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Solve Drive Cycle (A,V,W) in Experiment #1524

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Nov 10, 2021
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Solve Drive Cycle (A,V,W) in Experiment #1524

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b1a9184
Simulate Drive Cycle In Experiment
alibh95 Apr 28, 2021
351183b
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alibh95 Jun 25, 2021
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87 changes: 87 additions & 0 deletions examples/scripts/experiment_drive_cycle.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,87 @@
#
# Constant-current constant-voltage charge with US06 Drive Cycle using Experiment Class.
#
import pybamm
import pandas as pd
import os

os.chdir(pybamm.__path__[0] + "/..")

pybamm.set_logging_level("INFO")

# import drive cycle from file
drive_cycle_current = pd.read_csv("pybamm/input/drive_cycles/US06.csv",
comment="#",
header=None).to_numpy()


# Map Drive Cycle
def Map_Drive_Cycle(x, min_ip_value, max_ip_value, min_op_value, max_op_value):
return (x - min_ip_value) * (max_op_value - min_op_value) / (
max_ip_value - min_ip_value) + min_op_value


# Map Current to Voltage
temp_volts = np.array([])
min_ip_value = drive_cycle_current[:, 1].min()
max_ip_value = drive_cycle_current[:, 1].max()
min_Voltage = 3.5
max_Voltage = 4.1
for I in drive_cycle_current[:, 1]:
temp_volts = np.append(
temp_volts,
Map_Drive_Cycle(I, min_ip_value, max_ip_value, min_Voltage,
max_Voltage))

drive_cycle_voltage = drive_cycle_current
drive_cycle_voltage = np.column_stack((np.delete(drive_cycle_voltage, 1,
1), np.array(temp_volts)))

# Map Current to Power
temp_volts = np.array([])
min_ip_value = drive_cycle_current[:, 1].min()
max_ip_value = drive_cycle_current[:, 1].max()
min_Power = 2.5
max_Power = 5.5
for I in drive_cycle_current[:, 1]:
temp_volts = np.append(
temp_volts,
Map_Drive_Cycle(I, min_ip_value, max_ip_value, min_Power, max_Power))

drive_cycle_power = drive_cycle_current
drive_cycle_power = np.column_stack((np.delete(drive_cycle_power, 1,
1), np.array(temp_volts)))
experiment = pybamm.Experiment([
# "Charge at 1 A until 4.1 V",
# "Hold at 4.1 V until 50 mA",
# "Rest for 1 hour",
"Run US06_A (A),
# "Rest for 1 hour",
]
# + [
# "Charge at 1 A until 4.1 V",
# "Hold at 4.1 V until 50 mA",
# "Rest for 1 hour",
# "Run US06_V (V)",
# "Rest for 1 hour",
# ] + [
# "Charge at 1 A until 4.1 V",
# "Hold at 4.1 V until 50 mA",
# "Rest for 1 hour",
# "Run US06_W (W)",
# "Rest for 1 hour",
# ]
,drive_cycles={
"US06_A": drive_cycle_current,
"US06_V": drive_cycle_voltage,
"US06_W": drive_cycle_power,
})

model = pybamm.lithium_ion.DFN()
sim = pybamm.Simulation(model,
experiment=experiment,
solver=pybamm.CasadiSolver())
sim.solve()

# Show all plots
sim.plot()
2 changes: 1 addition & 1 deletion pybamm/experiments/experiment.py
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Original file line number Diff line number Diff line change
Expand Up @@ -233,7 +233,7 @@ def read_string(self, cond, drive_cycles):
examples
)
)
return electric + (time,) + (period,), events
return electric + (time,) + (period,) + (cond,), events

def extend_drive_cycle(self, drive_cycle, end_time):
"Extends the drive cycle to enable for event"
Expand Down
124 changes: 80 additions & 44 deletions pybamm/simulation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -170,44 +170,79 @@ def set_up_experiment(self, model, experiment):
self._experiment_inputs = []
self._experiment_times = []
for op, events in zip(experiment.operating_conditions, experiment.events):
if op[1] in ["A", "C"]:
# Update inputs for constant current
if isinstance(op[0], np.ndarray):
# If ndarray is recived from, create interpolant
# create interpolant
timescale = self._parameter_values.evaluate(model.timescale)
drive_cycle_interpolant = pybamm.Interpolant(
op[0][:, 0], op[0][:, 1], timescale * pybamm.t
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The last input here is the time that is evaluated by the interpolant. You could do the following:

drive_cycle_interpolant = pybamm.Interpolant(
                    op[0][:, 0], op[0][:, 1], timescale * pybamm.t - pybamm.InputParameter("start time")
)

and pass the appropriate "start time" to the model inputs when solving the model at each step

)
if op[1] == "A":
I = op[0]
else:
# Scale C-rate with capacity to obtain current
capacity = self._parameter_values["Nominal cell capacity [A.h]"]
I = op[0] * capacity
operating_inputs = {
"Current switch": 1,
"Voltage switch": 0,
"Power switch": 0,
"Current input [A]": I,
"Voltage input [V]": 0, # doesn't matter
"Power input [W]": 0, # doesn't matter
}
elif op[1] == "V":
# Update inputs for constant voltage
V = op[0]
operating_inputs = {
"Current switch": 0,
"Voltage switch": 1,
"Power switch": 0,
"Current input [A]": 0, # doesn't matter
"Voltage input [V]": V,
"Power input [W]": 0, # doesn't matter
}
elif op[1] == "W":
# Update inputs for constant power
P = op[0]
operating_inputs = {
"Current switch": 0,
"Voltage switch": 0,
"Power switch": 1,
"Current input [A]": 0, # doesn't matter
"Voltage input [V]": 0, # doesn't matter
"Power input [W]": P,
}
operating_inputs = {
"Current switch": 1,
"Voltage switch": 0,
"Power switch": 0,
"Current input [A]": drive_cycle_interpolant,
"Voltage input [V]": 0, # doesn't matter
"Power input [W]": 0, # doesn't matter
}
if op[1] == "V":
operating_inputs = {
"Current switch": 0,
"Voltage switch": 1,
"Power switch": 0,
"Current input [A]": 0, # doesn't matter
"Voltage input [V]": drive_cycle_interpolant,
"Power input [W]": 0, # doesn't matter
}
if op[1] == "W":
operating_inputs = {
"Current switch": 0,
"Voltage switch": 0,
"Power switch": 1,
"Current input [A]": 0, # doesn't matter
"Voltage input [V]": 0, # doesn't matter
"Power input [W]": drive_cycle_interpolant,
}
else:
if op[1] in ["A", "C"]:
# Update inputs for constant current
if op[1] == "A":
I = op[0]
else:
# Scale C-rate with capacity to obtain current
capacity = self._parameter_values["Nominal cell capacity [A.h]"]
I = op[0] * capacity
operating_inputs = {
"Current switch": 1,
"Voltage switch": 0,
"Power switch": 0,
"Current input [A]": I,
"Voltage input [V]": 0, # doesn't matter
"Power input [W]": 0, # doesn't matter
}
elif op[1] == "V":
# Update inputs for constant voltage
V = op[0]
operating_inputs = {
"Current switch": 0,
"Voltage switch": 1,
"Power switch": 0,
"Current input [A]": 0, # doesn't matter
"Voltage input [V]": V,
"Power input [W]": 0, # doesn't matter
}
elif op[1] == "W":
# Update inputs for constant power
P = op[0]
operating_inputs = {
"Current switch": 0,
"Voltage switch": 0,
"Power switch": 1,
"Current input [A]": 0, # doesn't matter
"Voltage input [V]": 0, # doesn't matter
"Power input [W]": P,
}
# Update period
operating_inputs["period"] = op[3]
# Update events
Expand Down Expand Up @@ -319,7 +354,7 @@ def set_up_model_for_experiment_old(self, model):
self.model = new_model

self.op_conds_to_model_and_param = {
op_cond[:2]: (new_model, self.parameter_values)
op_cond[-1]: (new_model, self.parameter_values)
for op_cond in set(self.experiment.operating_conditions)
}
self.op_conds_to_built_models = None
Expand All @@ -339,7 +374,7 @@ def set_up_model_for_experiment_new(self, model):
):
# Create model for this operating condition if it has not already been seen
# before
if op_cond[:2] not in self.op_conds_to_model_and_param:
if op_cond[-1] not in self.op_conds_to_model_and_param:
if op_inputs["Current switch"] == 1:
# Current control
# Make a new copy of the model (we will update events later))
Expand Down Expand Up @@ -422,7 +457,8 @@ def set_up_model_for_experiment_new(self, model):
for event in new_model.events
if event.name not in ["Minimum voltage", "Maximum voltage"]
]

# Make Interpolant Here
print("OK GEE")
# Update parameter values
new_parameter_values = self.parameter_values.copy()
if op_inputs["Current switch"] == 1:
Expand All @@ -439,8 +475,10 @@ def set_up_model_for_experiment_new(self, model):
{"Power function [W]": op_inputs["Power input [W]"]},
check_already_exists=False,
)

# print(new_parameter_values) #!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!)

self.op_conds_to_model_and_param[op_cond[:2]] = (
self.op_conds_to_model_and_param[op_cond[-1]] = (
new_model,
new_parameter_values,
)
Expand Down Expand Up @@ -691,7 +729,7 @@ def solve(
dt = self._experiment_times[idx]
op_conds_str = self.experiment.operating_conditions_strings[idx]
op_conds_elec = self.experiment.operating_conditions[idx][:2]
model = self.op_conds_to_built_models[op_conds_elec]
model = self.op_conds_to_built_models[op_conds_str]
# Use 1-indexing for printing cycle number as it is more
# human-intuitive
pybamm.logger.notice(
Expand All @@ -712,9 +750,7 @@ def solve(
)
steps.append(step_solution)
current_solution = step_solution

cycle_solution = cycle_solution + step_solution

# Only allow events specified by experiment
if not (
cycle_solution is None
Expand Down
6 changes: 6 additions & 0 deletions pybamm/solvers/base_solver.py
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Original file line number Diff line number Diff line change
Expand Up @@ -907,6 +907,12 @@ def step(
# Set up external variables and inputs
external_variables = external_variables or {}
inputs = inputs or {}
if isinstance(inputs['Current input [A]'], pybamm.Interpolant):
del inputs['Current input [A]']
elif isinstance(inputs['Voltage input [V]'], pybamm.Interpolant):
del inputs['Voltage input [V]']
elif isinstance(inputs['Power input [W]'], pybamm.Interpolant):
del inputs['Power input [W]']
ext_and_inputs = {**external_variables, **inputs}

# Check that any inputs that may affect the scaling have not changed
Expand Down