#492 trying to get charging strategies working

Author: valentinsulzer

examples/scripts/charging_strategies.py

@@ -19,67 +19,94 @@
 else:
     pybamm.set_logging_level("INFO")
 
+
+class CCCV:
+    num_switches = 1
+
+    def __call__(self, variables):
+        # switch controls 1A charge vs 4.2V charge
+        # charging current is negative
+        a = variables["Switch 1"]
+        I = variables["Current [A]"]
+        V = variables["Terminal voltage [V]"]
+        return (a < 0.5) * (I + 1) + (a > 0.5) * (I)
+
+
+class CCCP:
+    num_switches = 1
+
+    def __call__(self, variables):
+        # switch controls 4W charge vs 4.2V charge
+        # charging current (and hence power) is negative
+        a = variables["Switch 1"]
+        I = variables["Current [A]"]
+        V = variables["Terminal voltage [V]"]
+        return (a * (V > 0) <= 0) * (I * V + 4) + (a * (V > 0) > 0) * (V - 4.2)
+
+
 # load models
 models = [
-    pybamm.lithium_ion.DFN({"operating mode": "custom"}),
-    pybamm.lithium_ion.DFN({"operating mode": "voltage"}),
-    pybamm.lithium_ion.DFN({"operating mode": "custom"}),
+    pybamm.lithium_ion.SPM({"operating mode": CCCV}, name="CCCV SPM"),
+    # pybamm.lithium_ion.DFN({"operating mode": "voltage"}, name="CV DFN"),
+    # pybamm.lithium_ion.DFN({"operating mode": CCCP}, name="CCCP DFN"),
 ]
 
 
 # load parameter values and process models and geometry
-params = [models[0].default_parameter_values] * 3
+params = [model.default_parameter_values for model in models]
 
 # 1. CC-CV: Charge at 1C ( A) to 4.2V then 4.2V hold
-a = pybamm.Parameter("CCCV switch")
+params[0]["Switch 1"] = 0
+params[0]["Upper voltage cut-off [V]"] = 4.15
 
+# # 2. CV: Charge at 4.1V
+# params[1]["Voltage function"] = 4.1
 
-def cccv(I, V):
-    # switch a controls 1A charge vs 4.2V charge
-    # charging current is negative
-    return a * (I + 1) + (1 - a) * (V - 4.2)
+# # 3. CP-CV: Charge at 4W to 4.2V then 4.2V hold
+# b = pybamm.Parameter("CCCP switch")
 
 
-params[0]["CCCV switch"] = 1  # start with CC
-params[0]["External circuit function"] = cccv
+# params[2]["CCCP switch"] = 1  # start with CP
+# params[2]["External circuit function"] = cccp
 
-# 2. CV: Charge at 4.1V
-params[1]["Voltage function"] = 4.1
 for model, param in zip(models, params):
     param.process_model(model)
 
-# 3. CP-CV: Charge at 4W to 4.2V then 4.2V hold
-b = pybamm.Parameter("CCCP switch")
-
-
-def cccp(I, V):
-    # switch a controls 1A charge vs 4.2V charge
-    # charging current is negative
-    return b * (I * V + 4) + (1 - b) * (V - 4.2)
-
-
-params[0]["CCCP switch"] = 1  # start with CP
-params[0]["External circuit function"] = cccp
-
 # 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
+discs = {}
 for model in models:
     # create geometry
+    model.convert_to_format = "python"
     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)
-t_eval = np.linspace(0, 0.3, 100)
-for i, model in enumerate(models):
-    solutions[i] = model.default_solver.solve(model, t_eval)
-
+    discs[model] = disc
+
+# solve models
+solver0 = model.default_solver
+solution0 = solver0.step(model, 1, npts=1000)
+params[0]["Switch 1"] = 1
+params[0]["Upper voltage cut-off [V]"] = 4.16
+params[0].update_model(models[0], discs[models[0]])
+solution0.append(solver0.step(model, 1 - solution0.t[-1], npts=1000))
+solutions = [solution0]
+# # Step
+# solution0 = models[0].default_solver.step(models[0], t_eval)
+# # Switch to CV
+# params[0].update({"CCCV switch": 0})
+# params[0].update_model(models[0], discs[models[0]])
+# # Step
+# solution0.append(models[0].default_solver.step(models[0], t_eval))
+
+# solution1 = models[1].default_solver.solve(models[1], t_eval)
+
+# solutions = [solution0, solution1]
 # plot
 output_variables = [
     "Negative particle surface concentration",
@@ -88,7 +115,7 @@ def cccp(I, V):
     "Current [A]",
     "Negative electrode potential [V]",
     "Electrolyte potential [V]",
-    "Terminal power [W]",
+    "Switch 1",
     "Terminal voltage [V]",
 ]
 plot = pybamm.QuickPlot(models, mesh, solutions, output_variables)

pybamm/models/full_battery_models/base_battery_model.py

@@ -157,7 +157,7 @@ def options(self, extra_options):
             "particle": "Fickian diffusion",
             "thermal": "isothermal",
             "thermal current collector": False,
-            "external submodels": []
+            "external submodels": [],
         }
         options = default_options
         # any extra options overwrite the default options
@@ -169,12 +169,10 @@ def options(self, extra_options):
                     raise pybamm.OptionError("option {} not recognised".format(name))
 
         # Some standard checks to make sure options are compatible
-        if options["operating mode"] not in [
-            "current",
-            "voltage",
-            "power",
-            "custom",
-        ]:
+        if not (
+            options["operating mode"] in ["current", "voltage", "power"]
+            or callable(options["operating mode"])
+        ):
             raise pybamm.OptionError(
                 "operating mode '{}' not recognised".format(options["operating mode"])
             )
@@ -543,10 +541,12 @@ def set_external_circuit_submodel(self):
             self.submodels["external circuit"] = pybamm.external_circuit.PowerControl(
                 self.param
             )
-        elif self.options["operating mode"] == "custom":
+        elif callable(self.options["operating mode"]):
             self.submodels[
                 "external circuit"
-            ] = pybamm.external_circuit.FunctionControl(self.param)
+            ] = pybamm.external_circuit.FunctionControl(
+                self.param, self.options["operating mode"]
+            )
 
     def set_tortuosity_submodels(self):
         self.submodels["electrolyte tortuosity"] = pybamm.tortuosity.Bruggeman(

pybamm/models/submodels/external_circuit/function_control_external_circuit.py

@@ -8,15 +8,9 @@
 class FunctionControl(BaseModel):
     """External circuit with an arbitrary function. """
 
-    def __init__(self, param):
+    def __init__(self, param, ExternalCircuitClass):
         super().__init__(param)
-
-    def external_circuit_function(self, I, V):
-        """
-        Function that fixes the current, I (in Amps), or voltage, V (in Volts), or a
-        combination of the two
-        """
-        return pybamm.FunctionParameter("External circuit function", I, V)
+        self.external_circuit_class = ExternalCircuitClass()
 
     def get_fundamental_variables(self):
         # Current is a variable
@@ -31,6 +25,11 @@ def get_fundamental_variables(self):
             "Current [A]": I,
         }
 
+        # Add switches
+        for i in range(self.external_circuit_class.num_switches):
+            s = pybamm.Parameter("Switch {}".format(i + 1))
+            variables["Switch {}".format(i + 1)] = s
+
         return variables
 
     def set_initial_conditions(self, variables):
@@ -43,6 +42,4 @@ def set_algebraic(self, variables):
         # The external circuit function should fix either the current, or the voltage,
         # or a combination (e.g. I*V for power control)
         i_cell = variables["Total current density"]
-        I = variables["Current [A]"]
-        V = variables["Terminal voltage [V]"]
-        self.algebraic[i_cell] = self.external_circuit_function(I, V)
+        self.algebraic[i_cell] = self.external_circuit_class(variables)