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Equivalent Circuit Model with Split OCV (SplitOCVR) | ||
===================================================== | ||
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.. autoclass:: pybamm.lithium_ion.SplitOCVR | ||
:members: | ||
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.. footbibliography:: |
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@@ -12,3 +12,4 @@ Lithium-ion Models | |
msmr | ||
yang2017 | ||
electrode_soh | ||
ecm_split_ocv |
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src/pybamm/models/full_battery_models/lithium_ion/basic_splitOCVR.py
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# | ||
# Equivalent Circuit Model with split OCV | ||
# | ||
import pybamm | ||
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class SplitOCVR(pybamm.BaseModel): | ||
"""Basic Equivalent Circuit Model that uses two OCV functions | ||
for each electrode. This model is easily parameterizable with minimal parameters. | ||
This class differs from the :class: pybamm.equivalent_circuit.Thevenin() due | ||
to dual OCV functions to make up the voltage from each electrode. | ||
Parameters | ||
---------- | ||
name: str, optional | ||
The name of the model. | ||
""" | ||
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def __init__(self, name="ECM with split OCV"): | ||
super().__init__(name) | ||
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###################### | ||
# Variables | ||
###################### | ||
# All variables are only time-dependent | ||
# No domain definition needed | ||
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theta_n = pybamm.Variable("Negative particle stoichiometry") | ||
theta_p = pybamm.Variable("Positive particle stoichiometry") | ||
Q = pybamm.Variable("Discharge capacity [A.h]") | ||
V = pybamm.Variable("Voltage [V]") | ||
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# model is isothermal | ||
I = pybamm.FunctionParameter("Current function [A]", {"Time [s]": pybamm.t}) | ||
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# Capacity equation | ||
self.rhs[Q] = I / 3600 | ||
self.initial_conditions[Q] = pybamm.Scalar(0) | ||
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# Capacity in each electrode | ||
Q_n = pybamm.Parameter("Negative electrode capacity [A.h]") | ||
Q_p = pybamm.Parameter("Positive electrode capacity [A.h]") | ||
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# State of charge electrode equations | ||
theta_n_0 = pybamm.Parameter("Negative electrode initial stoichiometry") | ||
theta_p_0 = pybamm.Parameter("Positive electrode initial stoichiometry") | ||
self.rhs[theta_n] = -I / Q_n / 3600 | ||
self.rhs[theta_p] = I / Q_p / 3600 | ||
self.initial_conditions[theta_n] = theta_n_0 | ||
self.initial_conditions[theta_p] = theta_p_0 | ||
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# Resistance for IR expression | ||
R = pybamm.Parameter("Ohmic resistance [Ohm]") | ||
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# Open-circuit potential for each electrode | ||
Un = pybamm.FunctionParameter( | ||
"Negative electrode OCP [V]", {"Negative particle stoichiometry": theta_n} | ||
) | ||
Up = pybamm.FunctionParameter( | ||
"Positive electrode OCP [V]", {"Positive particle stoichiometry": theta_p} | ||
) | ||
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# Voltage expression | ||
V = Up - Un - I * R | ||
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# Parameters for Voltage cutoff | ||
voltage_high_cut = pybamm.Parameter("Upper voltage cut-off [V]") | ||
voltage_low_cut = pybamm.Parameter("Lower voltage cut-off [V]") | ||
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self.variables = { | ||
"Negative particle stoichiometry": theta_n, | ||
"Positive particle stoichiometry": theta_p, | ||
"Current [A]": I, | ||
"Discharge capacity [A.h]": Q, | ||
"Voltage [V]": V, | ||
"Times [s]": pybamm.t, | ||
"Positive electrode OCP [V]": Up, | ||
"Negative electrode OCP [V]": Un, | ||
"Current function [A]": I, | ||
} | ||
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# Events specify points at which a solution should terminate | ||
self.events += [ | ||
pybamm.Event("Minimum voltage [V]", V - voltage_low_cut), | ||
pybamm.Event("Maximum voltage [V]", voltage_high_cut - V), | ||
pybamm.Event("Maximum Negative Electrode stoichiometry", 0.999 - theta_n), | ||
pybamm.Event("Maximum Positive Electrode stoichiometry", 0.999 - theta_p), | ||
pybamm.Event("Minimum Negative Electrode stoichiometry", theta_n - 0.0001), | ||
pybamm.Event("Minimum Positive Electrode stoichiometry", theta_p - 0.0001), | ||
] | ||
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@property | ||
def default_quick_plot_variables(self): | ||
return [ | ||
"Voltage [V]", | ||
["Negative particle stoichiometry", "Positive particle stoichiometry"], | ||
"Negative electrode OCP [V]", | ||
"Positive electrode OCP [V]", | ||
"Current [A]", | ||
] |
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