fixed tests

examples/scripts/compare_lithium_ion_half_cell.py

@@ -7,9 +7,9 @@
 
 # load models
 models = [
-    pybamm.lithium_ion.SPM({"working electrode": "positive"}),
-    pybamm.lithium_ion.SPMe({"working electrode": "positive"}),
-    pybamm.lithium_ion.DFN({"working electrode": "positive"}),
+    pybamm.lithium_ion.SPM({"half-cell": "true"}),
+    pybamm.lithium_ion.SPMe({"half-cell": "true"}),
+    pybamm.lithium_ion.DFN({"half-cell": "true"}),
 ]
 
 # create and run simulations

pybamm/expression_tree/averages.py

@@ -273,7 +273,7 @@ def r_average(symbol):
     # "positive electrode", take the r-average of the child then broadcast back
     elif isinstance(symbol, pybamm.SecondaryBroadcast) and symbol.domains[
         "secondary"
-    ] in [["positive electrode"], ["negative electrode"], ["working electrode"]]:
+    ] in [["positive electrode"], ["negative electrode"]]:
         child = symbol.orphans[0]
         child_av = pybamm.r_average(child)
         return pybamm.PrimaryBroadcast(child_av, symbol.domains["secondary"])

pybamm/models/full_battery_models/base_battery_model.py

@@ -49,6 +49,10 @@ class BatteryModelOptions(pybamm.FuzzyDict):
             * "electrolyte conductivity" : str
                 Can be "default" (default), "full", "leading order", "composite" or
                 "integrated".
+            * "half-cell" : str
+                Can be "false" (default) for a standard battery or "true" for a 
+                half-cell where the negative electrode is replaced with a lithium metal
+                counter electrode.
             * "hydrolysis" : str
                 Whether to include hydrolysis in the model. Only implemented for
                 lead-acid models. Can be "false" (default) or "true". If "true", then
@@ -168,10 +172,6 @@ class BatteryModelOptions(pybamm.FuzzyDict):
                 solve an algebraic equation for it. Default is "false", unless "SEI film
                 resistance" is distributed in which case it is automatically set to
                 "true".
-            * "working electrode": str
-                Which electrode(s) intercalates and which is counter. If "both"
-                (default), the model is a standard battery. Otherwise can be "negative"
-                or "positive" to indicate a half-cell model.
             * "x-average side reactions": str
                 Whether to average the side reactions (SEI growth, lithium plating and
                 the respective porosity change) over the x-axis in Single Particle
@@ -199,6 +199,7 @@ def __init__(self, extra_options):
                 "composite",
                 "integrated",
             ],
+            "half-cell": ["false", "true"],
             "hydrolysis": ["false", "true"],
             "intercalation kinetics": [
                 "symmetric Butler-Volmer",
@@ -262,7 +263,6 @@ def __init__(self, extra_options):
             "surface form": ["false", "differential", "algebraic"],
             "thermal": ["isothermal", "lumped", "x-lumped", "x-full"],
             "total interfacial current density as a state": ["false", "true"],
-            "working electrode": ["both", "negative", "positive"],
             "x-average side reactions": ["false", "true"],
         }
 
@@ -495,7 +495,7 @@ def __init__(self, extra_options):
                     "mechanics model"
                 )
 
-        if options["working electrode"] != "both":
+        if options["half-cell"] == "true":
             if options["thermal"] == "x-full":
                 raise pybamm.OptionError(
                     "X-full thermal submodel is not compatible with half-cell models"
@@ -506,10 +506,6 @@ def __init__(self, extra_options):
                     f"X-lumped thermal submodels do not yet support {n}D "
                     "current collectors in a half-cell configuration"
                 )
-            elif options["SEI on cracks"] == "true":
-                raise NotImplementedError(
-                    "SEI on cracks not yet implemented for half-cell models"
-                )
 
         if options["particle phases"] != "1":
             if not (
@@ -530,7 +526,7 @@ def __init__(self, extra_options):
 
         # Check options are valid
         for option, value in options.items():
-            if option in ["working electrode"]:
+            if option in ["half-cell"]:  # is this exception still necessary?
                 pass
             else:
                 if isinstance(value, str) or option in [
@@ -597,11 +593,9 @@ def phases(self):
 
     @cached_property
     def whole_cell_domains(self):
-        if self["working electrode"] == "positive":
+        if self["half-cell"] == "true":
             return ["separator", "positive electrode"]
-        elif self["working electrode"] == "negative":
-            return ["negative electrode", "separator"]
-        elif self["working electrode"] == "both":
+        else:
             return ["negative electrode", "separator", "positive electrode"]
 
     @property

pybamm/models/full_battery_models/lithium_ion/basic_dfn_half_cell.py

@@ -38,11 +38,6 @@ class BasicDFNHalfCell(BaseModel):
 
     def __init__(self, options=None, name="Doyle-Fuller-Newman half cell model"):
         super().__init__(options, name)
-        if self.options["working electrode"] not in ["negative", "positive"]:
-            raise ValueError(
-                "The option 'working electrode' should be either 'positive'"
-                " or 'negative'"
-            )
         pybamm.citations.register("Marquis2019")
         # `param` is a class containing all the relevant parameters and functions for
         # this model. These are purely symbolic at this stage, and will be set by the

pybamm/models/full_battery_models/lithium_ion/electrode_soh_half_cell.py

@@ -25,21 +25,17 @@ class ElectrodeSOHHalfCell(pybamm.BaseModel):
            expansion. Journal of Power Sources, 427, 101-111.
     """
 
-    def __init__(self, working_electrode, name="Electrode-specific SOH model"):
-        self.working_electrode = working_electrode
+    def __init__(self, name="Electrode-specific SOH model"):
         pybamm.citations.register("Mohtat2019")
         super().__init__(name)
-        param = pybamm.LithiumIonParameters({"working electrode": working_electrode})
+        param = pybamm.LithiumIonParameters({"half-cell": "true"})
 
         x_100 = pybamm.Variable("x_100", bounds=(0, 1))
         x_0 = pybamm.Variable("x_0", bounds=(0, 1))
         Q_w = pybamm.InputParameter("Q_w")
         T_ref = param.T_ref
-        if working_electrode == "negative":  # pragma: no cover
-            raise NotImplementedError
-        elif working_electrode == "positive":
-            U_w = param.p.prim.U
-            Q = Q_w * (x_100 - x_0)
+        U_w = param.p.prim.U
+        Q = Q_w * (x_100 - x_0)
 
         V_max = param.voltage_high_cut
         V_min = param.voltage_low_cut

pybamm/models/full_battery_models/lithium_ion/mpm.py

@@ -53,6 +53,6 @@ def __init__(self, options=None, name="Many-Particle Model", build=True):
     def default_parameter_values(self):
         default_params = super().default_parameter_values
         default_params = pybamm.get_size_distribution_parameters(
-            default_params, electrode=self.options["working electrode"]
+            default_params, halfcell=self.options["half-cell"]
         )
         return default_params

pybamm/models/full_battery_models/lithium_metal/dfn.py

@@ -29,7 +29,7 @@ def __init__(
         self, options=None, name="Doyle-Fuller-Newman lithium metal model", build=True
     ):
         options = options or {}
-        options["working electrode"] = "positive"
+        options["half-cell"] = "positive"
         super().__init__(options, name, build=False)
 
         if build:

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

@@ -30,40 +30,45 @@ def __init__(self, param, options, phase="primary", cracks=False):
 
     def get_coupled_variables(self, variables):
         # Update some common variables
+        zero_av = pybamm.PrimaryBroadcast(0, "current collector")
+        zero = pybamm.FullBroadcast(0, "positive electrode", "current collector")
 
         if self.reaction_loc != "interface":
-            j_sei_av = variables[
-                f"X-averaged {self.reaction_name}interfacial current density [A.m-2]"
-            ]
-            j_sei = variables[
-                f"{self.reaction_name}interfacial current density [A.m-2]"
-            ]
             variables.update(
                 {
                     f"X-averaged negative electrode {self.reaction_name}interfacial "
-                    "current density [A.m-2]": j_sei_av,
+                    "current density": variables[
+                        f"X-averaged {self.reaction_name}interfacial current density"
+                    ],
+                    f"Negative electrode {self.reaction_name}interfacial current "
+                    "density": variables[
+                        f"{self.reaction_name}interfacial current density"
+                    ],
                     f"Negative electrode {self.reaction_name}interfacial current "
-                    "density [A.m-2]": j_sei,
+                    "density [A.m-2]": variables[
+                        f"{self.reaction_name}interfacial current density [A.m-2]"
+                    ],
                 }
             )
+            variables.update(
+                self._get_standard_volumetric_current_density_variables(variables)
+            )
 
-        zero_av = pybamm.PrimaryBroadcast(0, "current collector")
-        zero = pybamm.FullBroadcast(0, "positive electrode", "current collector")
         variables.update(
             {
+                f"X-averaged positive electrode {self.reaction} "
+                "interfacial current density": zero_av,
+                f"Positive electrode {self.reaction} "
+                "interfacial current density": zero,
                 f"Positive electrode {self.reaction} "
                 "interfacial current density [A.m-2]": zero,
                 f"X-averaged positive electrode {self.reaction} "
-                "volumetric interfacial current density [A.m-2]": zero_av,
+                "volumetric interfacial current density": zero_av,
                 f"Positive electrode {self.reaction} "
-                "volumetric interfacial current density [A.m-3]": zero,
+                "volumetric interfacial current density": zero,
             }
         )
 
-        variables.update(
-            self._get_standard_volumetric_current_density_variables(variables)
-        )
-
         return variables
 
     def _get_standard_thickness_variables(self, L_inner, L_outer):
@@ -157,7 +162,7 @@ def _get_standard_concentration_variables(self, variables):
             else:
                 # m * (mol/m4) = mol/m3 (n is a bulk quantity)
                 a = variables[
-                    f"Negative electrode {self.phase_name}"
+                    f"{Domain} electrode {self.phase_name}"
                     "surface area to volume ratio [m-1]"
                 ]
                 L_to_n_inner = a / phase_param.V_bar_inner

pybamm/parameters/lithium_ion_parameters.py

@@ -16,14 +16,14 @@ class LithiumIonParameters(BaseParameters):
         A dictionary of options to be passed to the parameters. The options that
         can be set are listed below.
 
+            * "half-cell": str
+                Can be "false" (default) for a standard battery or "true" for a
+                half-cell where the negative electrode is replaced with a lithium metal
+                counter electrode.
             * "particle shape" : str, optional
                 Sets the model shape of the electrode particles. This is used to
                 calculate the surface area to volume ratio. Can be "spherical"
                 (default). TODO: implement "cylindrical" and "platelet".
-            * "working electrode": str
-                Which electrode(s) intercalates and which is counter. If "both"
-                (default), the model is a standard battery. Otherwise can be "negative"
-                or "positive" to indicate a half-cell model.
 
     """
 

pybamm/parameters/size_distribution_parameters.py

@@ -16,7 +16,7 @@ def get_size_distribution_parameters(
     R_min_p=None,
     R_max_n=None,
     R_max_p=None,
-    electrode="both",
+    halfcell="false",
 ):
     """
     A convenience method to add standard area-weighted particle-size distribution
@@ -60,7 +60,7 @@ def get_size_distribution_parameters(
         "positive" to indicate a half-cell model, in which case size distribution
         parameters are only added for a single electrode.
     """
-    if electrode in ["both", "negative"]:
+    if halfcell == "false":
         # Radii from given parameter set
         R_n_typ = param["Negative particle radius [m]"]
 
@@ -89,35 +89,33 @@ def f_a_dist_n(R):
             },
             check_already_exists=False,
         )
-    if electrode in ["both", "positive"]:
-        # Radii from given parameter set
-        R_p_typ = param["Positive particle radius [m]"]
-
-        # Set the mean particle radii
-        R_p_av = R_p_av or R_p_typ
-
-        # Minimum radii
-        R_min_p = R_min_p or np.max([0, 1 - sd_p * 5])
-
-        # Max radii
-        R_max_p = R_max_p or (1 + sd_p * 5)
-
-        # Area-weighted particle-size distribution
-        def f_a_dist_p(R):
-            return lognormal(R, R_p_av, sd_p * R_p_av)
-
-        param.update(
-            {
-                "Positive area-weighted mean particle radius [m]": R_p_av,
-                "Positive area-weighted particle-size "
-                + "standard deviation [m]": sd_p * R_p_av,
-                "Positive minimum particle radius [m]": R_min_p * R_p_av,
-                "Positive maximum particle radius [m]": R_max_p * R_p_av,
-                "Positive area-weighted "
-                + "particle-size distribution [m-1]": f_a_dist_p,
-            },
-            check_already_exists=False,
-        )
+    # Radii from given parameter set
+    R_p_typ = param["Positive particle radius [m]"]
+
+    # Set the mean particle radii
+    R_p_av = R_p_av or R_p_typ
+
+    # Minimum radii
+    R_min_p = R_min_p or np.max([0, 1 - sd_p * 5])
+
+    # Max radii
+    R_max_p = R_max_p or (1 + sd_p * 5)
+
+    # Area-weighted particle-size distribution
+    def f_a_dist_p(R):
+        return lognormal(R, R_p_av, sd_p * R_p_av)
+
+    param.update(
+        {
+            "Positive area-weighted mean particle radius [m]": R_p_av,
+            "Positive area-weighted particle-size "
+            + "standard deviation [m]": sd_p * R_p_av,
+            "Positive minimum particle radius [m]": R_min_p * R_p_av,
+            "Positive maximum particle radius [m]": R_max_p * R_p_av,
+            "Positive area-weighted " + "particle-size distribution [m-1]": f_a_dist_p,
+        },
+        check_already_exists=False,
+    )
     return param
 
 

pybamm/simulation.py

@@ -934,7 +934,7 @@ def _get_esoh_solver(self, calc_esoh):
             calc_esoh is False
             or isinstance(self.model, pybamm.lead_acid.BaseModel)
             or isinstance(self.model, pybamm.equivalent_circuit.Thevenin)
-            or self.model.options["working electrode"] != "both"
+            or self.model.options["half-cell"] == "true"
         ):
             return None
 

tests/integration/test_models/test_full_battery_models/test_lithium_ion/base_lithium_ion_half_cell_tests.py

@@ -7,7 +7,7 @@
 
 class BaseIntegrationTestLithiumIonHalfCell:
     def run_basic_processing_test(self, options, **kwargs):
-        options["working electrode"] = "positive"
+        options["half-cell"] = "true"
         model = self.model(options)
         modeltest = tests.StandardModelTest(model, **kwargs)
         modeltest.test_all(skip_output_tests=True)

tests/integration/test_models/test_full_battery_models/test_lithium_ion/test_basic_half_cell_models.py

@@ -10,7 +10,7 @@
 
 class TestBasicHalfCellModels(TestCase):
     def test_runs_Xu2019(self):
-        options = {"working electrode": "positive"}
+        options = {"half-cell": "true"}
         model = pybamm.lithium_ion.BasicDFNHalfCell(options=options)
 
         # create geometry
@@ -40,7 +40,7 @@ def test_runs_Xu2019(self):
 
     def test_runs_OKane2022(self):
         # load model
-        options = {"working electrode": "positive"}
+        options = {"half-cell": "true"}
         model = pybamm.lithium_ion.BasicDFNHalfCell(options=options)
 
         # create geometry

tests/unit/test_experiments/test_simulation_with_experiment.py

@@ -583,7 +583,7 @@ def test_run_experiment_half_cell(self):
         experiment = pybamm.Experiment(
             [("Discharge at C/20 until 3.5V", "Charge at 1C until 3.8 V")]
         )
-        model = pybamm.lithium_ion.SPM({"working electrode": "positive"})
+        model = pybamm.lithium_ion.SPM({"half-cell": "true"})
         sim = pybamm.Simulation(
             model,
             experiment=experiment,