybamm.x_average(L_outer)
+
+        n_SEI = n_inner + n_outer / v_bar  # SEI concentration
+        n_SEI_av = pybamm.x_average(n_SEI)
+
+        Q_sei = n_SEI_av * self.param.L_n * self.param.L_y * self.param.L_z
+
+        variables.update(
+            {
+                "Inner " + domain + " sei concentration [mol.m-3]": n_inner * n_scale,
+                "X-averaged inner "
+                + domain
+                + " sei concentration [mol.m-3]": n_inner_av * n_scale,
+                "Outer "
+                + domain
+                + " sei concentration [mol.m-3]": n_outer * n_outer_scale,
+                "X-averaged outer "
+                + domain
+                + " sei concentration [mol.m-3]": n_outer_av * n_outer_scale,
+                self.domain + " sei concentration [mol.m-3]": n_SEI * n_scale,
+                "X-averaged "
+                + domain
+                + " sei concentration [mol.m-3]": n_SEI_av * n_scale,
+                "Loss of lithium to " + domain + " sei [mol]": Q_sei * n_scale,
+            }
+        )
+
+        # Also set variables for EC surface concentration
+        if isinstance(self, pybamm.sei.EcReactionLimited):
+            variables.update(
+                {
+                    self.domain + " electrode EC surface concentration": c_ec,
+                    self.domain
+                    + " electrode EC surface concentration [mol.m-3]": c_ec
+                    * n_outer_scale,
+                    "X-averaged "
+                    + self.domain.lower()
+                    + " electrode EC surface concentration": c_ec_av,
+                    "X-averaged "
+                    + self.domain.lower()
+                    + " electrode EC surface concentration": c_ec_av * n_outer_scale,
+                }
+            )
+
+        return variables
+
     def _get_standard_reaction_variables(self, j_inner, j_outer):
         """
         A private function to obtain the standard variables which

pybamm/models/submodels/interface/sei/constant_sei.py

@@ -6,7 +6,8 @@
 
 
 class ConstantSEI(BaseModel):
-    """Base class for SEI with constant thickness.
+    """
+    Class for SEI with constant thickness.
 
     Note that there is no SEI current, so we don't need to update the "sum of
     interfacial current densities" variables from
@@ -31,6 +32,9 @@ def get_fundamental_variables(self):
         L_outer = self.param.L_outer_0
         variables = self._get_standard_thickness_variables(L_inner, L_outer)
 
+        # Concentrations (derived from thicknesses)
+        variables.update(self._get_standard_concentraion_variables(variables))
+
         # Reactions
         zero = pybamm.FullBroadcast(
             pybamm.Scalar(0), self.domain.lower() + " electrode", "current collector"