Change battery form factor¶

In this example we will redesign a battery form factor. Thereafter compare our virtual cells to the baseline

In [1]:

from breathe_design import api_interface as api
from breathe_design import enable_notebook_plotly

enable_notebook_plotly()

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

In [2]:

cell = "Molicel P45B"

cell = "Molicel P45B"

We will begin with load the format of the Molicel P45B

In [3]:

base_format = api.get_battery_format(cell)
base_format

base_format = api.get_battery_format(cell) base_format

Out[3]:

{'shape': 'cylinder',
 'material': 'steel',
 'housingThickness_mm': 0.18,
 'diameter_mm': 21.21,
 'height_mm': 70,
 'innerDiameter_mm': 2.3}

We will now apply changes to the format we do this with get_updated_format method. We will generate 10% shorter cell compared to baseline

In [4]:

smaller_format = api.get_updated_format(
    base_battery=cell,
    name="smaller_format",
    height_mm=0.9 * base_format["height_mm"],
)
smaller_format

smaller_format = api.get_updated_format( base_battery=cell, name="smaller_format", height_mm=0.9 * base_format["height_mm"], ) smaller_format

Out[4]:

{'shape': 'cylinder',
 'material': 'steel',
 'housingThickness_mm': 0.18,
 'diameter_mm': 21.21,
 'height_mm': 63.0,
 'innerDiameter_mm': 2.3,
 'name': 'smaller_format'}

We will also create a cell with 10% smaller diameter

In [5]:

thinner_format = api.get_updated_format(
    base_battery=cell,
    name="thinner_format",
    diameter_mm=0.9 * base_format["diameter_mm"],
)
thinner_format

thinner_format = api.get_updated_format( base_battery=cell, name="thinner_format", diameter_mm=0.9 * base_format["diameter_mm"], ) thinner_format

Out[5]:

{'shape': 'cylinder',
 'material': 'steel',
 'housingThickness_mm': 0.18,
 'diameter_mm': 19.089000000000002,
 'height_mm': 70,
 'innerDiameter_mm': 2.3,
 'name': 'thinner_format'}

In [6]:

formats = [smaller_format, thinner_format]

formats = [smaller_format, thinner_format]

Now we can calculate all the equilibrium KPIs for each format using the get_eqm_kpis function. Instead of passing multiple designs as in previous examples, we now pass multiple formats.

In [7]:

results = api.get_eqm_kpis(cell, designs=[], formats=formats)

results = api.get_eqm_kpis(cell, designs=[], formats=formats)

In [8]:

results.get_kpis()

results.get_kpis()

Out[8]:

	Baseline	smaller_format	thinner_format
KPI
Capacity [Ah]	4.500000	4.882076	4.379541
Nominal Voltage [V]	3.656630	3.656630	3.656630
Energy [Wh]	16.454837	17.851948	16.014364
Gravimetric Energy Density [Wh/kg]	241.196608	282.773533	280.179666
Volumetric Energy Density [Wh/l]	665.310409	801.999042	799.383931
Minimum Anode Voltage [mV]	80.490746	80.490746	80.490746
Weight [g]	68.221675	63.131609	57.157481
Volume [l]	0.024733	0.022259	0.020033
Heat Capacity [kJ/K]	0.052220	0.049868	0.044967

These can be plotted using the compare_designs method in two different ways: one for a relative change in the KPIs and one for a delta change in the KPIs.

In [9]:

results.compare_designs("relative")

results.compare_designs("relative")

In [10]:

results.compare_designs("delta")

results.compare_designs("delta")

In [11]:

results.plot_radar()

results.plot_radar()