Doyle-Fuller-Newman (DFN)

class pybamm.lithium_ion.DFN(options=None, name='Doyle-Fuller-Newman model', build=True)

Doyle-Fuller-Newman (DFN) model of a lithium-ion battery, from Marquis et al.[1]. See pybamm.lithium_ion.BaseModel for more details.

Examples

>>> import pybamm
>>> model = pybamm.lithium_ion.DFN()
>>> model.name
'Doyle-Fuller-Newman model'

Extends: pybamm.models.full_battery_models.lithium_ion.base_lithium_ion_model.BaseModel

class pybamm.lithium_ion.BasicDFN(name='Doyle-Fuller-Newman model')

Doyle-Fuller-Newman (DFN) model of a lithium-ion battery, from Marquis et al.[1].

This class differs from the pybamm.lithium_ion.DFN model class in that it shows the whole model in a single class. This comes at the cost of flexibility in comparing different physical effects, and in general the main DFN class should be used instead.

Parameters:

name (str, optional) – The name of the model.

Extends: pybamm.models.full_battery_models.lithium_ion.base_lithium_ion_model.BaseModel

class pybamm.lithium_ion.BasicDFNComposite(name='Composite graphite/silicon Doyle-Fuller-Newman model')

Doyle-Fuller-Newman (DFN) model of a lithium-ion battery with composite particles of graphite and silicon, from Ai et al.[2].

This class differs from the pybamm.lithium_ion.DFN model class in that it shows the whole model in a single class. This comes at the cost of flexibility in comparing different physical effects, and in general the main DFN class should be used instead.

Parameters:

name (str, optional) – The name of the model.

Extends: pybamm.models.full_battery_models.lithium_ion.base_lithium_ion_model.BaseModel

class pybamm.lithium_ion.BasicDFNHalfCell(options=None, name='Doyle-Fuller-Newman half cell model')

Doyle-Fuller-Newman (DFN) model of a lithium-ion battery with lithium counter electrode, adapted from Doyle et al.[3].

This class differs from the pybamm.lithium_ion.BasicDFN model class in that it is for a cell with a lithium counter electrode (half cell). This is a feature under development (for example, it cannot be used with the Experiment class for the moment) and in the future it will be incorporated as a standard model with the full functionality.

The electrode labeled “positive electrode” is the working electrode, and the electrode labeled “negative electrode” is the counter electrode. If the “negative electrode” is the working electrode, then the parameters for the “negative electrode” are used to define the “positive electrode”. This facilitates compatibility with the full-cell models.

Parameters:

• options (dict) – A dictionary of options to be passed to the model. For the half cell it should include which is the working electrode.

• name (str, optional) – The name of the model.

Extends: pybamm.models.full_battery_models.lithium_ion.base_lithium_ion_model.BaseModel

References

[1] (1,2)

Scott G. Marquis, Valentin Sulzer, Robert Timms, Colin P. Please, and S. Jon Chapman. An asymptotic derivation of a single particle model with electrolyte. Journal of The Electrochemical Society, 166(15):A3693–A3706, 2019. doi:10.1149/2.0341915jes.

[2]

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.

[3]

Marc Doyle, Thomas F. Fuller, and John Newman. Modeling of galvanostatic charge and discharge of the lithium/polymer/insertion cell. Journal of the Electrochemical society, 140(6):1526–1533, 1993. doi:10.1149/1.2221597.