def test_no_name(self):
ptree = PropertyTree()
ptree.put_double('initial_voltage', 0)
ptree.put_double('final_voltage', 0)
ptree.put_double('scan_limit_1', 1)
ptree.put_double('scan_limit_2', 0)
ptree.put_double('step_size', 0.1)
ptree.put_double('scan_rate', 1)
ptree.put_int('cycles', 1)
cv = CyclicVoltammetry(ptree)
try:
cv.run(device)
except:
self.fail('calling run without data should not raise')
data = initialize_data()
cv.run(device, data)
voltage = array([0., 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.,
0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.],
dtype=float)
time = linspace(0, 2, 21)
try:
testing.assert_array_almost_equal(data['voltage'], voltage)
testing.assert_array_almost_equal(data['time'], time)
except AssertionError as e:
print(e)
self.fail()
def testSeriesRC(self):
# make series RC equivalent circuit
device_database = PropertyTree()
device_database.put_string('type', 'SeriesRC')
device_database.put_double('series_resistance', R)
device_database.put_double('capacitance', C)
device = EnergyStorageDevice(device_database, MPI.COMM_WORLD)
# setup experiment and measure
eis_database = setup_expertiment()
spectrum_data = measure_impedance_spectrum(device, eis_database)
# extract data
f = spectrum_data['frequency']
Z_computed = spectrum_data['impedance']
R_computed = real(Z_computed)
X_computed = imag(Z_computed)
M_computed = 20*log10(absolute(Z_computed))
P_computed = angle(Z_computed)*180/pi
# compute the exact solution
Z_exact = R+1/(1j*C*2*pi*f)
R_exact = real(Z_exact)
X_exact = imag(Z_exact)
M_exact = 20*log10(absolute(Z_exact))
P_exact = angle(Z_exact)*180/pi
# ensure the error is small
max_phase_error_in_degree = linalg.norm(P_computed-P_exact, inf)
max_magniture_error_in_decibel = linalg.norm(M_computed-M_exact, inf)
print('max_phase_error_in_degree = {0}'.format(max_phase_error_in_degree))
print('max_magniture_error_in_decibel = {0}'.format(max_magniture_error_in_decibel))
self.assertLessEqual(max_phase_error_in_degree, 1)
self.assertLessEqual(max_magniture_error_in_decibel, 0.2)
def test_evolve_constant_voltage(self):
ptree = PropertyTree()
ptree.put_string('mode', 'constant_voltage')
ptree.put_double('voltage', 2.1)
evolve_one_time_step = TimeEvolution.factory(ptree)
evolve_one_time_step(device, 0.1)
self.assertEqual(device.get_voltage(), 2.1)
def test_evolve_constant_current(self):
ptree = PropertyTree()
ptree.put_string('mode', 'constant_current')
ptree.put_double('current', 100e-3)
evolve_one_time_step = TimeEvolution.factory(ptree)
evolve_one_time_step(device, 0.1)
self.assertEqual(device.get_current(), 100e-3)
def test_evolve_constant_load(self):
ptree = PropertyTree()
ptree.put_string('mode', 'constant_load')
ptree.put_double('load', 120)
evolve_one_time_step = TimeEvolution.factory(ptree)
evolve_one_time_step(device, 0.1)
self.assertAlmostEqual(device.get_voltage()/device.get_current(), -120)
def testRetrieveData(self):
try:
from h5py import File
except ImportError:
print('module h5py not found')
return
device_database = PropertyTree()
device_database.put_string('type', 'SeriesRC')
device_database.put_double('series_resistance', R)
device_database.put_double('capacitance', C)
device = EnergyStorageDevice(device_database, MPI.COMM_WORLD)
eis_database = setup_expertiment()
eis_database.put_int('steps_per_decade', 1)
eis_database.put_int('steps_per_cycle', 64)
eis_database.put_int('cycles', 2)
eis_database.put_int('ignore_cycles', 1)
fout = File('trash.hdf5', 'w')
spectrum_data = measure_impedance_spectrum(device, eis_database, fout)
fout.close()
fin = File('trash.hdf5', 'r')
retrieved_data = retrieve_impedance_spectrum(fin)
fin.close()
print(spectrum_data['impedance']-retrieved_data['impedance'])
print(retrieved_data)
self.assertEqual(linalg.norm(spectrum_data['frequency'] -
retrieved_data['frequency'], inf), 0.0)
# not sure why we don't get equality for the impedance
self.assertLess(linalg.norm(spectrum_data['impedance'] -
retrieved_data['impedance'], inf), 1e-10)
def test_time_limit(self):
ptree = PropertyTree()
ptree.put_string('end_criterion', 'time')
ptree.put_double('duration', 15)
time_limit = EndCriterion.factory(ptree)
time_limit.reset(0.0, device)
self.assertFalse(time_limit.check(2.0, device))
self.assertTrue(time_limit.check(15.0, device))
self.assertTrue(time_limit.check(60.0, device))
def test_verification_with_equivalent_circuit(self):
R = 50e-3 # ohm
R_L = 500 # ohm
C = 3 # farad
# setup EIS experiment
ptree = PropertyTree()
ptree.put_string('type', 'ElectrochemicalImpedanceSpectroscopy')
ptree.put_double('frequency_upper_limit', 1e+4)
ptree.put_double('frequency_lower_limit', 1e-6)
ptree.put_int('steps_per_decade', 3)
ptree.put_int('steps_per_cycle', 1024)
ptree.put_int('cycles', 2)
ptree.put_int('ignore_cycles', 1)
ptree.put_double('dc_voltage', 0)
ptree.put_string('harmonics', '3')
ptree.put_string('amplitudes', '5e-3')
ptree.put_string('phases', '0')
eis = Experiment(ptree)
# setup equivalent circuit database
device_database = PropertyTree()
device_database.put_double('series_resistance', R)
device_database.put_double('parallel_resistance', R_L)
device_database.put_double('capacitance', C)
# analytical solutions
Z = {}
Z['SeriesRC'] = lambda f: R + 1 / (1j * C * 2 * pi * f)
Z['ParallelRC'] = lambda f: R + R_L / (1 + 1j * R_L * C * 2 * pi * f)
for device_type in ['SeriesRC', 'ParallelRC']:
# create a device
device_database.put_string('type', device_type)
device = EnergyStorageDevice(device_database)
# setup experiment and measure
eis.reset()
eis.run(device)
f = eis._data['frequency']
Z_computed = eis._data['impedance']
# compute the exact solution
Z_exact = Z[device_type](f)
# ensure the error is small
max_phase_error_in_degree = linalg.norm(
angle(Z_computed) * 180 / pi - angle(Z_exact) * 180 / pi,
inf)
max_magniture_error_in_decibel = linalg.norm(
20 * log10(absolute(Z_exact)) - 20 *
log10(absolute(Z_computed)),
inf)
print(device_type)
print(
'-- max_phase_error_in_degree = {0}'.format(max_phase_error_in_degree))
print(
'-- max_magniture_error_in_decibel = {0}'.format(max_magniture_error_in_decibel))
self.assertLessEqual(max_phase_error_in_degree, 1)
self.assertLessEqual(max_magniture_error_in_decibel, 0.2)
def test_consistency_pycap_simulation(self):
#
# weak run test; simply ensures that Dualfoil object
# can be run with pycap.Charge
#
df1 = Dualfoil(path=path) # will use pycap
df2 = Dualfoil(path=path) # manual runs
im = df_manip.InputManager(path=path)
# testing a charge-to-hold-const-voltage
# manual
# use InputManager to set the input file
c = -12.0 # constant current
im.add_new_leg(c, 5.0, 1)
df1.run()
df1.outbot.update_output()
v = 4.54 # constant voltage
im.add_new_leg(v, 5.0, 0)
df1.run()
df1.outbot.update_output()
# pycap simulation
# build a ptree input
ptree = PropertyTree()
ptree.put_double('time_step', 300.0) # 5 minutes
ptree.put_string('charge_mode', 'constant_current')
ptree.put_double('charge_current', 12.0)
ptree.put_string('charge_stop_at_1', 'voltage_greater_than')
ptree.put_double('charge_voltage_limit', 4.54)
ptree.put_bool('charge_voltage_finish', True)
# hold end voltage after either 5 minutes have passed
# OR current falls under 1 ampere
ptree.put_double('charge_voltage_finish_max_time', 300.0)
ptree.put_double('charge_voltage_finish_current_limit', 1.0)
const_current_const_voltage = Charge(ptree)
const_current_const_voltage.run(df2)
# check the output lists of both devices
o1 = df1.outbot.output
o2 = df2.outbot.output
self.assertEqual(len(o1['time']), len(o2['time']))
for i in range(len(o1['time'])):
self.assertAlmostEqual(o1['time'][i], o2['time'][i])
# BELOW: relaxed delta for voltage
# REASON: dualfoil cuts off its voltages at 5
# decimal places, meaning that this end-digit
# is subject to roundoff errors
error = 1e-5
self.assertAlmostEqual(o1['voltage'][i], o2['voltage'][i],
delta=error)
self.assertAlmostEqual(o1['current'][i], o2['current'][i])
def setup_expertiment():
eis_database = PropertyTree()
eis_database.put_double('frequency_upper_limit', 1e+4)
eis_database.put_double('frequency_lower_limit', 1e-6)
eis_database.put_int('steps_per_decade', 3)
eis_database.put_int('steps_per_cycle', 1024)
eis_database.put_int('cycles', 2)
eis_database.put_int('ignore_cycles', 1)
eis_database.put_double('dc_voltage', 0)
eis_database.put_string('harmonics', ' 3')
eis_database.put_string('amplitudes', ' 5e-3')
eis_database.put_string('phases', '0')
return eis_database
def test_retrieve_data(self):
ptree = PropertyTree()
ptree.put_string('type', 'SeriesRC')
ptree.put_double('series_resistance', 100e-3)
ptree.put_double('capacitance', 2.5)
device = EnergyStorageDevice(ptree)
ptree = PropertyTree()
ptree.put_string('type', 'ElectrochemicalImpedanceSpectroscopy')
ptree.put_double('frequency_upper_limit', 1e+2)
ptree.put_double('frequency_lower_limit', 1e-1)
ptree.put_int('steps_per_decade', 1)
ptree.put_int('steps_per_cycle', 64)
ptree.put_int('cycles', 2)
ptree.put_int('ignore_cycles', 1)
ptree.put_double('dc_voltage', 0)
ptree.put_string('harmonics', '3')
ptree.put_string('amplitudes', '5e-3')
ptree.put_string('phases', '0')
eis = Experiment(ptree)
with File('trash.hdf5', 'w') as fout:
eis.run(device, fout)
spectrum_data = eis._data
with File('trash.hdf5', 'r') as fin:
retrieved_data = retrieve_impedance_spectrum(fin)
print(spectrum_data['impedance'] - retrieved_data['impedance'])
print(retrieved_data)
self.assertEqual(linalg.norm(spectrum_data['frequency'] -
retrieved_data['frequency'], inf), 0.0)
# not sure why we don't get equality for the impedance
self.assertLess(linalg.norm(spectrum_data['impedance'] -
retrieved_data['impedance'], inf), 1e-10)
def test_constant_current_charge_for_given_time(self):
ptree = PropertyTree()
ptree.put_string('mode', 'constant_current')
ptree.put_double('current', 5e-3)
ptree.put_string('end_criterion', 'time')
ptree.put_double('duration', 15.0)
ptree.put_double('time_step', 0.1)
stage = Stage(ptree)
data = initialize_data()
steps = stage.run(device, data)
self.assertEqual(steps, 150)
self.assertEqual(steps, len(data['time']))
self.assertAlmostEqual(data['time'][-1], 15.0)
self.assertAlmostEqual(data['current'][-1], 5e-3)
def test_setup_frequency_range(self):
ptree = PropertyTree()
ptree.put_string('type', 'ElectrochemicalImpedanceSpectroscopy')
# specify the upper and lower bounds of the range
# the number of points per decades controls the spacing on the log
# scale
ptree.put_double('frequency_upper_limit', 1e+2)
ptree.put_double('frequency_lower_limit', 1e-1)
ptree.put_int('steps_per_decade', 3)
eis = Experiment(ptree)
print(eis._frequencies)
f = eis._frequencies
self.assertEqual(len(f), 10)
self.assertAlmostEqual(f[0], 1e+2)
self.assertAlmostEqual(f[3], 1e+1)
self.assertAlmostEqual(f[9], 1e-1)
# or directly specify the frequencies
frequencies = [3, 2e3, 0.1]
eis = Experiment(ptree, frequencies)
self.assertTrue(all(equal(frequencies, eis._frequencies)))
def test_charge_constant_voltage(self):
ptree = PropertyTree()
ptree.put_string('charge_mode', 'constant_voltage')
ptree.put_double('charge_voltage', 1.4)
ptree.put_string('charge_stop_at_1', 'current_less_than')
ptree.put_double('charge_current_limit', 1e-6)
ptree.put_string('charge_stop_at_2', 'time')
ptree.put_double('charge_max_duration', 60)
ptree.put_double('time_step', 0.2)
charge = Charge(ptree)
data = initialize_data()
charge.run(device, data)
self.assertTrue(data['time'][-1] >= 60 or
abs(data['current'][-1]) <= 1e-6)
self.assertAlmostEqual(data['voltage'][-1], 1.4)
def test_compound_criterion(self):
ptree = PropertyTree()
ptree.put_string('end_criterion', 'compound')
ptree.put_string('criterion_0.end_criterion', 'time')
ptree.put_double('criterion_0.duration', 5.0)
ptree.put_string('criterion_1.end_criterion', 'voltage_greater_than')
ptree.put_double('criterion_1.voltage_limit', 2.0)
# no default value for now
self.assertRaises(KeyError, EndCriterion.factory, ptree)
ptree.put_string('logical_operator', 'bad_operator')
self.assertRaises(RuntimeError, EndCriterion.factory, ptree)
ptree.put_string('logical_operator', 'or')
compound_criterion = EndCriterion.factory(ptree)
compound_criterion.reset(0.0, device)
device.evolve_one_time_step_constant_voltage(0.1, 1.0)
self.assertFalse(compound_criterion.check(3.0, device))
self.assertTrue(compound_criterion.check(5.0, device))
device.evolve_one_time_step_constant_voltage(0.1, 2.0)
self.assertTrue(compound_criterion.check(3.0, device))
self.assertTrue(compound_criterion.check(5.0, device))
ptree.put_string('logical_operator', 'and')
compound_criterion = EndCriterion.factory(ptree)
compound_criterion.reset(0.0, device)
device.evolve_one_time_step_constant_voltage(0.1, 1.0)
self.assertFalse(compound_criterion.check(3.0, device))
self.assertFalse(compound_criterion.check(5.0, device))
device.evolve_one_time_step_constant_voltage(0.1, 2.0)
self.assertFalse(compound_criterion.check(3.0, device))
self.assertTrue(compound_criterion.check(5.0, device))
ptree.put_string('logical_operator', 'xor')
compound_criterion = EndCriterion.factory(ptree)
compound_criterion.reset(0.0, device)
device.evolve_one_time_step_constant_voltage(0.1, 1.0)
self.assertFalse(compound_criterion.check(3.0, device))
self.assertTrue(compound_criterion.check(5.0, device))
device.evolve_one_time_step_constant_voltage(0.1, 2.0)
self.assertTrue(compound_criterion.check(3.0, device))
self.assertFalse(compound_criterion.check(5.0, device))
def test_voltage_limit(self):
ptree = PropertyTree()
ptree.put_double('voltage_limit', 1.7)
# upper limit
ptree.put_string('end_criterion', 'voltage_greater_than')
voltage_limit = EndCriterion.factory(ptree)
voltage_limit.reset(5.0, device)
device.evolve_one_time_step_constant_voltage(0.2, 1.3)
self.assertFalse(voltage_limit.check(0.0, device))
self.assertFalse(voltage_limit.check(60.0, device))
device.evolve_one_time_step_constant_voltage(0.2, 1.7)
self.assertTrue(voltage_limit.check(45.0, device))
device.evolve_one_time_step_constant_voltage(0.2, 2.1)
self.assertTrue(voltage_limit.check(45.0, device))
# lower limit
ptree.put_string('end_criterion', 'voltage_less_than')
voltage_limit = EndCriterion.factory(ptree)
voltage_limit.reset(0.0, device)
device.evolve_one_time_step_constant_voltage(0.2, 1.3)
self.assertTrue(voltage_limit.check(0.0, device))
device.evolve_one_time_step_constant_voltage(0.2, 1.7)
self.assertTrue(voltage_limit.check(45.0, device))
device.evolve_one_time_step_constant_voltage(0.2, 2.1)
self.assertFalse(voltage_limit.check(45.0, device))
def test_time_steps(self):
ptree = PropertyTree()
ptree.put_int('stages', 2)
ptree.put_int('cycles', 1)
ptree.put_double('time_step', 1.0)
ptree.put_string('stage_0.mode', 'hold')
ptree.put_string('stage_0.end_criterion', 'time')
ptree.put_double('stage_0.duration', 2.0)
ptree.put_string('stage_1.mode', 'rest')
ptree.put_string('stage_1.end_criterion', 'time')
ptree.put_double('stage_1.duration', 1.0)
ptree.put_double('stage_1.time_step', 0.1)
multi = MultiStage(ptree)
data = initialize_data()
steps = multi.run(device, data)
self.assertEqual(steps, 12)
self.assertEqual(steps, len(data['time']))
self.assertAlmostEqual(data['time'][5], 2.4)
self.assertAlmostEqual(data['voltage'][0], data['voltage'][1])
self.assertAlmostEqual(data['current'][3], 0.0)
def test_charge_constant_current(self):
ptree = PropertyTree()
ptree.put_string('charge_mode', 'constant_current')
ptree.put_double('charge_current', 10e-3)
ptree.put_string('charge_stop_at_1', 'voltage_greater_than')
ptree.put_double('charge_voltage_limit', 1.4)
ptree.put_double('time_step', 0.2)
charge = Charge(ptree)
data = initialize_data()
charge.run(device, data)
self.assertAlmostEqual(data['current'][0], 10e-3)
self.assertAlmostEqual(data['current'][-1], 10e-3)
self.assertGreaterEqual(data['voltage'][-1], 1.4)
self.assertAlmostEqual(data['time'][1] - data['time'][0], 0.2)
def test_force_discharge(self):
ptree = PropertyTree()
ptree.put_string('mode', 'constant_voltage')
ptree.put_double('voltage', 0.0)
ptree.put_string('end_criterion', 'current_less_than')
ptree.put_double('current_limit', 1e-5)
ptree.put_double('time_step', 1.0)
stage = Stage(ptree)
data = initialize_data()
steps = stage.run(device, data)
self.assertGreaterEqual(steps, 1)
self.assertEqual(steps, len(data['time']))
self.assertAlmostEqual(data['voltage'][-1], 0.0)
self.assertLessEqual(data['current'][-1], 1e-5)
def test_retrieve_data(self):
ptree = PropertyTree()
ptree.put_string('type', 'SeriesRC')
ptree.put_double('series_resistance', 100e-3)
ptree.put_double('capacitance', 2.5)
device = EnergyStorageDevice(ptree)
ptree = PropertyTree()
ptree.put_string('type', 'ElectrochemicalImpedanceSpectroscopy')
ptree.put_double('frequency_upper_limit', 1e+2)
ptree.put_double('frequency_lower_limit', 1e-1)
ptree.put_int('steps_per_decade', 1)
ptree.put_int('steps_per_cycle', 64)
ptree.put_int('cycles', 2)
ptree.put_int('ignore_cycles', 1)
ptree.put_double('dc_voltage', 0)
ptree.put_string('harmonics', '3')
ptree.put_string('amplitudes', '5e-3')
ptree.put_string('phases', '0')
eis = Experiment(ptree)
with File('trash.hdf5', 'w') as fout:
eis.run(device, fout)
spectrum_data = eis._data
with File('trash.hdf5', 'r') as fin:
retrieved_data = retrieve_impedance_spectrum(fin)
print(spectrum_data['impedance'] - retrieved_data['impedance'])
print(retrieved_data)
self.assertEqual(
linalg.norm(
spectrum_data['frequency'] - retrieved_data['frequency'], inf),
0.0)
# not sure why we don't get equality for the impedance
self.assertLess(
linalg.norm(
spectrum_data['impedance'] - retrieved_data['impedance'], inf),
1e-10)
def test_retrieve_data(self):
ptree = PropertyTree()
ptree.put_string('type', 'SeriesRC')
ptree.put_double('series_resistance', 50e-3)
ptree.put_double('capacitance', 3)
device = EnergyStorageDevice(ptree)
ptree = PropertyTree()
ptree.put_string('type', 'RagoneAnalysis')
ptree.put_double('discharge_power_lower_limit', 1e-1)
ptree.put_double('discharge_power_upper_limit', 1e+1)
ptree.put_int('steps_per_decade', 1)
ptree.put_double('initial_voltage', 2.1)
ptree.put_double('final_voltage', 0.7)
ptree.put_double('time_step', 1.5)
ptree.put_int('min_steps_per_discharge', 20)
ptree.put_int('max_steps_per_discharge', 30)
ragone = Experiment(ptree)
with File('trash.hdf5', 'w') as fout:
ragone.run(device, fout)
performance_data = ragone._data
fin = File('trash.hdf5', 'r')
retrieved_data = retrieve_performance_data(fin)
fin.close()
# a few digits are lost when power is converted to string
self.assertLess(
linalg.norm(performance_data['power'] - retrieved_data['power'],
inf), 1e-12)
self.assertEqual(
linalg.norm(performance_data['energy'] - retrieved_data['energy'],
inf), 0.0)
# TODO: probably want to move this into its own test
ragoneplot = RagonePlot("ragone.png")
ragoneplot.update(ragone)
# check reset reinitialize the time step and empty the data
ragone.reset()
self.assertEqual(ragone._ptree.get_double('time_step'), 1.5)
self.assertFalse(ragone._data['power'])
self.assertFalse(ragone._data['energy'])
def test_accuracy_pycap_simulation(self):
#
# tests the accuracy of a pycap simulation against a
# straight run dualfoil sim with different timesteps
#
df1 = Dualfoil(path=path) # manual runs
df2 = Dualfoil(path=path) # pycap simulation
im = df_manip.InputManager(path=path)
# testing a charge-to-hold-const-voltage
# manual
# use InputManager to set the input file
c = -10.0 # constant charge current
# charge for 5 minutes straight
im.add_new_leg(c, 5, 1)
df1.run()
df1.outbot.update_output()
v = 4.539 # expected voltage after 5 minutes
# hold constant voltage for 3 minutes straight
im.add_new_leg(v, 3.0, 0)
df1.run()
df1.outbot.update_output()
# pycap simulation
# build a ptree input
ptree = PropertyTree()
ptree.put_double('time_step', 30.0) # 30 second time step
ptree.put_string('charge_mode', 'constant_current')
ptree.put_double('charge_current', 10.0)
ptree.put_string('charge_stop_at_1', 'voltage_greater_than')
ptree.put_double('charge_voltage_limit', v)
ptree.put_bool('charge_voltage_finish', True)
# hold end voltage after either 3 minutes have passed
# OR current falls under 1 ampere
ptree.put_double('charge_voltage_finish_max_time', 180.0)
ptree.put_double('charge_voltage_finish_current_limit', 1.0)
const_current_const_voltage = Charge(ptree)
const_current_const_voltage.run(df2)
o1 = df1.outbot.output # contains sim1 output
o2 = df2.outbot.output # contains sim2 output
# affirm we make it this far and have usable data
self.assertTrue(len(o1['time']) > 0)
self.assertTrue(len(o2['time']) > 0)
# lengths of data should be different
self.assertFalse(len(o1['time']) == len(o2['time']))
# TEST LOGIC:
# -Merge the two outputs into one, sorted by
# increasing time stamps.
# -Compare the consistency of the two simulations
# by checking for smooth changes within the curves
# of the combined output lists
o1['time'].extend(o2['time'])
time = ar(o1['time']) # nparray
o1['voltage'].extend(o2['voltage'])
voltage = ar(o1['voltage']) # nparray
o1['current'].extend(o2['current'])
current = ar(o1['current']) # np array
# create a dictionary with the combined output lists
output = {'time': time,
'voltage': voltage,
'current': current
}
# sort based on time, keeping the three types aligned
key = argsort(output['time'])
# for using the key to sort the list
tmp = {'time': [], 'voltage': [], 'current': []}
for i in key:
tmp['time'].append(output['time'][i])
tmp['voltage'].append(output['voltage'][i])
tmp['current'].append(output['current'][i])
# reassign ordered set to `output` as nparrays
output['time'] = ar(tmp['time'])
output['voltage'] = ar(tmp['voltage'])
output['current'] = ar(tmp['current'])
# BELOW: first 20 seconds are identical time stamps;
# skip these to avoid errors from incorrect sorting
# REASON FOR ERROR: Dualfoil only prints time data as
# precice as minutes to three decimal places. So when
# the following is generated....
# Manual Run | Pycap Simulation
# (min) (V) (amp) | (min) (V) (amp)
# .001 4.52345 10.0 | .001 4.52345 10.0
# .001 4.52349 10.0 | .001 4.52349 10.0
# ... ...
# ...python's `sorted()` function has no way of
# distinguishing entries; it instead returns this:
# [
# (.001, 4.52345, 10.0),
# (.001, 4.52349, 10.0), <- these two should
# (.001, 4.52345, 10.0), <- be switched
# (.001, 4.52349, 10.0)
# ]
# SOLUTION: consistency test affirms that the exact same
# time step will produce same current and voltage, so
# skip ahead to first instance where time stamps will
# be out of alignment
i = 0
while output['time'][i] <= 0.4: # 24 seconds
i = i + 1
index_limit = len(output['time'])-1
# go through and affirm smoothness of curve
while i < index_limit:
# Check if time values are the same to 3 decimal places.
# If so, current and voltage are not guarunteed
# to also be exactly the same, but should be close
if output['time'][i] == output['time'][i-1]:
# affirm that current is virtually the same
self.assertAlmostEqual(output['current'][i],
output['current'][i-1])
# BELOW: delta is eased slightly
# REASON: `sorted()` can't tell which entry came
# first from same time-stamp if from different
# simulations; allow for this with error
error = 3e-5
self.assertAlmostEqual(output['voltage'][i],
output['voltage'][i-1],
delta=error)
else:
# Time values are different
# Check to affirm that the variable NOT being held
# constant is steadily increasing / decreasing
# First part happens in first 4 minutes
if output['time'][i] <= 5.0: # part 1, const currrent
# current should be equal
self.assertEqual(output['current'][i],
output['current'][i-1])
# voltage should not have decreased
self.assertTrue(output['voltage'][i],
output['voltage'][i-1])
else: # part 2, const voltage
# current should be getting less positive
self.assertTrue(output['current'][i] <=
output['current'][i-1],
msg=(output['current'][i-2:i+10],
output['time'][i-2:i+10]))
# voltage should decrease, then stay at 4.54
if output['voltage'][i-1] == 4.54:
self.assertEqual(output['voltage'][i],
output['voltage'][i-1])
else:
self.assertTrue(output['voltage'][i] <=
output['voltage'][i-1])
# update index
i = i + 1
def run_discharge(device, ptree):
data = initialize_data()
# (re)charge the device
initial_voltage = ptree.get_double('initial_voltage')
charge_database = PropertyTree()
charge_database.put_string('charge_mode', 'constant_current')
charge_database.put_double('charge_current', 10.0)
charge_database.put_string('charge_stop_at_1', 'voltage_greater_than')
charge_database.put_double('charge_voltage_limit', initial_voltage)
charge_database.put_bool('charge_voltage_finish', True)
charge_database.put_double('charge_voltage_finish_current_limit', 1e-2)
charge_database.put_double('charge_voltage_finish_max_time', 600)
charge_database.put_double('charge_rest_time', 0)
charge_database.put_double('time_step', 10.0)
charge = Charge(charge_database)
start = time()
charge.run(device, data)
end = time()
# used for tracking time of this substep
print('Charge: %s min' % ((end - start) / 60))
data['time'] -= data['time'][-1]
# discharge at constant power
discharge_power = ptree.get_double('discharge_power')
final_voltage = ptree.get_double('final_voltage')
time_step = ptree.get_double('time_step')
discharge_database = PropertyTree()
discharge_database.put_string('discharge_mode', 'constant_power')
discharge_database.put_double('discharge_power', discharge_power)
discharge_database.put_string('discharge_stop_at_1', 'voltage_less_than')
discharge_database.put_double('discharge_voltage_limit', final_voltage)
discharge_database.put_double('discharge_rest_time', 10 * time_step)
discharge_database.put_double('time_step', time_step)
discharge = Discharge(discharge_database)
start = time()
discharge.run(device, data)
end = time()
# used for tracking time of this substep
print('Discharge: %s min' % ((end - start) / 60))
return data
def run_discharge(device, ptree):
data = initialize_data()
# (re)charge the device
initial_voltage = ptree.get_double('initial_voltage')
charge_database = PropertyTree()
charge_database.put_string('charge_mode', 'constant_current')
charge_database.put_double('charge_current', 10.0)
charge_database.put_string('charge_stop_at_1', 'voltage_greater_than')
charge_database.put_double('charge_voltage_limit', initial_voltage)
charge_database.put_bool('charge_voltage_finish', True)
charge_database.put_double('charge_voltage_finish_current_limit', 1e-2)
charge_database.put_double('charge_voltage_finish_max_time', 600)
charge_database.put_double('charge_rest_time', 0)
charge_database.put_double('time_step', 10.0)
charge = Charge(charge_database)
start = time()
charge.run(device, data)
end = time()
# used for tracking time of this substep
print('Charge: %s min' % ((end-start) / 60))
data['time'] -= data['time'][-1]
# discharge at constant power
discharge_power = ptree.get_double('discharge_power')
final_voltage = ptree.get_double('final_voltage')
time_step = ptree.get_double('time_step')
discharge_database = PropertyTree()
discharge_database.put_string('discharge_mode', 'constant_power')
discharge_database.put_double('discharge_power', discharge_power)
discharge_database.put_string('discharge_stop_at_1', 'voltage_less_than')
discharge_database.put_double('discharge_voltage_limit', final_voltage)
discharge_database.put_double('discharge_rest_time', 10 * time_step)
discharge_database.put_double('time_step', time_step)
discharge = Discharge(discharge_database)
start = time()
discharge.run(device, data)
end = time()
# used for tracking time of this substep
print('Discharge: %s min' % ((end-start) / 60))
return data
def test_current_limit(self):
# lower
ptree = PropertyTree()
ptree.put_string('end_criterion', 'current_less_than')
ptree.put_double('current_limit', -5e-3)
self.assertRaises(RuntimeError, EndCriterion.factory, ptree)
ptree.put_double('current_limit', 0.0)
self.assertRaises(RuntimeError, EndCriterion.factory, ptree)
ptree.put_double('current_limit', 5e-3)
current_limit = EndCriterion.factory(ptree)
device.evolve_one_time_step_constant_current(5.0, 0.0)
self.assertTrue(current_limit.check(NaN, device))
device.evolve_one_time_step_constant_current(5.0, 0.002)
self.assertTrue(current_limit.check(NaN, device))
device.evolve_one_time_step_constant_current(5.0, -0.001)
self.assertTrue(current_limit.check(180.0, device))
device.evolve_one_time_step_constant_current(5.0, 0.005)
self.assertTrue(current_limit.check(180.0, device))
device.evolve_one_time_step_constant_current(5.0, 0.007)
self.assertFalse(current_limit.check(180.0, device))
device.evolve_one_time_step_constant_current(5.0, -15e3)
self.assertFalse(current_limit.check(180.0, device))
# upper
ptree.put_string('end_criterion', 'current_greater_than')
ptree.put_double('current_limit', -5e-3)
self.assertRaises(RuntimeError, EndCriterion.factory, ptree)
ptree.put_double('current_limit', 0.0)
self.assertRaises(RuntimeError, EndCriterion.factory, ptree)
ptree.put_double('current_limit', 5e-3)
current_limit = EndCriterion.factory(ptree)
device.evolve_one_time_step_constant_current(5.0, -1e-3)
self.assertFalse(current_limit.check(NaN, device))
device.evolve_one_time_step_constant_current(5.0, 0.002)
self.assertFalse(current_limit.check(NaN, device))
device.evolve_one_time_step_constant_current(5.0, 0.005)
self.assertTrue(current_limit.check(NaN, device))
device.evolve_one_time_step_constant_current(5.0, -0.2)
self.assertTrue(current_limit.check(NaN, device))
device.evolve_one_time_step_constant_current(5.0, 3.0)
self.assertTrue(current_limit.check(NaN, device))
parser.add_option('--param_'+str(p),type=float)
# parse the command line arguments
(options,args)=parser.parse_args()
# make device database
device_database=PropertyTree()
device_database.parse_xml('super_capacitor.xml')
# adjust the parameters in the database
options_dict=vars(options)
for var in options_dict:
path=uq_database.get_string('uq.'+var+'.name')
# next line is there to ensure that path already exists
old_value=device_database.get_double(path)
new_value=options_dict[var]
print var,path,new_value
device_database.put_double(path,new_value)
# build the energy storage device
device=EnergyStorageDevice(device_database.get_child('device'))
# parse the electrochmical impedance spectroscopy database
eis_database=PropertyTree()
eis_database.parse_xml('eis.xml')
# measure the impedance
impedance_spectrum_data=measure_impedance_spectrum(device,eis_database.get_child('eis'))
# extract the results
frequency=impedance_spectrum_data['frequency']
complex_impedance=impedance_spectrum_data['impedance']
resistance=real(complex_impedance)
reactance=imag(complex_impedance)
modulus=absolute(complex_impedance)
argument=angle(complex_impedance,deg=True)
def test_verification_with_equivalent_circuit(self):
R = 50e-3 # ohm
R_L = 500 # ohm
C = 3 # farad
U_i = 2.7 # volt
U_f = 1.2 # volt
# setup experiment
ptree = PropertyTree()
ptree.put_double('discharge_power_lower_limit', 1e-2)
ptree.put_double('discharge_power_upper_limit', 1e+2)
ptree.put_int('steps_per_decade', 5)
ptree.put_double('initial_voltage', U_i)
ptree.put_double('final_voltage', U_f)
ptree.put_double('time_step', 15)
ptree.put_int('min_steps_per_discharge', 2000)
ptree.put_int('max_steps_per_discharge', 3000)
ragone = RagoneAnalysis(ptree)
# setup equivalent circuit database
device_database = PropertyTree()
device_database.put_double('series_resistance', R)
device_database.put_double('parallel_resistance', R_L)
device_database.put_double('capacitance', C)
# analytical solutions
E = {}
def E_SeriesRC(P):
U_0 = U_i / 2 + sqrt(U_i**2 / 4 - R * P)
return C / 2 * (-R * P * log(U_0**2 / U_f**2) + U_0**2 - U_f**2)
E['SeriesRC'] = E_SeriesRC
def E_ParallelRC(P):
U_0 = U_i / 2 + sqrt(U_i**2 / 4 - R * P)
tmp = (U_f**2 / R_L + P * (1 + R / R_L)) / \
(U_0**2 / R_L + P * (1 + R / R_L))
return C / 2 * (-R_L * P * log(tmp) - R * R_L /
(R + R_L) * P * log(tmp * U_0**2 / U_f**2))
E['ParallelRC'] = E_ParallelRC
for device_type in ['SeriesRC', 'ParallelRC']:
# create a device
device_database.put_string('type', device_type)
device = EnergyStorageDevice(device_database)
# setup experiment and measure
ragone.reset()
ragone.run(device)
P = ragone._data['power']
E_computed = ragone._data['energy']
# compute the exact solution
E_exact = E[device_type](P)
# ensure the error is small
max_percent_error = 100 * linalg.norm(
(E_computed - E_exact) / E_computed, inf)
self.assertLess(max_percent_error, 0.1)
def test_current_limit(self):
# lower
ptree = PropertyTree()
ptree.put_string('end_criterion', 'current_less_than')
ptree.put_double('current_limit', -5e-3)
self.assertRaises(RuntimeError, EndCriterion.factory, ptree)
ptree.put_double('current_limit', 0.0)
self.assertRaises(RuntimeError, EndCriterion.factory, ptree)
ptree.put_double('current_limit', 5e-3)
current_limit = EndCriterion.factory(ptree)
device.evolve_one_time_step_constant_current(5.0, 0.0)
self.assertTrue(current_limit.check(NaN, device))
device.evolve_one_time_step_constant_current(5.0, 0.002)
self.assertTrue(current_limit.check(NaN, device))
device.evolve_one_time_step_constant_current(5.0, -0.001)
self.assertTrue(current_limit.check(180.0, device))
device.evolve_one_time_step_constant_current(5.0, 0.005)
self.assertTrue(current_limit.check(180.0, device))
device.evolve_one_time_step_constant_current(5.0, 0.007)
self.assertFalse(current_limit.check(180.0, device))
device.evolve_one_time_step_constant_current(5.0, -15e3)
self.assertFalse(current_limit.check(180.0, device))
# upper
ptree.put_string('end_criterion', 'current_greater_than')
ptree.put_double('current_limit', -5e-3)
self.assertRaises(RuntimeError, EndCriterion.factory, ptree)
ptree.put_double('current_limit', 0.0)
self.assertRaises(RuntimeError, EndCriterion.factory, ptree)
ptree.put_double('current_limit', 5e-3)
current_limit = EndCriterion.factory(ptree)
device.evolve_one_time_step_constant_current(5.0, -1e-3)
self.assertFalse(current_limit.check(NaN, device))
device.evolve_one_time_step_constant_current(5.0, 0.002)
self.assertFalse(current_limit.check(NaN, device))
device.evolve_one_time_step_constant_current(5.0, 0.005)
self.assertTrue(current_limit.check(NaN, device))
device.evolve_one_time_step_constant_current(5.0, -0.2)
self.assertTrue(current_limit.check(NaN, device))
device.evolve_one_time_step_constant_current(5.0, 3.0)
self.assertTrue(current_limit.check(NaN, device))
def test_retrieve_data(self):
ptree = PropertyTree()
ptree.put_string('type', 'SeriesRC')
ptree.put_double('series_resistance', 50e-3)
ptree.put_double('capacitance', 3)
device = EnergyStorageDevice(ptree)
ptree = PropertyTree()
ptree.put_string('type', 'RagoneAnalysis')
ptree.put_double('discharge_power_lower_limit', 1e-1)
ptree.put_double('discharge_power_upper_limit', 1e+1)
ptree.put_int('steps_per_decade', 1)
ptree.put_double('initial_voltage', 2.1)
ptree.put_double('final_voltage', 0.7)
ptree.put_double('time_step', 1.5)
ptree.put_int('min_steps_per_discharge', 20)
ptree.put_int('max_steps_per_discharge', 30)
ragone = Experiment(ptree)
with File('trash.hdf5', 'w') as fout:
ragone.run(device, fout)
performance_data = ragone._data
fin = File('trash.hdf5', 'r')
retrieved_data = retrieve_performance_data(fin)
fin.close()
# a few digits are lost when power is converted to string
self.assertLess(linalg.norm(performance_data['power'] -
retrieved_data['power'], inf), 1e-12)
self.assertEqual(linalg.norm(performance_data['energy'] -
retrieved_data['energy'], inf), 0.0)
# TODO: probably want to move this into its own test
ragoneplot = RagonePlot("ragone.png")
ragoneplot.update(ragone)
# check reset reinitialize the time step and empty the data
ragone.reset()
self.assertEqual(ragone._ptree.get_double('time_step'), 1.5)
self.assertFalse(ragone._data['power'])
self.assertFalse(ragone._data['energy'])
def test_accuracy_pycap_simulation(self):
#
# tests the accuracy of a pycap simulation against a
# straight run dualfoil sim with different timesteps
#
df1 = Dualfoil(path=path) # manual runs
df2 = Dualfoil(path=path) # pycap simulation
im = df_manip.InputManager(path=path)
# testing a charge-to-hold-const-voltage
# manual
# use InputManager to set the input file
c = -10.0 # constant charge current
# charge for 5 minutes straight
im.add_new_leg(c, 5, 1)
df1.run()
df1.outbot.update_output()
v = 4.539 # expected voltage after 5 minutes
# hold constant voltage for 3 minutes straight
im.add_new_leg(v, 3.0, 0)
df1.run()
df1.outbot.update_output()
# pycap simulation
# build a ptree input
ptree = PropertyTree()
ptree.put_double('time_step', 30.0) # 30 second time step
ptree.put_string('charge_mode', 'constant_current')
ptree.put_double('charge_current', 10.0)
ptree.put_string('charge_stop_at_1', 'voltage_greater_than')
ptree.put_double('charge_voltage_limit', v)
ptree.put_bool('charge_voltage_finish', True)
# hold end voltage after either 3 minutes have passed
# OR current falls under 1 ampere
ptree.put_double('charge_voltage_finish_max_time', 180.0)
ptree.put_double('charge_voltage_finish_current_limit', 1.0)
const_current_const_voltage = Charge(ptree)
const_current_const_voltage.run(df2)
o1 = df1.outbot.output # contains sim1 output
o2 = df2.outbot.output # contains sim2 output
# affirm we make it this far and have usable data
self.assertTrue(len(o1['time']) > 0)
self.assertTrue(len(o2['time']) > 0)
# lengths of data should be different
self.assertFalse(len(o1['time']) == len(o2['time']))
# TEST LOGIC:
# -Merge the two outputs into one, sorted by
# increasing time stamps.
# -Compare the consistency of the two simulations
# by checking for smooth changes within the curves
# of the combined output lists
o1['time'].extend(o2['time'])
time = ar(o1['time']) # nparray
o1['voltage'].extend(o2['voltage'])
voltage = ar(o1['voltage']) # nparray
o1['current'].extend(o2['current'])
current = ar(o1['current']) # np array
# create a dictionary with the combined output lists
output = {'time': time, 'voltage': voltage, 'current': current}
# sort based on time, keeping the three types aligned
key = argsort(output['time'])
# for using the key to sort the list
tmp = {'time': [], 'voltage': [], 'current': []}
for i in key:
tmp['time'].append(output['time'][i])
tmp['voltage'].append(output['voltage'][i])
tmp['current'].append(output['current'][i])
# reassign ordered set to `output` as nparrays
output['time'] = ar(tmp['time'])
output['voltage'] = ar(tmp['voltage'])
output['current'] = ar(tmp['current'])
# BELOW: first 20 seconds are identical time stamps;
# skip these to avoid errors from incorrect sorting
# REASON FOR ERROR: Dualfoil only prints time data as
# precice as minutes to three decimal places. So when
# the following is generated....
# Manual Run | Pycap Simulation
# (min) (V) (amp) | (min) (V) (amp)
# .001 4.52345 10.0 | .001 4.52345 10.0
# .001 4.52349 10.0 | .001 4.52349 10.0
# ... ...
# ...python's `sorted()` function has no way of
# distinguishing entries; it instead returns this:
# [
# (.001, 4.52345, 10.0),
# (.001, 4.52349, 10.0), <- these two should
# (.001, 4.52345, 10.0), <- be switched
# (.001, 4.52349, 10.0)
# ]
# SOLUTION: consistency test affirms that the exact same
# time step will produce same current and voltage, so
# skip ahead to first instance where time stamps will
# be out of alignment
i = 0
while output['time'][i] <= 0.4: # 24 seconds
i = i + 1
index_limit = len(output['time']) - 1
# go through and affirm smoothness of curve
while i < index_limit:
# Check if time values are the same to 3 decimal places.
# If so, current and voltage are not guarunteed
# to also be exactly the same, but should be close
if output['time'][i] == output['time'][i - 1]:
# affirm that current is virtually the same
self.assertAlmostEqual(output['current'][i],
output['current'][i - 1])
# BELOW: delta is eased slightly
# REASON: `sorted()` can't tell which entry came
# first from same time-stamp if from different
# simulations; allow for this with error
error = 3e-5
self.assertAlmostEqual(output['voltage'][i],
output['voltage'][i - 1],
delta=error)
else:
# Time values are different
# Check to affirm that the variable NOT being held
# constant is steadily increasing / decreasing
# First part happens in first 4 minutes
if output['time'][i] <= 5.0: # part 1, const currrent
# current should be equal
self.assertEqual(output['current'][i],
output['current'][i - 1])
# voltage should not have decreased
self.assertTrue(output['voltage'][i],
output['voltage'][i - 1])
else: # part 2, const voltage
# current should be getting less positive
self.assertTrue(
output['current'][i] <= output['current'][i - 1],
msg=(output['current'][i - 2:i + 10],
output['time'][i - 2:i + 10]))
# voltage should decrease, then stay at 4.54
if output['voltage'][i - 1] == 4.54:
self.assertEqual(output['voltage'][i],
output['voltage'][i - 1])
else:
self.assertTrue(
output['voltage'][i] <= output['voltage'][i - 1])
# update index
i = i + 1
def test_verification_with_equivalent_circuit(self):
R = 50e-3 # ohm
R_L = 500 # ohm
C = 3 # farad
U_i = 2.7 # volt
U_f = 1.2 # volt
# setup experiment
ptree = PropertyTree()
ptree.put_double('discharge_power_lower_limit', 1e-2)
ptree.put_double('discharge_power_upper_limit', 1e+2)
ptree.put_int('steps_per_decade', 5)
ptree.put_double('initial_voltage', U_i)
ptree.put_double('final_voltage', U_f)
ptree.put_double('time_step', 15)
ptree.put_int('min_steps_per_discharge', 2000)
ptree.put_int('max_steps_per_discharge', 3000)
ragone = RagoneAnalysis(ptree)
# setup equivalent circuit database
device_database = PropertyTree()
device_database.put_double('series_resistance', R)
device_database.put_double('parallel_resistance', R_L)
device_database.put_double('capacitance', C)
# analytical solutions
E = {}
def E_SeriesRC(P):
U_0 = U_i / 2 + sqrt(U_i**2 / 4 - R * P)
return C / 2 * (-R * P * log(U_0**2 / U_f**2) + U_0**2 - U_f**2)
E['SeriesRC'] = E_SeriesRC
def E_ParallelRC(P):
U_0 = U_i / 2 + sqrt(U_i**2 / 4 - R * P)
tmp = (U_f**2 / R_L + P * (1 + R / R_L)) / \
(U_0**2 / R_L + P * (1 + R / R_L))
return C / 2 * (-R_L * P * log(tmp) - R * R_L / (R + R_L) * P * log(tmp * U_0**2 / U_f**2))
E['ParallelRC'] = E_ParallelRC
for device_type in ['SeriesRC', 'ParallelRC']:
# create a device
device_database.put_string('type', device_type)
device = EnergyStorageDevice(device_database)
# setup experiment and measure
ragone.reset()
ragone.run(device)
P = ragone._data['power']
E_computed = ragone._data['energy']
# compute the exact solution
E_exact = E[device_type](P)
# ensure the error is small
max_percent_error = 100 * linalg.norm(
(E_computed - E_exact) / E_computed,
inf)
self.assertLess(max_percent_error, 0.1)
parser.add_option('--param_' + str(p), type=float)
# parse the command line arguments
(options, args) = parser.parse_args()
# make device database
device_database = PropertyTree()
device_database.parse_xml('super_capacitor.xml')
# adjust the parameters in the database
options_dict = vars(options)
for var in options_dict:
path = uq_database.get_string('uq.' + var + '.name')
# next line is there to ensure that path already exists
old_value = device_database.get_double(path)
new_value = options_dict[var]
print var, path, new_value
device_database.put_double(path, new_value)
# build the energy storage device
device = EnergyStorageDevice(device_database.get_child('device'))
# parse the electrochmical impedance spectroscopy database
eis_database = PropertyTree()
eis_database.parse_xml('eis.xml')
# measure the impedance
impedance_spectrum_data = measure_impedance_spectrum(
device, eis_database.get_child('eis'))
# extract the results
frequency = impedance_spectrum_data['frequency']
complex_impedance = impedance_spectrum_data['impedance']
resistance = real(complex_impedance)
reactance = imag(complex_impedance)
modulus = absolute(complex_impedance)