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julian-evers committed Oct 14, 2023
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2 changes: 1 addition & 1 deletion README.md
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#

![logo](https://raw.githubusercontent.com/pybamm-team/pybamm-tea/main/docs/pybamm_tea_logo.png)
![logo](pybamm_tea_logo.png)


# PyBaMM-TEA
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671 changes: 0 additions & 671 deletions examples/Potentials and capacities.ipynb
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2 changes: 1 addition & 1 deletion examples/stackbreakdown.ipynb
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.9.12"
},
"orig_nbformat": 4,
"vscode": {
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330 changes: 138 additions & 192 deletions pybamm_tea/tea.py
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Expand Up @@ -333,209 +333,155 @@ def print_stack_breakdown(self):
def print_stack_energy_densities(self):
"""A dataframe with capacities, energy densities, stoichiometry- and potential windows, n/p ratios, (single-)stack thickness and stack density."""
stack_ed = self.stack_energy_densities
data = [
{
"Parameter": "Volumetric energy density",
"Unit": "Wh.L-1",
"Value": stack_ed.get("Volumetric stack energy density [Wh.L-1]"),
},
{
"Parameter": "Gravimetric energy density",
"Unit": "Wh.kg-1",
"Value": stack_ed.get("Gravimetric stack energy density [Wh.kg-1]"),
},
{
"Parameter": "Stack average OCP",
"Unit": "V",
"Value": stack_ed.get("Stack average OCP [V]"),
},
{
"Parameter": "Capacity",
"Unit": "mA.h.cm-2",
"Value": stack_ed.get("Capacity [mA.h.cm-2]"),
},
{
"Parameter": "(Single-) stack thickness",
"Unit": "um",
"Value": 10**6 * stack_ed.get("Stack thickness [m]"),
},
{
"Parameter": "Stack density",
"Unit": "kg.L-1",
"Value": 10**-3 * stack_ed.get("Stack density [kg.m-3]"),
},
]
# Create the DataFrame from the list of dictionaries

data = {
"Parameter": [
"Volumetric energy density",
"Gravimetric energy density",
"Stack average OCP",
"Capacity",
"(Single-) stack thickness",
"Stack density",
],
"Unit": [
"Wh.L-1",
"Wh.kg-1",
"V",
"mA.h.cm-2",
"um",
"kg.L-1",
],
"Value": [
stack_ed.get("Volumetric stack energy density [Wh.L-1]"),
stack_ed.get("Gravimetric stack energy density [Wh.kg-1]"),
stack_ed.get("Stack average OCP [V]"),
stack_ed.get("Capacity [mA.h.cm-2]"),
10**6 * stack_ed.get("Stack thickness [m]"),
10**-3 * stack_ed.get("Stack density [kg.m-3]"),
],
}
# Create the DataFrame from the dictionary
df = pd.DataFrame(data)
return df

def print_capacities_and_potentials(self):
"""A dataframe with capacities, energy densities, stoichiometry- and potential windows, n/p ratios, (single-)stack thickness and stack density."""
stack_ed = self.stack_energy_densities
data = [
# stack potentials
{"Parameter": "Stack potentials", "Unit": "", "Value": ""},
{
"Parameter": "Stack average OCP",
"Unit": "V",
"Value": stack_ed.get("Stack average OCP [V]"),
},
{
"Parameter": "Maximal OCP",
"Unit": "V",
"Value": stack_ed.get("Maximal OCP [V]"),
},
{
"Parameter": "Minimal OCP",
"Unit": "V",
"Value": stack_ed.get("Minimal OCP [V]"),
},
# electrode potentials
{"Parameter": "Electrode potentials", "Unit": "", "Value": ""},
{
"Parameter": "Negative electrode average OCP",
"Unit": "V",
"Value": stack_ed.get("Negative electrode average OCP [V]"),
},
{
"Parameter": "Positive electrode average OCP",
"Unit": "V",
"Value": stack_ed.get("Positive electrode average OCP [V]"),
},
# n/p ratio
{"Parameter": "n/p ratio's", "Unit": "", "Value": ""},
{
"Parameter": "Practical n/p ratio",
"Unit": "-",
"Value": stack_ed.get("Practical n/p ratio"),
},
{
"Parameter": "Theoretical n/p ratio",
"Unit": "-",
"Value": self.parameter_values.get("Theoretical n/p ratio"),
},
# stack capacities
{"Parameter": "Stack capacities", "Unit": "", "Value": ""},
{
"Parameter": "Volumetric stack capacity",
"Unit": "Ah.L-1",
"Value": stack_ed.get("Volumetric stack capacity [Ah.L-1]"),
},
{
"Parameter": "Gravimetric stack capacity",
"Unit": "Ah.kg-1",
"Value": stack_ed.get("Gravimetric stack capacity [Ah.kg-1]"),
},
{
"Parameter": "Capacity",
"Unit": "mA.h.cm-2",
"Value": stack_ed.get("Capacity [mA.h.cm-2]"),
},
# electrode capacities
{"Parameter": "Electrode capacities", "Unit": "", "Value": ""},
{
"Parameter": "Negative electrode theoretical capacity",
"Unit": "mA.h.cm-2",
"Value": stack_ed.get(
"Negative electrode theoretical capacity [mA.h.cm-2]"
),
},
{
"Parameter": "Positive electrode theoretical capacity",
"Unit": "mA.h.cm-2",
"Value": stack_ed.get(
"Positive electrode theoretical capacity [mA.h.cm-2]"
),
},
{
"Parameter": "Negative electrode volumetric capacity",
"Unit": "mA.h.cm-3",
"Value": stack_ed.get(
"Negative electrode volumetric capacity [mA.h.cm-3]"
),
},
{
"Parameter": "Positive electrode volumetric capacity",
"Unit": "mA.h.cm-3",
"Value": stack_ed.get(
"Positive electrode volumetric capacity [mA.h.cm-3]"
),
},
{
"Parameter": "Negative electrode gravimetric capacity",
"Unit": "mA.h.g-1",
"Value": stack_ed.get(
"Negative electrode gravimetric capacity [mA.h.g-1]"
),
},
{
"Parameter": "Positive electrode gravimetric capacity",
"Unit": "mA.h.g-1",
"Value": stack_ed.get(
"Positive electrode gravimetric capacity [mA.h.g-1]"
),
},
# active material capacities
{"Parameter": "Active material capacities", "Unit": "", "Value": ""},
{
"Parameter": "Negative electrode active material practical capacity",
"Unit": "mA.h.g-1",
"Value": stack_ed.get(
"Negative electrode active material practical capacity [mA.h.g-1]"
),
},
{
"Parameter": "Positive electrode active material practical capacity",
"Unit": "mA.h.g-1",
"Value": stack_ed.get(
"Positive electrode active material practical capacity [mA.h.g-1]"
),
},
{
"Parameter": "Negative electrode active material theoretical capacity",
"Unit": "mA.h.g-1",
"Value": self.parameter_values.get(
"Negative electrode active material capacity [mA.h.g-1]"
),
},
{
"Parameter": "Positive electrode active material theoretical capacity",
"Unit": "mA.h.g-1",
"Value": self.parameter_values.get(
"Positive electrode active material capacity [mA.h.g-1]"
),
},
# stoichiometries
{"Parameter": "Stoichiometries", "Unit": "", "Value": ""},
{
"Parameter": "Negative electrode stoichiometry at 0% SoC",
"Unit": "-",
"Value": stack_ed.get("Negative electrode stoichiometry at 0% SoC"),
},
{
"Parameter": "Negative electrode stoichiometry at 100% SoC",
"Unit": "-",
"Value": stack_ed.get("Negative electrode stoichiometry at 100% SoC"),
},
{
"Parameter": "Positive electrode stoichiometry at 100% SoC",
"Unit": "-",
"Value": stack_ed.get("Positive electrode stoichiometry at 100% SoC"),
},
{
"Parameter": "Positive electrode stoichiometry at 0% SoC",
"Unit": "-",
"Value": stack_ed.get("Positive electrode stoichiometry at 0% SoC"),
},
]
# Create the DataFrame from the list of dictionaries

data = {
"Parameter": [
"",
"Stack average OCP",
"Maximal OCP",
"Minimal OCP",
"",
"Negative electrode average OCP",
"Positive electrode average OCP",
"",
"n/p ratio's",
"Practical n/p ratio",
"Theoretical n/p ratio",
"",
"Stack capacities",
"Volumetric stack capacity",
"Gravimetric stack capacity",
"Capacity",
"",
"Electrode capacities",
"Negative electrode theoretical capacity",
"Positive electrode theoretical capacity",
"Negative electrode volumetric capacity",
"Positive electrode volumetric capacity",
"Negative electrode gravimetric capacity",
"Positive electrode gravimetric capacity",
"",
"Active material capacities",
"Negative electrode active material practical capacity",
"Positive electrode active material practical capacity",
"Negative electrode active material theoretical capacity",
"Positive electrode active material theoretical capacity",
"",
"Stoichiometries",
"Negative electrode stoichiometry at 0% SoC",
"Negative electrode stoichiometry at 100% SoC",
"Positive electrode stoichiometry at 100% SoC",
"Positive electrode stoichiometry at 0% SoC",
],
"Unit": [
"",
"V",
"V",
"V",
"",
"V",
"V",
"",
"-",
"-",
"",
"A.h.L-1",
"A.h.kg-1",
"mA.h.cm-2",
"",
"mA.h.cm-2",
"mA.h.cm-2",
"A.h.L-1",
"A.h.L-1",
"A.h.kg-1",
"A.h.kg-1",
"",
"A.h.kg-1",
"A.h.kg-1",
"A.h.kg-1",
"A.h.kg-1",
"",
"-",
"-",
"-",
"-",
],
"Value": [
"",
stack_ed.get("Stack average OCP [V]"),
stack_ed.get("Maximal OCP [V]"),
stack_ed.get("Minimal OCP [V]"),
"",
stack_ed.get("Negative electrode average OCP [V]"),
stack_ed.get("Positive electrode average OCP [V]"),
"",
stack_ed.get("Practical n/p ratio"),
self.parameter_values.get("Theoretical n/p ratio"),
"",
stack_ed.get("Volumetric stack capacity [Ah.L-1]"),
stack_ed.get("Gravimetric stack capacity [Ah.kg-1]"),
stack_ed.get("Capacity [mA.h.cm-2]"),
"",
stack_ed.get("Negative electrode theoretical capacity [mA.h.cm-2]"),
stack_ed.get("Positive electrode theoretical capacity [mA.h.cm-2]"),
stack_ed.get("Negative electrode volumetric capacity [mA.h.cm-3]"),
stack_ed.get("Positive electrode volumetric capacity [mA.h.cm-3]"),
stack_ed.get("Negative electrode gravimetric capacity [mA.h.g-1]"),
stack_ed.get("Positive electrode gravimetric capacity [mA.h.g-1]"),
"",
stack_ed.get("Negative electrode active material practical capacity [mA.h.g-1]"),
stack_ed.get("Positive electrode active material practical capacity [mA.h.g-1]"),
self.parameter_values.get("Negative electrode active material capacity [mA.h.g-1]"),
self.parameter_values.get("Positive electrode active material capacity [mA.h.g-1]"),
"",
stack_ed.get("Negative electrode stoichiometry at 0% SoC"),
stack_ed.get("Negative electrode stoichiometry at 100% SoC"),
stack_ed.get("Positive electrode stoichiometry at 100% SoC"),
stack_ed.get("Positive electrode stoichiometry at 0% SoC"),
],
}
# Create the DataFrame from the dictionary
df = pd.DataFrame(data)
return df



def calculate_stack_energy_densities(self):
"""Calculate ideal volumetric and gravimetric energy densities on stack level."""
stack_ed = {} # stack energy densities dict
pava = None
pava = self.parameter_values # parameter values

# stoichiometries - calculation based on input stoichiometries or cell potential limits
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