Make basic models compatible with experiments

CHANGELOG.md

@@ -2,6 +2,7 @@
 
 ## Features
 
+- "Basic" models are now compatible with experiments ([#3995](https://github.com/pybamm-team/PyBaMM/pull/3995))
 - Updates multiprocess `Pool` in `BaseSolver.solve()` to be constructed with context `fork`. Adds small example for multiprocess inputs. ([#3974](https://github.com/pybamm-team/PyBaMM/pull/3974))
 - Added custom experiment steps ([#3835](https://github.com/pybamm-team/PyBaMM/pull/3835))
 - Added support for macOS arm64 (M-series) platforms. ([#3789](https://github.com/pybamm-team/PyBaMM/pull/3789))

pybamm/models/full_battery_models/lithium_ion/basic_dfn.py

@@ -34,6 +34,7 @@ def __init__(self, name="Doyle-Fuller-Newman model"):
         ######################
         # Variables that depend on time only are created without a domain
         Q = pybamm.Variable("Discharge capacity [A.h]")
+
         # Variables that vary spatially are created with a domain
         c_e_n = pybamm.Variable(
             "Negative electrolyte concentration [mol.m-3]",
@@ -240,21 +241,39 @@ def __init__(self, name="Doyle-Fuller-Newman model"):
         # (Some) variables
         ######################
         voltage = pybamm.boundary_value(phi_s_p, "right")
+        num_cells = pybamm.Parameter(
+            "Number of cells connected in series to make a battery"
+        )
         # The `variables` dictionary contains all variables that might be useful for
         # visualising the solution of the model
         self.variables = {
+            "Negative particle concentration [mol.m-3]": c_s_n,
             "Negative particle surface concentration [mol.m-3]": c_s_surf_n,
             "Electrolyte concentration [mol.m-3]": c_e,
+            "Negative electrolyte concentration [mol.m-3]": c_e_n,
+            "Separator electrolyte concentration [mol.m-3]": c_e_s,
+            "Positive electrolyte concentration [mol.m-3]": c_e_p,
+            "Positive particle concentration [mol.m-3]": c_s_p,
             "Positive particle surface concentration [mol.m-3]": c_s_surf_p,
             "Current [A]": I,
+            "Current variable [A]": I,  # for compatibility with pybamm.Experiment
             "Negative electrode potential [V]": phi_s_n,
             "Electrolyte potential [V]": phi_e,
+            "Negative electrolyte potential [V]": phi_e_n,
+            "Separator electrolyte potential [V]": phi_e_s,
+            "Positive electrolyte potential [V]": phi_e_p,
             "Positive electrode potential [V]": phi_s_p,
             "Voltage [V]": voltage,
+            "Battery voltage [V]": voltage * num_cells,
             "Time [s]": pybamm.t,
+            "Discharge capacity [A.h]": Q,
         }
         # Events specify points at which a solution should terminate
         self.events += [
             pybamm.Event("Minimum voltage [V]", voltage - param.voltage_low_cut),
             pybamm.Event("Maximum voltage [V]", param.voltage_high_cut - voltage),
         ]
+        # Summary variables is a list of variables that can be accessed and plotted
+        # per-cycle when running experiments. Typically used to track degradation
+        # variables (e.g LAM, LLI, capacity fade, etc.)
+        self.summary_variables = ["Time [s]", "Voltage [V]"]

pybamm/models/full_battery_models/lithium_ion/basic_dfn_composite.py

@@ -341,18 +341,40 @@
         ocp_av_p = pybamm.x_average(ocp_p)
         a_j_n_p1_av = pybamm.x_average(a_j_n_p1)
         a_j_n_p2_av = pybamm.x_average(a_j_n_p2)
+        num_cells = pybamm.Parameter(
+            "Number of cells connected in series to make a battery"
+        )
         # The `variables` dictionary contains all variables that might be useful for
         # visualising the solution of the model
         self.variables = {
             "Negative primary particle concentration [mol.m-3]": c_s_n_p1,
             "Negative secondary particle concentration [mol.m-3]": c_s_n_p2,
+            "R-averaged negative primary particle concentration "
+            "[mol.m-3]": c_s_rav_n_p1,
+            "R-averaged negative secondary particle concentration "
+            "[mol.m-3]": c_s_rav_n_p2,
+            "Average negative primary particle concentration "
+            "[mol.m-3]": c_s_xrav_n_p1,
+            "Average negative secondary particle concentration "
+            "[mol.m-3]": c_s_xrav_n_p2,
+            "Positive particle concentration [mol.m-3]": c_s_p,
+            "Average positive particle concentration [mol.m-3]": c_s_xrav_p,
+            "Electrolyte concentration [mol.m-3]": c_e,
+            "Negative electrolyte concentration [mol.m-3]": c_e_n,
+            "Separator electrolyte concentration [mol.m-3]": c_e_s,
+            "Positive electrolyte concentration [mol.m-3]": c_e_p,
             "Negative electrode potential [V]": phi_s_n,
-            "Electrolyte potential [V]": phi_e,
             "Positive electrode potential [V]": phi_s_p,
+            "Electrolyte potential [V]": phi_e,
+            "Negative electrolyte potential [V]": phi_e_n,
+            "Separator electrolyte potential [V]": phi_e_s,
+            "Positive electrolyte potential [V]": phi_e_p,
             "Current [A]": I,
+            "Current variable [A]": I,  # for compatibility with pybamm.Experiment
             "Discharge capacity [A.h]": Q,
             "Time [s]": pybamm.t,
             "Voltage [V]": voltage,
+            "Battery voltage [V]": voltage * num_cells,
             "Negative electrode primary open-circuit potential [V]": ocp_n_p1,
             "Negative electrode secondary open-circuit potential [V]": ocp_n_p2,
             "X-averaged negative electrode primary open-circuit potential "
@@ -361,15 +383,6 @@
             "[V]": ocp_av_n_p2,
             "Positive electrode open-circuit potential [V]": ocp_p,
             "X-averaged positive electrode open-circuit potential [V]": ocp_av_p,
-            "R-averaged negative primary particle concentration "
-            "[mol.m-3]": c_s_rav_n_p1,
-            "R-averaged negative secondary particle concentration "
-            "[mol.m-3]": c_s_rav_n_p2,
-            "Average negative primary particle concentration "
-            "[mol.m-3]": c_s_xrav_n_p1,
-            "Average negative secondary particle concentration "
-            "[mol.m-3]": c_s_xrav_n_p2,
-            "Average positive particle concentration [mol.m-3]": c_s_xrav_p,
             "Negative electrode primary interfacial current density [A.m-2]": j_n_p1,
             "Negative electrode secondary interfacial current density [A.m-2]": j_n_p2,
             "X-averaged negative electrode primary interfacial current density "
@@ -385,7 +398,16 @@
             "X-averaged negative electrode secondary volumetric "
             "interfacial current density [A.m-3]": a_j_n_p2_av,
         }
+        # Events specify points at which a solution should terminate
         self.events += [
             pybamm.Event("Minimum voltage [V]", voltage - param.voltage_low_cut),
             pybamm.Event("Maximum voltage [V]", param.voltage_high_cut - voltage),
         ]
+        # Summary variables is a list of variables that can be accessed and plotted
+        # per-cycle when running experiments. Typically used to track degradation
+        # variables (e.g LAM, LLI, capacity fade, etc.)
+        self.summary_variables = ["Time [s]", "Voltage [V]"]
+
+    @property
+    def default_parameter_values(self):
+        return pybamm.ParameterValues("Chen2020_composite")

pybamm/models/full_battery_models/lithium_ion/basic_dfn_half_cell.py

@@ -244,6 +244,10 @@ def __init__(self, options=None, name="Doyle-Fuller-Newman half cell model"):
         vdrop_cell = pybamm.boundary_value(phi_s_w, "right") - ref_potential
         vdrop_Li = -eta_Li - delta_phis_Li
         voltage = vdrop_cell + vdrop_Li
+        num_cells = pybamm.Parameter(
+            "Number of cells connected in series to make a battery"
+        )
+
         c_e_total = pybamm.x_average(eps * c_e)
         c_s_surf_w_av = pybamm.x_average(c_s_surf_w)
 
@@ -286,16 +290,26 @@ def __init__(self, options=None, name="Doyle-Fuller-Newman half cell model"):
             "Positive particle concentration [mol.m-3]": c_s_w,
             "Total lithium in positive electrode [mol]": c_s_vol_av * L_w * param.A_cc,
             "Electrolyte concentration [mol.m-3]": c_e,
+            "Separator electrolyte concentration [mol.m-3]": c_e_s,
+            "Positive electrolyte concentration [mol.m-3]": c_e_w,
             "Total lithium in electrolyte [mol]": c_e_total * param.L_x * param.A_cc,
             "Current [A]": I,
+            "Current variable [A]": I,  # for compatibility with pybamm.Experiment
             "Current density [A.m-2]": i_cell,
             "Positive electrode potential [V]": phi_s_w,
             "Positive electrode open-circuit potential [V]": U_w(sto_surf_w, T),
             "Electrolyte potential [V]": phi_e,
+            "Separator electrolyte potential [V]": phi_e_s,
+            "Positive electrolyte potential [V]": phi_e_w,
             "Voltage drop in the cell [V]": vdrop_cell,
             "Negative electrode exchange current density [A.m-2]": j_Li,
             "Negative electrode reaction overpotential [V]": eta_Li,
             "Negative electrode potential drop [V]": delta_phis_Li,
             "Voltage [V]": voltage,
+            "Battery voltage [V]": voltage * num_cells,
             "Instantaneous power [W.m-2]": i_cell * voltage,
         }
+        # Summary variables is a list of variables that can be accessed and plotted
+        # per-cycle when running experiments. Typically used to track degradation
+        # variables (e.g LAM, LLI, capacity fade, etc.)
+        self.summary_variables = ["Time [s]", "Voltage [V]"]

pybamm/models/full_battery_models/lithium_ion/basic_spm.py

@@ -139,26 +139,33 @@ def __init__(self, name="Single Particle Model"):
         phi_e = -eta_n - param.n.prim.U(sto_surf_n, T)
         phi_s_p = eta_p + phi_e + param.p.prim.U(sto_surf_p, T)
         V = phi_s_p
+        num_cells = pybamm.Parameter(
+            "Number of cells connected in series to make a battery"
+        )
 
         whole_cell = ["negative electrode", "separator", "positive electrode"]
         # The `variables` dictionary contains all variables that might be useful for
         # visualising the solution of the model
         # Primary broadcasts are used to broadcast scalar quantities across a domain
         # into a vector of the right shape, for multiplying with other vectors
         self.variables = {
+            "Time [s]": pybamm.t,
             "Discharge capacity [A.h]": Q,
+            "X-averaged negative particle concentration [mol.m-3]": c_s_n,
             "Negative particle surface "
             "concentration [mol.m-3]": pybamm.PrimaryBroadcast(
                 c_s_surf_n, "negative electrode"
             ),
             "Electrolyte concentration [mol.m-3]": pybamm.PrimaryBroadcast(
                 param.c_e_init_av, whole_cell
             ),
+            "X-averaged positive particle concentration [mol.m-3]": c_s_p,
             "Positive particle surface "
             "concentration [mol.m-3]": pybamm.PrimaryBroadcast(
                 c_s_surf_p, "positive electrode"
             ),
             "Current [A]": I,
+            "Current variable [A]": I,  # for compatibility with pybamm.Experiment
             "Negative electrode potential [V]": pybamm.PrimaryBroadcast(
                 phi_s_n, "negative electrode"
             ),
@@ -167,8 +174,14 @@ def __init__(self, name="Single Particle Model"):
                 phi_s_p, "positive electrode"
             ),
             "Voltage [V]": V,
+            "Battery voltage [V]": V * num_cells,
         }
+        # Events specify points at which a solution should terminate
         self.events += [
             pybamm.Event("Minimum voltage [V]", V - param.voltage_low_cut),
             pybamm.Event("Maximum voltage [V]", param.voltage_high_cut - V),
         ]
+        # Summary variables is a list of variables that can be accessed and plotted
+        # per-cycle when running experiments. Typically used to track degradation
+        # variables (e.g LAM, LLI, capacity fade, etc.)
+        self.summary_variables = ["Time [s]", "Voltage [V]"]

pybamm/simulation.py

@@ -81,12 +81,6 @@ def __init__(
         self._parameter_values = parameter_values or model.default_parameter_values
         self._unprocessed_parameter_values = self._parameter_values
 
-        if isinstance(model, pybamm.lithium_ion.BasicDFNHalfCell):
-            if experiment is not None:
-                raise NotImplementedError(
-                    "BasicDFNHalfCell is not compatible with experiment simulations."
-                )
-
         if experiment is None:
             # Check to see if the current is provided as data (i.e. drive cycle)
             current = self._parameter_values.get("Current function [A]")

pybamm/solvers/solution.py

@@ -974,6 +974,8 @@ def _get_cycle_summary_variables(cycle_solution, esoh_solver, user_inputs=None):
         esoh_solver is not None
         and isinstance(model, pybamm.lithium_ion.BaseModel)
         and model.options.electrode_types["negative"] == "porous"
+        and "Negative electrode capacity [A.h]" in model.variables
+        and "Positive electrode capacity [A.h]" in model.variables
     ):
         Q_n = last_state["Negative electrode capacity [A.h]"].data[0]
         Q_p = last_state["Positive electrode capacity [A.h]"].data[0]

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

@@ -0,0 +1,51 @@
+#
+# Test basic model classes
+#
+from tests import TestCase
+import pybamm
+
+import unittest
+
+
+class BaseBasicModelTest:
+    def test_with_experiment(self):
+        model = self.model
+        experiment = pybamm.Experiment(
+            [
+                "Discharge at C/3 until 3.5V",
+                "Hold at 3.5V for 1 hour",
+                "Rest for 10 min",
+            ]
+        )
+        sim = pybamm.Simulation(model, experiment=experiment)
+        sim.solve(calc_esoh=False)
+
+
+class TestBasicSPM(BaseBasicModelTest, TestCase):
+    def setUp(self):
+        self.model = pybamm.lithium_ion.SPM()
+
+
+class TestBasicDFN(BaseBasicModelTest, TestCase):
+    def setUp(self):
+        self.model = pybamm.lithium_ion.DFN()
+
+
+class TestBasicDFNComposite(BaseBasicModelTest, TestCase):
+    def setUp(self):
+        self.model = pybamm.lithium_ion.BasicDFNComposite()
+
+
+class TestBasicDFNHalfCell(BaseBasicModelTest, TestCase):
+    def setUp(self):
+        options = {"working electrode": "positive"}
+        self.model = pybamm.lithium_ion.BasicDFNHalfCell(options)
+
+
+if __name__ == "__main__":
+    print("Add -v for more debug output")
+    import sys
+
+    if "-v" in sys.argv:
+        debug = True
+    unittest.main()