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Added graphite half-cell parameter files
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DrSOKane committed Jun 12, 2023
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377 changes: 377 additions & 0 deletions pybamm/input/parameters/lithium_ion/Chen2020_composite_halfcell.py
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import pybamm
import os


def graphite_LGM50_electrolyte_exchange_current_density_Chen2020(
c_e, c_s_surf, c_s_max, T
):
"""
Exchange-current density for Butler-Volmer reactions between graphite and LiPF6 in
EC:DMC.
References
----------
.. [1] Chang-Hui Chen, Ferran Brosa Planella, Kieran O’Regan, Dominika Gastol, W.
Dhammika Widanage, and Emma Kendrick. "Development of Experimental Techniques for
Parameterization of Multi-scale Lithium-ion Battery Models." Journal of the
Electrochemical Society 167 (2020): 080534.
Parameters
----------
c_e : :class:`pybamm.Symbol`
Electrolyte concentration [mol.m-3]
c_s_surf : :class:`pybamm.Symbol`
Particle concentration [mol.m-3]
c_s_max : :class:`pybamm.Symbol`
Maximum particle concentration [mol.m-3]
T : :class:`pybamm.Symbol`
Temperature [K]
Returns
-------
:class:`pybamm.Symbol`
Exchange-current density [A.m-2]
"""
m_ref = 6.48e-7 # (A/m2)(m3/mol)**1.5 - includes ref concentrations
E_r = 35000
arrhenius = pybamm.exp(E_r / pybamm.constants.R * (1 / 298.15 - 1 / T))

return (
m_ref * arrhenius * c_e**0.5 * c_s_surf**0.5 * (c_s_max - c_s_surf) ** 0.5
)


def silicon_ocp_lithiation_Mark2016(sto):
"""
silicon Open-circuit Potential (OCP) as a a function of the
stochiometry. The fit is taken from the Enertech cell [1], which is only accurate
for 0 < sto < 1.
References
----------
.. [1] Verbrugge M, Baker D, Xiao X. Formulation for the treatment of multiple
electrochemical reactions and associated speciation for the Lithium-Silicon
electrode[J]. Journal of The Electrochemical Society, 2015, 163(2): A262.
Parameters
----------
sto: double
Stochiometry of material (li-fraction)
Returns
-------
:class:`pybamm.Symbol`
OCP [V]
"""
p1 = -96.63
p2 = 372.6
p3 = -587.6
p4 = 489.9
p5 = -232.8
p6 = 62.99
p7 = -9.286
p8 = 0.8633

U_lithiation = (
p1 * sto**7
+ p2 * sto**6
+ p3 * sto**5
+ p4 * sto**4
+ p5 * sto**3
+ p6 * sto**2
+ p7 * sto
+ p8
)
return U_lithiation


def silicon_ocp_delithiation_Mark2016(sto):
"""
silicon Open-circuit Potential (OCP) as a a function of the
stochiometry. The fit is taken from the Enertech cell [1], which is only accurate
for 0 < sto < 1.
References
----------
.. [1] Verbrugge M, Baker D, Xiao X. Formulation for the treatment of multiple
electrochemical reactions and associated speciation for the Lithium-Silicon
electrode[J]. Journal of The Electrochemical Society, 2015, 163(2): A262.
Parameters
----------
sto: double
Stochiometry of material (li-fraction)
Returns
-------
:class:`pybamm.Symbol`
OCP [V]
"""
p1 = -51.02
p2 = 161.3
p3 = -205.7
p4 = 140.2
p5 = -58.76
p6 = 16.87
p7 = -3.792
p8 = 0.9937

U_delithiation = (
p1 * sto**7
+ p2 * sto**6
+ p3 * sto**5
+ p4 * sto**4
+ p5 * sto**3
+ p6 * sto**2
+ p7 * sto
+ p8
)
return U_delithiation


def silicon_LGM50_electrolyte_exchange_current_density_Chen2020(
c_e, c_s_surf, c_s_max, T
):
"""
Exchange-current density for Butler-Volmer reactions between silicon and LiPF6 in
EC:DMC.
References
----------
.. [1] Chang-Hui Chen, Ferran Brosa Planella, Kieran O’Regan, Dominika Gastol, W.
Dhammika Widanage, and Emma Kendrick. "Development of Experimental Techniques for
Parameterization of Multi-scale Lithium-ion Battery Models." Journal of the
Electrochemical Society 167 (2020): 080534.
Parameters
----------
c_e : :class:`pybamm.Symbol`
Electrolyte concentration [mol.m-3]
c_s_surf : :class:`pybamm.Symbol`
Particle concentration [mol.m-3]
c_s_max : :class:`pybamm.Symbol`
Maximum particle concentration [mol.m-3]
T : :class:`pybamm.Symbol`
Temperature [K]
Returns
-------
:class:`pybamm.Symbol`
Exchange-current density [A.m-2]
"""

m_ref = (
6.48e-7 * 28700 / 278000
) # (A/m2)(m3/mol)**1.5 - includes ref concentrations
E_r = 35000
arrhenius = pybamm.exp(E_r / pybamm.constants.R * (1 / 298.15 - 1 / T))

return (
m_ref * arrhenius * c_e**0.5 * c_s_surf**0.5 * (c_s_max - c_s_surf) ** 0.5
)


def electrolyte_diffusivity_Nyman2008(c_e, T):
"""
Diffusivity of LiPF6 in EC:EMC (3:7) as a function of ion concentration. The data
comes from [1]
References
----------
.. [1] A. Nyman, M. Behm, and G. Lindbergh, "Electrochemical characterisation and
modelling of the mass transport phenomena in LiPF6-EC-EMC electrolyte,"
Electrochim. Acta, vol. 53, no. 22, pp. 6356–6365, 2008.
Parameters
----------
c_e: :class:`pybamm.Symbol`
Dimensional electrolyte concentration
T: :class:`pybamm.Symbol`
Dimensional temperature
Returns
-------
:class:`pybamm.Symbol`
Solid diffusivity
"""

D_c_e = 8.794e-11 * (c_e / 1000) ** 2 - 3.972e-10 * (c_e / 1000) + 4.862e-10

# Nyman et al. (2008) does not provide temperature dependence

return D_c_e


def electrolyte_conductivity_Nyman2008(c_e, T):
"""
Conductivity of LiPF6 in EC:EMC (3:7) as a function of ion concentration. The data
comes from [1].
References
----------
.. [1] A. Nyman, M. Behm, and G. Lindbergh, "Electrochemical characterisation and
modelling of the mass transport phenomena in LiPF6-EC-EMC electrolyte,"
Electrochim. Acta, vol. 53, no. 22, pp. 6356–6365, 2008.
Parameters
----------
c_e: :class:`pybamm.Symbol`
Dimensional electrolyte concentration
T: :class:`pybamm.Symbol`
Dimensional temperature
Returns
-------
:class:`pybamm.Symbol`
Solid diffusivity
"""

sigma_e = (
0.1297 * (c_e / 1000) ** 3 - 2.51 * (c_e / 1000) ** 1.5 + 3.329 * (c_e / 1000)
)

# Nyman et al. (2008) does not provide temperature dependence

return sigma_e


# Load data in the appropriate format
path, _ = os.path.split(os.path.abspath(__file__))
graphite_ocp_Enertech_Ai2020_data = pybamm.parameters.process_1D_data(
"graphite_ocp_Enertech_Ai2020.csv", path=path
)


def graphite_ocp_Enertech_Ai2020(sto):
name, (x, y) = graphite_ocp_Enertech_Ai2020_data
return pybamm.Interpolant(x, y, sto, name=name, interpolator="cubic")


# Call dict via a function to avoid errors when editing in place
def get_parameter_values():
"""
Parameters for a composite graphite/silicon electrode, from the paper
Weilong Ai, Niall Kirkaldy, Yang Jiang, Gregory Offer, Huizhi Wang, and Billy
Wu. A composite electrode model for lithium-ion batteries with silicon/graphite
negative electrodes. Journal of Power Sources, 527:231142, 2022. URL:
https://www.sciencedirect.com/science/article/pii/S0378775322001604,
doi:https://doi.org/10.1016/j.jpowsour.2022.231142.
based on the paper
Chang-Hui Chen, Ferran Brosa Planella, Kieran O'Regan, Dominika Gastol, W.
Dhammika Widanage, and Emma Kendrick. Development of Experimental Techniques for
Parameterization of Multi-scale Lithium-ion Battery Models. Journal of The
Electrochemical Society, 167(8):080534, 2020. doi:10.1149/1945-7111/ab9050.
and references therein.
SEI parameters are example parameters for composite SEI on silicon/graphite. Both
phases use the same values, from the paper.
Xiao Guang Yang, Yongjun Leng, Guangsheng Zhang, Shanhai Ge, and Chao Yang Wang.
Modeling of lithium plating induced aging of lithium-ion batteries: transition
from linear to nonlinear aging. Journal of Power Sources, 360:28–40, 2017.
doi:10.1016/j.jpowsour.2017.05.110.
"""

return {
"chemistry": "lithium_ion",
# sei
"Primary: Ratio of lithium moles to SEI moles": 2.0,
"Primary: Inner SEI partial molar volume [m3.mol-1]": 9.585e-05,
"Primary: Outer SEI partial molar volume [m3.mol-1]": 9.585e-05,
"Primary: SEI resistivity [Ohm.m]": 200000.0,
"Primary: Initial inner SEI thickness [m]": 2.5e-09,
"Primary: Initial outer SEI thickness [m]": 2.5e-09,
"Primary: EC initial concentration in electrolyte [mol.m-3]": 4541.0,
"Primary: EC diffusivity [m2.s-1]": 2e-18,
"Primary: SEI kinetic rate constant [m.s-1]": 1e-12,
"Primary: SEI open-circuit potential [V]": 0.4,
"Primary: SEI growth activation energy [J.mol-1]": 0.0,
"Secondary: Ratio of lithium moles to SEI moles": 2.0,
"Secondary: Inner SEI partial molar volume [m3.mol-1]": 9.585e-05,
"Secondary: Outer SEI partial molar volume [m3.mol-1]": 9.585e-05,
"Secondary: SEI resistivity [Ohm.m]": 200000.0,
"Secondary: Initial inner SEI thickness [m]": 2.5e-09,
"Secondary: Initial outer SEI thickness [m]": 2.5e-09,
"Secondary: EC initial concentration in electrolyte [mol.m-3]": 4541.0,
"Secondary: EC diffusivity [m2.s-1]": 2e-18,
"Secondary: SEI kinetic rate constant [m.s-1]": 1e-12,
"Secondary: SEI open-circuit potential [V]": 0.4,
"Secondary: SEI growth activation energy [J.mol-1]": 0.0,
# cell
"Positive current collector thickness [m]": 1.2e-05,
"Positive electrode thickness [m]": 8.52e-05,
"Separator thickness [m]": 1.2e-05,
"Electrode height [m]": 0.065,
"Electrode width [m]": 1.58,
"Cell cooling surface area [m2]": 0.00531,
"Cell volume [m3]": 2.42e-05,
"Cell thermal expansion coefficient [m.K-1]": 1.1e-06,
"Positive current collector conductivity [S.m-1]": 58411000.0,
"Positive current collector density [kg.m-3]": 8960.0,
"Positive current collector specific heat capacity [J.kg-1.K-1]": 385.0,
"Positive current collector thermal conductivity [W.m-1.K-1]": 401.0,
"Nominal cell capacity [A.h]": 5.0,
"Current function [A]": 5.0,
"Contact resistance [Ohm]": 0,
# positive electrode
"Positive electrode conductivity [S.m-1]": 215.0,
"Primary: Maximum concentration in positive electrode [mol.m-3]": 28700.0,
"Primary: Initial concentration in positive electrode [mol.m-3]": 27700.0,
"Primary: Positive electrode diffusivity [m2.s-1]": 5.5e-14,
"Primary: Positive electrode OCP [V]": graphite_ocp_Enertech_Ai2020,
"Negative electrode porosity": 0.25,
"Primary: Positive electrode active material volume fraction": 0.735,
"Primary: Positive particle radius [m]": 5.86e-06,
"Positive electrode Bruggeman coefficient (electrolyte)": 1.5,
"Positive electrode Bruggeman coefficient (electrode)": 0,
"Positive electrode charge transfer coefficient": 0.5,
"Positive electrode double-layer capacity [F.m-2]": 0.2,
"Primary: Positive electrode exchange-current density [A.m-2]"
"": graphite_LGM50_electrolyte_exchange_current_density_Chen2020,
"Primary: Positive electrode density [kg.m-3]": 1657.0,
"Positive electrode specific heat capacity [J.kg-1.K-1]": 700.0,
"Positive electrode thermal conductivity [W.m-1.K-1]": 1.7,
"Primary: Positive electrode OCP entropic change [V.K-1]": 0.0,
"Secondary: Maximum concentration in positive electrode [mol.m-3]": 278000.0,
"Secondary: Initial concentration in positive electrode [mol.m-3]": 276610.0,
"Secondary: Positive electrode diffusivity [m2.s-1]": 1.67e-14,
"Secondary: Positive electrode lithiation OCP [V]"
"": silicon_ocp_lithiation_Mark2016,
"Secondary: Positive electrode delithiation OCP [V]"
"": silicon_ocp_delithiation_Mark2016,
"Secondary: Positive electrode active material volume fraction": 0.015,
"Secondary: Positive particle radius [m]": 1.52e-06,
"Secondary: Positive electrode exchange-current density [A.m-2]"
"": silicon_LGM50_electrolyte_exchange_current_density_Chen2020,
"Secondary: Positive electrode density [kg.m-3]": 2650.0,
"Secondary: Positive electrode OCP entropic change [V.K-1]": 0.0,
# separator
"Separator porosity": 0.47,
"Separator Bruggeman coefficient (electrolyte)": 1.5,
"Separator density [kg.m-3]": 397.0,
"Separator specific heat capacity [J.kg-1.K-1]": 700.0,
"Separator thermal conductivity [W.m-1.K-1]": 0.16,
# electrolyte
"Initial concentration in electrolyte [mol.m-3]": 1000.0,
"Cation transference number": 0.2594,
"Thermodynamic factor": 1.0,
"Electrolyte diffusivity [m2.s-1]": electrolyte_diffusivity_Nyman2008,
"Electrolyte conductivity [S.m-1]": electrolyte_conductivity_Nyman2008,
# experiment
"Reference temperature [K]": 298.15,
"Total heat transfer coefficient [W.m-2.K-1]": 10.0,
"Ambient temperature [K]": 298.15,
"Number of electrodes connected in parallel to make a cell": 1.0,
"Number of cells connected in series to make a battery": 1.0,
"Lower voltage cut-off [V]": 2.5,
"Upper voltage cut-off [V]": 4.2,
"Initial concentration in positive electrode [mol.m-3]": 29866.0,
"Initial temperature [K]": 298.15,
# citations
"citations": ["Chen2020", "Ai2022"],
}
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