Changing conditions¶

In this example we will simulate different ambient temperature conditions.

In [11]:

from breathe_design import api_interface as api
from breathe_design import Cycler
from breathe_design import enable_notebook_plotly

enable_notebook_plotly()

from breathe_design import api_interface as api from breathe_design import Cycler from breathe_design import enable_notebook_plotly enable_notebook_plotly()

Get the design parameters and equilibrium KPIs for the Molicel P45B.

In [12]:

base_params = api.get_design_parameters("Molicel P45B")
results = api.get_eqm_kpis("Molicel P45B")
baseline_capacity = results.capacity

base_params = api.get_design_parameters("Molicel P45B") results = api.get_eqm_kpis("Molicel P45B") baseline_capacity = results.capacity

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Now lets set up a cycler for 1C charge up to 4.2 V.

In [13]:

cycler = Cycler(selected_unit="C", cell_capacity=baseline_capacity)
cycler_dict = cycler.cc_chg(1.0, 4.2)
print(cycler_dict)

cycler = Cycler(selected_unit="C", cell_capacity=baseline_capacity) cycler_dict = cycler.cc_chg(1.0, 4.2) print(cycler_dict)

{'cycle_type': 'CC_CHG', 'selected_unit': 'C', 'control_parameters': {'I_chg': 1.0, 'V_max': 4.2}}

Now we can run a batch of simulations for different ambient temperature breakpoints. We can also define the initial temperature to be different to the ambient temperature.

In [14]:

output = api.run_sim(
    base_battery="Molicel P45B",
    cycler=cycler_dict,
    designs=[],
    initialSoC=0.5,
    initialTemperature_degC=20.0,
    ambientTemperature_degC=[15.0, 25.0],
)

output = api.run_sim( base_battery="Molicel P45B", cycler=cycler_dict, designs=[], initialSoC=0.5, initialTemperature_degC=20.0, ambientTemperature_degC=[15.0, 25.0], )

In [15]:

output.plot_dynamic_response("tempSurfaceModel")

output.plot_dynamic_response("tempSurfaceModel")

In [ ]: