pybamm-team · rtimms · Aug 4, 2020 · Jul 28, 2020 · Jul 28, 2020 · Jul 29, 2020
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -2,7 +2,9 @@
 
 ## Features
 
--   Added "R-averaged particle concentration" variables` ([#1118](https://github.com/pybamm-team/PyBaMM/pull/1118))
+
+-   Automatically compute surface area per unit volume based on particle shape for li-ion models ([#1120])(https://github.com/pybamm-team/PyBaMM/pull/1120)
+-   Added "R-averaged particle concentration" variables ([#1118](https://github.com/pybamm-team/PyBaMM/pull/1118))
 -   Added support for sensitivity calculations to the casadi solver ([#1109](https://github.com/pybamm-team/PyBaMM/pull/1109))
 -   Added support for index 1 semi-explicit dae equations and sensitivity calculations to JAX BDF solver ([#1107](https://github.com/pybamm-team/PyBaMM/pull/1107))
 -   Allowed keyword arguments to be passed to `Simulation.plot()` ([#1099](https://github.com/pybamm-team/PyBaMM/pull/1099))
@@ -18,6 +20,8 @@
 
 ## Breaking changes
 
+-  The modules containing standard parameters are now classes so they can take options
+(e.g. `standard_parameters_lithium_ion` is now `LithiumIonParameters`) ([#1120])(https://github.com/pybamm-team/PyBaMM/pull/1120)
 -  Renamed `quick_plot_vars` to `output_variables` in `Simulation` to be consistent with `QuickPlot`. Passing `quick_plot_vars` to `Simulation.plot()` has been deprecated and `output_variables` should be passed instead ([#1099](https://github.com/pybamm-team/PyBaMM/pull/1099))
 
 

@@ -1,4 +1,4 @@
 Electrical Parameters
 =====================
 
-.. automodule:: pybamm.parameters.electrical_parameters
+.. autoclass:: pybamm.ElectricalParameters
@@ -1,5 +1,4 @@
 Geometric Parameters
 ====================
 
-.. automodule:: pybamm.parameters.geometric_parameters
-
+.. autoclass:: pybamm.GeometricParameters
@@ -7,6 +7,6 @@ Parameters
   geometric_parameters
   electrical_parameters
   thermal_parameters
-  standard_parameters_lithium_ion
-  standard_parameters_lead_acid
-  parameter_sets
+  lithium_ion_parameters
+  lead_acid_parameters
+  parameter_sets
@@ -0,0 +1,4 @@
+Lead-Acid Parameters
+====================
+
+.. autoclass:: pybamm.LeadAcidParameters
@@ -0,0 +1,4 @@
+Lithium-ion Parameters
+======================
+
+.. autoclass:: pybamm.LithiumIonParameters
@@ -1,5 +1,5 @@
-Base Parameter Values
-=====================
+Parameter Values
+================
 
 .. autoclass:: pybamm.ParameterValues
   :members:
@@ -1,4 +1,4 @@
 Thermal Parameters
-=====================
+==================
 
-.. automodule:: pybamm.parameters.thermal_parameters
+.. autoclass:: pybamm.ThermalParameters
@@ -142,10 +142,11 @@ The inbuilt models in PyBaMM do not add all the model attributes within their ow
 In addition to calling submodels, common sets of variables and parameters found in
 lithium-ion and lead acid batteries are provided in
 `standard_variables.py`,
-`standard_parameters_lithium_ion.py`,
-`standard_parameters_lead_acid.py`,
+`lithium_ion_parameters.py`,
+`lead_acid_parameters.py`,
 `electrical_parameters.py`,
 `geometric_parameters.py`,
+`thermal_parameters.py`,
 and `standard_spatial_vars.py`
 which we encourage use of to save redefining the same parameters and variables in
 every model and submodel.

@@ -34,8 +34,6 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\u001b[33mWARNING: You are using pip version 20.1.1; however, version 20.2 is available.\n",
-      "You should consider upgrading via the '/home/ferranbrosa/PyBaMM/env/bin/python -m pip install --upgrade pip' command.\u001b[0m\n",
       "Note: you may need to restart the kernel to use updated packages.\n"
      ]
     }
@@ -77,7 +75,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "55b83465a9ea4937bfd3444fa7198460",
+       "model_id": "0b6d24762adc49bb95efa892bed183da",
        "version_major": 2,
        "version_minor": 0
       },
@@ -126,7 +124,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "b827d913896b418caf161f6d8ee9df92",
+       "model_id": "9cdb5f149490457796917576b3d5eb13",
        "version_major": 2,
        "version_minor": 0
       },
@@ -164,7 +162,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "64e6f94728be4ef5bfec800bc26f0768",
+       "model_id": "a43ac5cc2f204becbb8263f606f7fe94",
        "version_major": 2,
        "version_minor": 0
       },
@@ -270,7 +268,7 @@
     "param = model.default_parameter_values\n",
     "\n",
     "# set user defined current function\n",
-    "A = pybamm.electrical_parameters.I_typ\n",
+    "A = model.param.I_typ\n",
     "omega = 0.1\n",
     "param[\"Current function [A]\"] = my_fun(A,omega)\n",
     "\n",
@@ -294,7 +292,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "c2a1fdc7aa5246aaa9543650d96894ca",
+       "model_id": "373a98b202d54b958d2a1bc8c5653aba",
        "version_major": 2,
        "version_minor": 0
       },
@@ -326,20 +324,13 @@
     "quick_plot = pybamm.QuickPlot(solution, output_variables, label)\n",
     "quick_plot.dynamic_plot();"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "PyBaMM development (env)",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "pybamm-dev"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -351,7 +342,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.8"
+   "version": "3.6.9"
   }
  },
  "nbformat": 4,

@@ -12,9 +12,6 @@
 import numpy as np
 import matplotlib.pyplot as plt
 
-plt.close("all")
-pybamm.set_logging_level(30)
-
 factor = 6.38
 capacities = []
 specific_capacities = []
@@ -56,8 +53,6 @@
                 "Maximum concentration in positive electrode [mol.m-3]": 50000,
                 "Initial concentration in negative electrode [mol.m-3]": 12500,
                 "Initial concentration in positive electrode [mol.m-3]": 25000,
-                "Negative electrode surface area to volume ratio [m-1]": 180000.0,
-                "Positive electrode surface area to volume ratio [m-1]": 150000.0,
                 "Current function [A]": I_app,
             }
         )
@@ -133,3 +128,4 @@
 ax1.set_ylabel("Capacity [mAh]")
 ax2.set_ylabel("Specific Capacity [mAh.cm-3]")
 ax2.set_xlabel("Anode : Cathode thickness")
+plt.show()
@@ -32,9 +32,16 @@
 
 # load parameters and process model and geometry
 param = pybamm_model.default_parameter_values
-param["Electrode width [m]"] = 1
-param["Electrode height [m]"] = 1
-param["Current function [A]"] = 24 * C_rates[C_rate]
+param.update(
+    {
+        "Electrode width [m]": 1,
+        "Electrode height [m]": 1,
+        "Negative electrode conductivity [S.m-1]": 126,
+        "Positive electrode conductivity [S.m-1]": 16.6,
+        "Current function [A]": 24 * C_rates[C_rate],
+    }
+)
+
 param.process_model(pybamm_model)
 param.process_geometry(geometry)
 
@@ -55,7 +62,7 @@
 # Make Comsol 'model' for comparison
 whole_cell = ["negative electrode", "separator", "positive electrode"]
 comsol_t = comsol_variables["time"]
-L_x = param.evaluate(pybamm.standard_parameters_lithium_ion.L_x)
+L_x = param.evaluate(pybamm_model.param.L_x)
 
 
 def get_interp_fun(variable_name, domain):

@@ -17,9 +17,15 @@
 
 # load parameters and process model and geometry
 param = model.default_parameter_values
-param["Electrode width [m]"] = 1
-param["Electrode height [m]"] = 1
-param["Current function [A]"] = "[input]"
+param.update(
+    {
+        "Electrode width [m]": 1,
+        "Electrode height [m]": 1,
+        "Negative electrode conductivity [S.m-1]": 126,
+        "Positive electrode conductivity [S.m-1]": 16.6,
+        "Current function [A]": "[input]",
+    }
+)
 param.process_model(model)
 param.process_geometry(geometry)
 

@@ -1,68 +1,40 @@
 #
-# Compare lithium-ion battery models
+# Compare lithium-ion battery models with and without particle size distibution
 #
-import argparse
 import numpy as np
 import pybamm
 
-parser = argparse.ArgumentParser()
-parser.add_argument(
-    "--debug", action="store_true", help="Set logging level to 'DEBUG'."
-)
-args = parser.parse_args()
-if args.debug:
-    pybamm.set_logging_level("DEBUG")
-else:
-    pybamm.set_logging_level("INFO")
+pybamm.set_logging_level("INFO")
 
 # load models
-options = {"thermal": "isothermal"}
 models = [
-    pybamm.lithium_ion.DFN(options, name="standard DFN"),
-    pybamm.lithium_ion.DFN(options, name="particle DFN"),
+    pybamm.lithium_ion.DFN(name="standard DFN"),
+    pybamm.lithium_ion.DFN(name="particle DFN"),
 ]
 
-
-# load parameter values and process models and geometry
+# load parameter values
 params = [models[0].default_parameter_values, models[1].default_parameter_values]
-params[0]["Typical current [A]"] = 1.0
-params[0].process_model(models[0])
-
-
-params[1]["Typical current [A]"] = 1.0
 
 
 def negative_distribution(x):
-    return 1 + x
+    return 1 + 2 * x / models[1].param.l_n
 
 
 def positive_distribution(x):
-    return 1 + (x - (1 - models[1].param.l_p))
+    return 1 + 2 * (1 - x) / models[1].param.l_p
 
 
 params[1]["Negative particle distribution in x"] = negative_distribution
 params[1]["Positive particle distribution in x"] = positive_distribution
-params[1].process_model(models[1])
 
-# set mesh
-var = pybamm.standard_spatial_vars
-var_pts = {var.x_n: 10, var.x_s: 10, var.x_p: 10, var.r_n: 5, var.r_p: 5}
 
-# discretise models
-for param, model in zip(params, models):
-    # create geometry
-    geometry = model.default_geometry
-    param.process_geometry(geometry)
-    mesh = pybamm.Mesh(geometry, models[-1].default_submesh_types, var_pts)
-    disc = pybamm.Discretisation(mesh, model.default_spatial_methods)
-    disc.process_model(model)
-
-# solve model
-solutions = [None] * len(models)
+# set up and solve simulations
 t_eval = np.linspace(0, 3600, 100)
-for i, model in enumerate(models):
-    solutions[i] = pybamm.CasadiSolver().solve(model, t_eval)
-
+sols = []
+for model, param in zip(models, params):
+    sim = pybamm.Simulation(model, parameter_values=param)
+    sol = sim.solve(t_eval)
+    sols.append(sol)
 
 output_variables = [
     "Negative particle surface concentration",
@@ -78,5 +50,5 @@ def positive_distribution(x):
 ]
 
 # plot
-plot = pybamm.QuickPlot(solutions, output_variables=output_variables)
+plot = pybamm.QuickPlot(sols, output_variables=output_variables)
 plot.dynamic_plot()
@@ -0,0 +1,53 @@
+#
+# Example showing how to prescribe the surface area per unit volume independent of
+# the assumed particle shape. Setting the "particle shape" option to "user" returns
+# a model which solves a spherical diffusion problem in the particles, but passes
+# a user supplied surface area per unit volume
+#
+
+import pybamm
+import numpy as np
+
+pybamm.set_logging_level("INFO")
+
+models = [
+    pybamm.lithium_ion.DFN({"particle shape": "spherical"}, name="spherical"),
+    pybamm.lithium_ion.DFN({"particle shape": "user"}, name="user"),
+]
+params = [models[0].default_parameter_values, models[0].default_parameter_values]
+
+# set up and solve simulations
+solutions = []
+t_eval = np.linspace(0, 3600, 100)
+
+for model, param in zip(models, params):
+    if model.name == "user":
+        # add the user supplied parameters
+        param.update(
+            {
+                "Negative electrode surface area to volume ratio [m-1]": 170000,
+                "Positive electrode surface area to volume ratio [m-1]": 200000,
+                "Negative surface area per unit volume distribution in x": 1,
+                "Positive surface area per unit volume distribution in x": 1,
+            },
+            check_already_exists=False,
+        )
+
+    sim = pybamm.Simulation(model, parameter_values=param)
+    solution = sim.solve(t_eval)
+    solutions.append(solution)
+
+# plot solutions
+pybamm.dynamic_plot(
+    solutions,
+    [
+        "Negative particle surface concentration [mol.m-3]",
+        "Positive particle surface concentration [mol.m-3]",
+        "Negative electrode interfacial current density [A.m-2]",
+        "Positive electrode interfacial current density [A.m-2]",
+        "Negative electrode potential [V]",
+        "Electrolyte potential [V]",
+        "Positive electrode potential [V]",
+        "Terminal voltage [V]",
+    ],
+)