def test_update_initial_state_of_charge(self):
# Load parameters to be tested
parameters = pybamm.standard_parameters_lead_acid
parameter_values = pybamm.lead_acid.BaseModel().default_parameter_values
param_eval = pybamm.print_parameters(parameters, parameter_values)
param_eval = {k: v[0] for k, v in param_eval.items()}
# Update initial state of charge
parameter_values.update({"Initial State of Charge": 0.2})
param_eval_update = pybamm.print_parameters(parameters, parameter_values)
param_eval_update = {k: v[0] for k, v in param_eval_update.items()}
# Test that relevant parameters have changed as expected
self.assertLess(param_eval_update["q_init"], param_eval["q_init"])
self.assertLess(param_eval_update["c_e_init"], param_eval["c_e_init"])
self.assertLess(
param_eval_update["epsilon_n_init"], param_eval["epsilon_n_init"]
)
self.assertEqual(
param_eval_update["epsilon_s_init"], param_eval["epsilon_s_init"]
)
self.assertLess(
param_eval_update["epsilon_p_init"], param_eval["epsilon_p_init"]
)
self.assertGreater(
param_eval_update["curlyU_n_init"], param_eval["curlyU_n_init"]
)
self.assertGreater(
param_eval_update["curlyU_p_init"], param_eval["curlyU_p_init"]
)
def test_all_defined(self):
parameters = pybamm.standard_parameters_lead_acid
parameter_values = pybamm.lead_acid.BaseModel().default_parameter_values
output_file = "lead_acid_parameters.txt"
pybamm.print_parameters(parameters, parameter_values, output_file)
# test print_parameters with dict and without C-rate
del parameter_values["Cell capacity [A.h]"]
parameters = {
"C_e": pybamm.standard_parameters_lead_acid.C_e,
"sigma_n": pybamm.standard_parameters_lead_acid.sigma_n,
}
pybamm.print_parameters(parameters, parameter_values)
def test_parameters_defaults_lead_acid(self):
# Load parameters to be tested
parameters = pybamm.standard_parameters_lead_acid
parameter_values = pybamm.lead_acid.BaseModel().default_parameter_values
param_eval = pybamm.print_parameters(parameters, parameter_values)
param_eval = {k: v[0] for k, v in param_eval.items()}
# Diffusional C-rate should be smaller than C-rate
self.assertLess(param_eval["C_e"], param_eval["C_rate"])
# Dimensionless electrode conductivities should be large
self.assertGreater(param_eval["sigma_n"], 10)
self.assertGreater(param_eval["sigma_p"], 10)
# Dimensionless double-layer capacity should be small
self.assertLess(param_eval["C_dl_n"], 1e-3)
self.assertLess(param_eval["C_dl_p"], 1e-3)
# Volume change positive in negative electrode and negative in positive
# electrode
self.assertLess(param_eval["DeltaVsurf_n"], 0)
self.assertGreater(param_eval["DeltaVsurf_p"], 0)
def test_functions_lead_acid(self):
# Load parameters to be tested
parameters = {
"D_e_1":
pybamm.standard_parameters_lead_acid.D_e(pybamm.Scalar(1),
pybamm.Scalar(0)),
"kappa_e_0":
pybamm.standard_parameters_lead_acid.kappa_e(
pybamm.Scalar(0), pybamm.Scalar(0)),
"chi_1":
pybamm.standard_parameters_lead_acid.chi(pybamm.Scalar(1)),
"chi_0.5":
pybamm.standard_parameters_lead_acid.chi(pybamm.Scalar(0.5)),
"U_n_1":
pybamm.standard_parameters_lead_acid.U_n(pybamm.Scalar(1),
pybamm.Scalar(0)),
"U_n_0.5":
pybamm.standard_parameters_lead_acid.U_n(pybamm.Scalar(0.5),
pybamm.Scalar(0)),
"U_p_1":
pybamm.standard_parameters_lead_acid.U_p(pybamm.Scalar(1),
pybamm.Scalar(0)),
"U_p_0.5":
pybamm.standard_parameters_lead_acid.U_p(pybamm.Scalar(0.5),
pybamm.Scalar(0)),
}
# Process
parameter_values = pybamm.ParameterValues(
chemistry=pybamm.parameter_sets.Sulzer2019)
param_eval = pybamm.print_parameters(parameters, parameter_values)
param_eval = {k: v[0] for k, v in param_eval.items()}
# Known values for dimensionless functions
self.assertEqual(param_eval["D_e_1"], 1)
self.assertEqual(param_eval["kappa_e_0"], 0)
# Known monotonicity for dimensionless functions
self.assertGreater(param_eval["chi_1"], param_eval["chi_0.5"])
self.assertLess(param_eval["U_n_1"], param_eval["U_n_0.5"])
self.assertGreater(param_eval["U_p_1"], param_eval["U_p_0.5"])
# # Print parameters for lead-acid models # import pybamm parameters = pybamm.standard_parameters_lead_acid parameter_values = pybamm.lead_acid.BaseModel().default_parameter_values output_file = "results/2019_08_sulzer_thesis/parameters.txt" pybamm.print_parameters(parameters, parameter_values, output_file)
