example implementation with GITT class

pybop-team · Apr 9, 2024 · c55b2a3 · c55b2a3
1 parent 2f6a0e7
commit c55b2a3
Show file tree

Hide file tree

Showing 2 changed files with 22 additions and 20 deletions.
diff --git a/examples/scripts/gitt.py b/examples/scripts/gitt.py
@@ -23,6 +23,16 @@
     }
 )
 
+# Define diffusion parameter for fitting
+parameters = [
+    pybop.Parameter(
+        "Positive electrode diffusivity [m2.s-1]",
+        prior=pybop.Gaussian(5e-14, 1e-13),
+        bounds=[1e-16, 1e-11],
+        true_value=parameter_set["Positive electrode diffusivity [m2.s-1]"],
+    ),
+]
+
 # Define parameter set
 parameter_set.update(
     {
@@ -32,9 +42,12 @@
     check_already_exists=False,
 )
 
+# Weppner & Huggins model
+wep_huggins_model = pybop.lithium_ion.WeppnerHuggins(parameter_set=parameter_set)
+
 # Define the cost to optimise
-problem = pybop.GITT(
-    model="Weppner & Huggins", parameter_set=parameter_set, dataset=dataset
+problem = pybop.FittingProblem(
+    model=wep_huggins_model, parameters=parameters, dataset=dataset
 )
 cost = pybop.RootMeanSquaredError(problem)
 

diff --git a/pybop/models/lithium_ion/weppner_huggins.py b/pybop/models/lithium_ion/weppner_huggins.py
@@ -36,11 +36,7 @@ def __init__(self, name="Weppner & Huggins model"):
         # `ParameterValues` class when the model is processed.
         self.options["working electrode"] = "positive"
 
-        t = pybamm.t
-        ######################
         # Parameters
-        ######################
-
         d_s = pybamm.Parameter("Positive electrode diffusivity [m2.s-1]")
 
         c_s_max = pybamm.Parameter(
@@ -49,34 +45,27 @@ def __init__(self, name="Weppner & Huggins model"):
 
         i_app = self.param.current_density_with_time
 
-        U = pybamm.Parameter("Reference OCP [V]")
-
-        U_prime = pybamm.Parameter("Derivative of the OCP wrt stoichiometry [V]")
+        u_prime = pybamm.Parameter("Derivative of the OCP wrt stoichiometry [V]")
 
         epsilon = pybamm.Parameter("Positive electrode active material volume fraction")
 
         r_particle = pybamm.Parameter("Positive particle radius [m]")
 
         a = 3 * (epsilon / r_particle)
 
-        l_w = self.param.p.L
-
-        ######################
         # Governing equations
-        ######################
         u_surf = (
             (2 / (np.pi**0.5))
-            * (i_app / ((d_s**0.5) * a * self.param.F * l_w))
-            * (t**0.5)
+            * (i_app / ((d_s**0.5) * a * self.param.F * self.param.p.L))
+            * (pybamm.t**0.5)
         )
         # Linearised voltage
-        V = U + (U_prime * u_surf) / c_s_max
-        ######################
-        # (Some) variables
-        ######################
+        V = pybamm.Parameter("Reference OCP [V]") + (u_prime * u_surf) / c_s_max
+
+        # Variables
         self.variables = {
             "Voltage [V]": V,
-            "Time [s]": t,
+            "Time [s]": pybamm.t,
         }
 
     @property