Results handling¶
This worked example shows how to work with Breathe Design results objects, from quick equilibrium KPIs to dynamic simulations and batch runs.
You’ll learn to master:
- Fetch equilibrium KPIs for a baseline cell
- Inspect and compare designs
- Run a worked example simulation with a
Cycler - Explore dynamic data and plot key variables
- Scale up to batch simulations and summarize results
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from breathe_design import api_interface as api, Cycler
from breathe_design import api_interface as api, Cycler
The first result we can get from the api is the equilibrium KPIs
Designs & Equilibrium KPIs¶
We start with a baseline cell (here: "Molicel P45B").
get_eqm_kpis returns a results object with convenient accessors for capacity and other KPIs.
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eqm_results = api.get_eqm_kpis("Molicel P45B")
eqm_results = api.get_eqm_kpis("Molicel P45B")
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The results class is
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eqm_results.__class__
eqm_results.__class__
Out[39]:
breathe_design.results.SingleSimulationResults
With methods and attributes
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for attr in dir(eqm_results):
if not attr.startswith("_"):
print(f"{attr}")
for attr in dir(eqm_results):
if not attr.startswith("_"):
print(f"{attr}")
baseline capacity compare_designs design_names dynamic_data dynamic_kpis get_dynamic_data get_input_parameters get_kpis get_normalized_kpis get_summary kpis plot_dynamic_response plot_radar plot_sensitivities plot_voltage_response print_dynamic_variables
baseline provides a shortcut to the Baseline KPIs
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eqm_results.baseline
eqm_results.baseline
Out[41]:
KPI Capacity [Ah] 4.500000 Nominal Voltage [V] 3.656630 Energy [Wh] 16.454837 Gravimetric Energy Density [Wh/kg] 241.196608 Volumetric Energy Density [Wh/l] 665.310409 Minimum Anode Voltage [mV] 80.490746 Weight [g] 68.221675 Volume [l] 0.024733 Heat Capacity [kJ/K] 0.052220 Name: Baseline, dtype: float64
capacity gets the capacity value for the Baseline design
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eqm_results.capacity
eqm_results.capacity
Out[42]:
np.float64(4.499999999999997)
compare_designs compares the KPIs of the designs but will return an error if only the Baseline design is present
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try:
eqm_results.compare_designs()
except ValueError as e:
print(e)
try:
eqm_results.compare_designs()
except ValueError as e:
print(e)
Only Baseline design found. Cannot compare designs.
design_names gets list of design names.
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eqm_results.design_names
eqm_results.design_names
Out[44]:
['Baseline']
dynamic_data returns the dynamic data as result of passing a cycler to the api and running a simulation for each design and input parameter. However, in this case it will be empty as no designs or cycler objects were passed.
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eqm_results.dynamic_data
eqm_results.dynamic_data
Out[45]:
{}
get_input_parameters gets the original input parameters used for the api call.
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eqm_results.get_input_parameters()
eqm_results.get_input_parameters()
Out[46]:
{'base_battery': 'Molicel P45B', 'designs': [], 'formats': []}
get_kpis and kpis both return the kpi data. get_kpi can accept a design name and only return data for that design providing it exists.
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try:
eqm_results.get_kpis("testDesign")
except ValueError as e:
print(e)
try:
eqm_results.get_kpis("testDesign")
except ValueError as e:
print(e)
Design testDesign not found. Cannot normalize results.
get_normalized_kpis divides the values for each design by the Baseline values. If there is only a Baseline design this will return all 1.0s.
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eqm_results.get_normalized_kpis()
eqm_results.get_normalized_kpis()
Out[48]:
| Baseline | |
|---|---|
| KPI | |
| Capacity [Ah] | 1.0 |
| Nominal Voltage [V] | 1.0 |
| Energy [Wh] | 1.0 |
| Gravimetric Energy Density [Wh/kg] | 1.0 |
| Volumetric Energy Density [Wh/l] | 1.0 |
| Minimum Anode Voltage [mV] | 1.0 |
| Weight [g] | 1.0 |
| Volume [l] | 1.0 |
| Heat Capacity [kJ/K] | 1.0 |
get_summary prints a summary of the results
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eqm_results.get_summary()
eqm_results.get_summary()
Out[49]:
{'is_batch': False,
'num_simulations': 1,
'design_names': ['Baseline'],
'num_designs': 1,
'input_parameters': {'base_battery': 'Molicel P45B',
'designs': [],
'formats': []}}
plot_sensitivities plots the sensitivities of each KPI to variation in each design parameter
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eqm_results.plot_sensitivities()
eqm_results.plot_sensitivities()
Some of the methods will not work without designs or dynamic data generated from passing a cycler to the api
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try:
eqm_results.plot_radar()
except ValueError as e:
print(e)
try:
eqm_results.plot_radar()
except ValueError as e:
print(e)
Only Baseline design found. Cannot compare designs.
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try:
eqm_results.plot_dynamic_response()
except ValueError as e:
print(e)
try:
eqm_results.plot_dynamic_response()
except ValueError as e:
print(e)
No dynamic data available for this simulation
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try:
eqm_results.plot_voltage_response()
except ValueError as e:
print(e)
try:
eqm_results.plot_voltage_response()
except ValueError as e:
print(e)
No dynamic data available for this simulation
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try:
eqm_results.print_dynamic_variables()
except ValueError as e:
print(e)
try:
eqm_results.print_dynamic_variables()
except ValueError as e:
print(e)
No dynamic data available for this simulation
Designs & Dynamic Data¶
Lets add a virtual cell design and run a dynamic simulation in parallel with our baseline cell. In this example we will adjust the NPratio to a fixed value of 1.0.
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designs = [{"designName": "Lower NP", "NPratio": 1.0}]
designs = [{"designName": "Lower NP", "NPratio": 1.0}]
Build a Cycler¶
A Cycler describes the protocol (e.g., CC charge to a voltage limit).
Here we set units and (optionally) pass in the baseline capacity for relative C‑rates.
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cycler = Cycler(selected_unit="C", cell_capacity=eqm_results.capacity)
cycler = Cycler(selected_unit="C", cell_capacity=eqm_results.capacity)
Worked Example: P45B Charge Run¶
We’ll run one simulation using our cycler and a simple design list (including Baseline).
This returns a results object with:
.kpisand.get_kpis(designName)for design‑specific KPIs.compare_designs()to compare across designs.plot_*helpers for quick visualizations
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single_output = api.run_sim(
base_battery="Molicel P45B",
cycler=cycler.cccv(1.0, -1.0, 0.01, 4.2, 2.6, 60.0, 60.0),
designs=designs,
initialSoC=0.5,
initialTemperature_degC=25.0,
ambientTemperature_degC=25.0,
)
single_output = api.run_sim(
base_battery="Molicel P45B",
cycler=cycler.cccv(1.0, -1.0, 0.01, 4.2, 2.6, 60.0, 60.0),
designs=designs,
initialSoC=0.5,
initialTemperature_degC=25.0,
ambientTemperature_degC=25.0,
)
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single_output.kpis
single_output.kpis
Out[58]:
| Baseline | Lower NP | |
|---|---|---|
| KPI | ||
| Capacity [Ah] | 4.500000 | 4.626559 |
| Nominal Voltage [V] | 3.656630 | 3.659476 |
| Energy [Wh] | 16.454837 | 16.930780 |
| Gravimetric Energy Density [Wh/kg] | 241.196608 | 246.933081 |
| Volumetric Energy Density [Wh/l] | 665.310409 | 684.554009 |
| Minimum Anode Voltage [mV] | 80.490746 | 77.407029 |
| Weight [g] | 68.221675 | 68.564246 |
| Volume [l] | 0.024733 | 0.024733 |
| Heat Capacity [kJ/K] | 0.052220 | 0.052487 |
If we only want the equilibrium KPIs for a specific design, we can use .get_kpis(designName)
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single_output.get_kpis("Lower NP")
single_output.get_kpis("Lower NP")
Out[59]:
| Lower NP | |
|---|---|
| KPI | |
| Capacity [Ah] | 4.626559 |
| Nominal Voltage [V] | 3.659476 |
| Energy [Wh] | 16.930780 |
| Gravimetric Energy Density [Wh/kg] | 246.933081 |
| Volumetric Energy Density [Wh/l] | 684.554009 |
| Minimum Anode Voltage [mV] | 77.407029 |
| Weight [g] | 68.564246 |
| Volume [l] | 0.024733 |
| Heat Capacity [kJ/K] | 0.052487 |
We can now compare the results of our virtual cell design with the baseline cell.
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single_output.compare_designs()
single_output.compare_designs()
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single_output.plot_voltage_response()
single_output.plot_voltage_response()
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single_output.print_dynamic_variables()
single_output.print_dynamic_variables()
Available variables: Time voltModel voltAnode voltCathode ocvModel ocvAnode ocvCathode tempSurfaceModel socModel socAnode socCathode currModel heatFluxModel
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single_output.plot_dynamic_response("tempSurfaceModel")
single_output.plot_dynamic_response("tempSurfaceModel")
Batch Results¶
Now we scale up: pass lists (e.g., initialSoC) to evaluate multiple starting conditions in one call.
- Use
.get_summary()for an at‑a‑glance table across runs - Use
.get_dynamic_data(design)to retrieve time‑series data - Use
.plot_dynamic_response(variable)to visualize across designs/runs
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initial_socs = [0.1, 0.25, 0.5, 0.75, 0.9]
batch_output = api.run_sim(
base_battery="Molicel P45B",
cycler=cycler.cc_chg(1.0, 4.2),
designs=designs,
initialSoC=initial_socs, # List of SOC values
initialTemperature_degC=25.0,
ambientTemperature_degC=25.0,
)
initial_socs = [0.1, 0.25, 0.5, 0.75, 0.9]
batch_output = api.run_sim(
base_battery="Molicel P45B",
cycler=cycler.cc_chg(1.0, 4.2),
designs=designs,
initialSoC=initial_socs, # List of SOC values
initialTemperature_degC=25.0,
ambientTemperature_degC=25.0,
)
Here we get a different class but the methods should be the very similar
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batch_output.__class__
batch_output.__class__
Out[65]:
breathe_design.results.BatchSimulationResults
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for attr in dir(batch_output):
if not attr.startswith("_"):
print(f"{attr}")
for attr in dir(batch_output):
if not attr.startswith("_"):
print(f"{attr}")
baseline capacity compare_designs design_names dynamic_data dynamic_kpis first get_dynamic_data get_input_parameters get_kpis get_normalized_kpis get_summary num_simulations plot_dynamic_response plot_radar plot_sensitivities plot_voltage_response print_dynamic_variables
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batch_output.get_summary()
batch_output.get_summary()
Out[67]:
{'is_batch': True,
'num_simulations': 5,
'design_names': ['Baseline', 'Lower NP'],
'num_designs': 2,
'input_parameters': [{'base_battery': 'Molicel P45B',
'cycler': {'cycle_type': 'CC_CHG',
'selected_unit': 'C',
'control_parameters': {'I_chg': 1.0, 'V_max': 4.2}},
'designs': [{'designName': 'Lower NP', 'NPratio': 1.0}],
'initialSoC': 0.1,
'initialTemperature_degC': 25.0,
'ambientTemperature_degC': 25.0},
{'base_battery': 'Molicel P45B',
'cycler': {'cycle_type': 'CC_CHG',
'selected_unit': 'C',
'control_parameters': {'I_chg': 1.0, 'V_max': 4.2}},
'designs': [{'designName': 'Lower NP', 'NPratio': 1.0}],
'initialSoC': 0.25,
'initialTemperature_degC': 25.0,
'ambientTemperature_degC': 25.0},
{'base_battery': 'Molicel P45B',
'cycler': {'cycle_type': 'CC_CHG',
'selected_unit': 'C',
'control_parameters': {'I_chg': 1.0, 'V_max': 4.2}},
'designs': [{'designName': 'Lower NP', 'NPratio': 1.0}],
'initialSoC': 0.5,
'initialTemperature_degC': 25.0,
'ambientTemperature_degC': 25.0},
{'base_battery': 'Molicel P45B',
'cycler': {'cycle_type': 'CC_CHG',
'selected_unit': 'C',
'control_parameters': {'I_chg': 1.0, 'V_max': 4.2}},
'designs': [{'designName': 'Lower NP', 'NPratio': 1.0}],
'initialSoC': 0.75,
'initialTemperature_degC': 25.0,
'ambientTemperature_degC': 25.0},
{'base_battery': 'Molicel P45B',
'cycler': {'cycle_type': 'CC_CHG',
'selected_unit': 'C',
'control_parameters': {'I_chg': 1.0, 'V_max': 4.2}},
'designs': [{'designName': 'Lower NP', 'NPratio': 1.0}],
'initialSoC': 0.9,
'initialTemperature_degC': 25.0,
'ambientTemperature_degC': 25.0}]}
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batch_output.get_kpis()
batch_output.get_kpis()
Out[68]:
| Baseline | Lower NP | |
|---|---|---|
| KPI | ||
| Capacity [Ah] | 4.500000 | 4.626559 |
| Nominal Voltage [V] | 3.656630 | 3.659476 |
| Energy [Wh] | 16.454837 | 16.930780 |
| Gravimetric Energy Density [Wh/kg] | 241.196608 | 246.933081 |
| Volumetric Energy Density [Wh/l] | 665.310409 | 684.554009 |
| Minimum Anode Voltage [mV] | 80.490746 | 77.407029 |
| Weight [g] | 68.221675 | 68.564246 |
| Volume [l] | 0.024733 | 0.024733 |
| Heat Capacity [kJ/K] | 0.052220 | 0.052487 |
We can plot the variables of interest for the designs across the batch
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batch_output.plot_dynamic_response("voltModel")
batch_output.plot_dynamic_response("voltModel")
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batch_output.plot_dynamic_response("tempSurfaceModel")
batch_output.plot_dynamic_response("tempSurfaceModel")
We can also retrieve all of the dynamic data for the batch for all designs, or for a single design
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batch_output.dynamic_data
batch_output.dynamic_data
Out[71]:
[{'Baseline': {'Time': [0,
5.6218269514104555e-09,
5.6218269514104554e-08,
5.115862525783514e-07,
4.609898100156573e-06,
4.559301657593879e-05,
0.0004554242013337609,
0.0017231747057562892,
0.003928865814958606,
0.007481532612260344,
0.014308295900367671,
0.029243109233920907,
0.06080681194829878,
0.12335651995953212,
0.2451179040012637,
0.4866763882692177,
0.9740587099813205,
1.6666990472278949,
2.3593393844744694,
3.051979721721044,
3.7446200589676186,
4.437260396214193,
5.129900733460768,
5.822541070707342,
6.666743702525612,
7.510946334343882,
8.355148966162151,
9.400515651334981,
10.445882336507811,
11.491249021680641,
12.845682338138916,
14.200115654597191,
15.903978488904134,
17.607841323211076,
19.810192913100707,
22.551146981321843,
25.866932746562078,
29.941079713961738,
35.22819327040568,
42.656953376274,
50.08571348214231,
57.514473588010624,
64.94323369387894,
72.37199379974726,
81.8932987818724,
91.41460376399756,
100.93590874612269,
113.00745605432587,
125.07900336252905,
139.91264308566917,
154.7462828088093,
173.3799330045779,
195.93486453108602,
218.48979605759413,
241.04472758410225,
276.5627061294231,
312.0806846747439,
347.59866322006474,
400.1783690849596,
500.2445773316303,
552.5829912228274,
576.9781971472971,
584.649854939588,
592.3215127318788,
599.9931705241696,
607.6648283164604,
626.2668336782588,
648.0040489736142,
669.7412642689696,
691.4784795643251,
713.2156948596805,
752.0729057669361,
790.9301166741916,
829.7873275814471,
853.8378550186494,
877.8883824558517,
901.938909893054,
925.9894373302562,
950.0399647674585,
980.39629807004,
1014.742145107185,
1049.0879921443302,
1083.4338391814754,
1117.7796862186206,
1172.6743514376005,
1214.9562155266353,
1257.2380796156701,
1310.0199077350992,
1362.8017358545278,
1443.2345361302223,
1488.6279355375593,
1534.0213349448964,
1597.8976037652758,
1661.7738725856552,
1751.922227142592,
1928.5813289625278,
1965.40518233505,
2002.2290357075724,
2039.0528890800947,
2071.9388224359272,
2104.82475579176,
2151.82849955443,
2198.8322433171,
2245.8359870797703,
2292.8397308424405,
2339.8434746051107,
2386.847218367781,
2445.3691713151707,
2503.8911242625604,
2562.4130772099497,
2705.058533277745,
2728.542218560647,
2752.0259038435493,
2775.5095891264514,
2808.3004431102127,
2855.4653248827663,
2916.741955274694,
3002.9852968413543,
3035.9397004887437,
3051.0411298100817,
3051.0411298101117,
3051.246507912511,
3051.2465079125486,
3051.271889090545,
3051.2718890905826,
3051.2755374225535,
3051.2755374226012,
3051.2755377576004],
'voltModel': [3.3117314754311935,
3.311731475473621,
3.3117314758554235,
3.3117314792879977,
3.311731510055519,
3.3117318104978746,
3.311734579058731,
3.311741970853703,
3.311753209099335,
3.311770468579695,
3.311803672353021,
3.311876490702662,
3.312030195446999,
3.3123339576743906,
3.31292217983204,
3.3140759661811354,
3.316348171273453,
3.319470868532057,
3.322470399401189,
3.325378628055867,
3.32820494901598,
3.33095270036218,
3.333638024781692,
3.336256649218421,
3.339368105701341,
3.3423884157719774,
3.3453120199695676,
3.348831332316697,
3.3522343742320526,
3.355516923938384,
3.3595840672780195,
3.363476454917059,
3.3682011927991082,
3.3727936620027186,
3.3783302140286993,
3.3847764109427425,
3.392085500233051,
3.400229861076431,
3.4097043885134197,
3.421210664928292,
3.4310015642146867,
3.4396055330502056,
3.446946802948065,
3.4534399559744298,
3.460719755195254,
3.4671118505322305,
3.4729164697508277,
3.479564486707428,
3.485529166315743,
3.4924106054650914,
3.498778182729953,
3.506341496363981,
3.5149115024721107,
3.5221139636251375,
3.527706924342105,
3.534314824670698,
3.5403877658673806,
3.546677605817455,
3.556868048928696,
3.5836518604053977,
3.6008046651583623,
3.609327998115443,
3.611039324687422,
3.61251313978143,
3.614082436862599,
3.6157521306449634,
3.620279881744847,
3.6260897559088057,
3.6321753161332606,
3.638146248169577,
3.6441107256681184,
3.653900448538502,
3.6638500610019764,
3.6756528655558807,
3.6834234180718273,
3.6903069738362873,
3.696372902638304,
3.7016997670567817,
3.7068439281148047,
3.713764402050615,
3.721609481103146,
3.7292348100621977,
3.736871675750088,
3.7445367423558245,
3.7572816750729907,
3.7670936493203864,
3.776887196425018,
3.789427156694811,
3.8022172431158534,
3.821209071576309,
3.8318507636169152,
3.8425667142316353,
3.8574544809182307,
3.8720862199586286,
3.8922111199532776,
3.93134425216811,
3.9410310424705055,
3.9519408905367617,
3.9637435984220364,
3.9734966339718287,
3.982084632698736,
3.9953561699992024,
4.0095742955992995,
4.023247951483016,
4.036750816637662,
4.050793404088837,
4.06511646079052,
4.082454346121591,
4.098445554554013,
4.1123616106507335,
4.133593227869811,
4.135993979967104,
4.138292766075087,
4.140685571458225,
4.144160247223272,
4.149932389466441,
4.1595819543273915,
4.180983603599889,
4.193240608243772,
4.199999999999988,
4.199894756699426,
4.199999999999982,
4.199986964383741,
4.199999999999989,
4.199998360783237,
4.199999999999992,
4.199999999849493,
4.199999999999999],
'voltAnode': [0.34239064956639986,
0.34239064954265386,
0.34239064932883756,
0.3423906473963997,
0.34239062972661805,
0.34239043958001375,
0.34238843405265423,
0.34238243114391387,
0.34237267530184884,
0.34235753324827034,
0.34232848606023863,
0.34226484129708007,
0.3421305084268843,
0.3418650855341792,
0.3413513243626519,
0.3403431874373946,
0.33835157689574347,
0.3356218428336548,
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In [72]:
Copied!
batch_output.get_dynamic_data("Baseline")
batch_output.get_dynamic_data("Baseline")
Out[72]:
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