pybop.models.lithium_ion

Submodules

• pybop.models.lithium_ion.base_echem
• pybop.models.lithium_ion.basic_SPMe
• pybop.models.lithium_ion.echem
• pybop.models.lithium_ion.weppner_huggins

Classes

DFN	Wraps the Doyle-Fuller-Newman (DFN) model for simulating lithium-ion batteries, as implemented in PyBaMM.
EChemBaseModel	Overwrites and extends BaseModel class for electrochemical PyBaMM models.
GroupedSPMe	Represents the grouped-parameter version of the SPMe.
MPM	Wraps the Multi-Particle-Model (MPM) model for simulating lithium-ion batteries, as implemented in PyBaMM.
MSMR	Wraps the Multi-Species-Multi-Reactions (MSMR) model for simulating lithium-ion batteries, as implemented in PyBaMM.
SPM	Wraps the Single Particle Model (SPM) for simulating lithium-ion batteries, as implemented in PyBaMM.
SPMe	Represents the Single Particle Model with Electrolyte (SPMe) for lithium-ion batteries.
WeppnerHuggins	Represents the Weppner & Huggins model to fit diffusion coefficients to GITT data.

Package Contents

class pybop.models.lithium_ion.DFN(name='Doyle-Fuller-Newman', eis: bool = False, **model_kwargs)

Bases: pybop.models.lithium_ion.base_echem.EChemBaseModel

Wraps the Doyle-Fuller-Newman (DFN) model for simulating lithium-ion batteries, as implemented in PyBaMM.

The DFN represents lithium-ion battery dynamics using multiple spherical particles to simulate the behaviour of the negative and positive electrodes. This model includes electrolyte dynamics, solid-phase diffusion, and Butler-Volmer kinetics. This model is the full-order representation used to reduce to the SPM, and SPMe models.

Parameters:

• name (str, optional) – The name for the model instance, defaulting to “Doyle-Fuller-Newman”.

• eis (bool, optional) – A flag to build the forward model for EIS predictions. Defaults to False.

• **model_kwargs (optional) –

  Valid PyBaMM model option keys and their values, for example: parameter_set : pybamm.ParameterValues or dict, optional

  The parameters for the model. If None, default parameters provided by PyBaMM are used.

  geometrydict, optional

  The geometry definitions for the model. If None, default geometry from PyBaMM is used.

  submesh_typesdict, optional

  The types of submeshes to use. If None, default submesh types from PyBaMM are used.

  var_ptsdict, optional

  The discretization points for each variable in the model. If None, default points from PyBaMM are used.

  spatial_methodsdict, optional

  The spatial methods used for discretization. If None, default spatial methods from PyBaMM are used.

  solverpybamm.Solver, optional

  The solver to use for simulating the model. If None, the default solver from PyBaMM is used.

  buildbool, optional

  If True, the model is built upon creation (default: False).

  optionsdict, optional

  A dictionary of options to customise the behaviour of the PyBaMM model.

class pybop.models.lithium_ion.EChemBaseModel(pybamm_model, name='Electrochemical Base Model', parameter_set=None, geometry=None, submesh_types=None, var_pts=None, spatial_methods=None, solver=None, eis=False, **model_kwargs)

Bases: pybop.models.base_model.BaseModel

Overwrites and extends BaseModel class for electrochemical PyBaMM models.

Parameters:

• pybamm_model (pybamm.BaseModel) – A subclass of the pybamm Base Model.

• name (str, optional) – The name for the model instance, defaulting to “Electrochemical Base Model”.

• parameter_set (pybamm.ParameterValues or dict, optional) – The parameters for the model. If None, default parameters provided by PyBaMM are used.

• geometry (dict, optional) – The geometry definitions for the model. If None, default geometry from PyBaMM is used.

• submesh_types (dict, optional) – The types of submeshes to use. If None, default submesh types from PyBaMM are used.

• var_pts (dict, optional) – The discretization points for each variable in the model. If None, default points from PyBaMM are used.

• spatial_methods (dict, optional) – The spatial methods used for discretization. If None, default spatial methods from PyBaMM are used.

• solver (pybamm.Solver, optional) – The solver to use for simulating the model. If None, the default solver from PyBaMM is used.

• eis (bool, optional) – A flag to build the forward model for EIS predictions. Defaults to False.

• **model_kwargs (optional) –

  Valid PyBaMM model option keys and their values. For example, build : bool, optional

  If True, the model is built upon creation (default: False).

  optionsdict, optional

  A dictionary of options to customise the behaviour of the PyBaMM model.

_check_params(inputs: pybop.models.base_model.Inputs, parameter_set: pybop.parameters.parameter_set.ParameterSet, allow_infeasible_solutions: bool = True)

Check compatibility of the model parameters.

Parameters:

• inputs (Inputs) – The input parameters for the simulation.

• parameter_set (pybop.ParameterSet) – A PyBOP parameter set object or a dictionary containing the parameter values.

• allow_infeasible_solutions (bool, optional) – If True, infeasible parameter values will be allowed in the optimisation (default: True).

Returns:

A boolean which signifies whether the parameters are compatible.

Return type:

bool

_set_initial_state(initial_state: dict, inputs: pybop.models.base_model.Inputs | None = None)

Set the initial state of charge or concentrations for the battery model.

Parameters:

• initial_state (dict) – A valid initial state, e.g. the initial state of charge or open-circuit voltage.

• inputs (Inputs) – The input parameters to be used when building the model.

approximate_capacity(parameter_set: pybop.parameters.parameter_set.ParameterSet | None = None)

Calculate an estimate for the nominal cell capacity. The estimate is computed by estimating the capacity of the positive electrode that lies between the stoichiometric limits corresponding to the upper and lower voltage limits.

Parameters:

parameter_set (dict, optional) – A dictionary containing the parameter values necessary for the calculation.

Returns:

The estimate of the nominal cell capacity [A.h].

Return type:

float

cell_mass(parameter_set: pybop.parameters.parameter_set.ParameterSet | None = None)

Calculate the total cell mass in kilograms.

This method uses the provided parameter set to calculate the mass of different components of the cell, such as electrodes, separator, and current collectors, based on their densities, porosities, and thicknesses. It then calculates the total mass by summing the mass of each component.

Parameters:

parameter_set (dict, optional) – A dictionary containing the parameter values necessary for the calculation.

Returns:

The total mass of the cell in kilograms.

Return type:

float

cell_volume(parameter_set: pybop.parameters.parameter_set.ParameterSet | None = None)

Calculate the total cell volume in m3.

This method uses the provided parameter set to calculate the total thickness of the cell including electrodes, separator, and current collectors. It then calculates the volume by multiplying by the cross-sectional area.

Parameters:

parameter_set (dict, optional) – A dictionary containing the parameter values necessary for the calculation.

Returns:

The total volume of the cell in m3.

Return type:

float

set_geometric_parameters()

Sets the parameters that can be changed when rebuilding the model.

Returns:

A dictionary of parameters that can be changed when rebuilding the model.

Return type:

dict

_built_initial_soc = None

_built_model = None

_disc = None

_electrode_soh

_electrode_soh_half_cell

_geometry

_mesh = None

_model_with_set_params = None

_parameter_set

_spatial_methods

_submesh_types

_unprocessed_model

_unprocessed_parameter_set

_var_pts

default_parameter_values

geometric_parameters

pybamm_model

class pybop.models.lithium_ion.GroupedSPMe(name='Grouped Single Particle Model with Electrolyte', eis=False, **model_kwargs)

Bases: pybop.models.lithium_ion.base_echem.EChemBaseModel

Represents the grouped-parameter version of the SPMe.

Parameters:

• name (str, optional) – A name for the model instance, defaults to “Grouped SPMe”.

• **model_kwargs (optional) –

  Valid PyBaMM model option keys and their values, for example: parameter_set : pybamm.ParameterValues or dict, optional

  The parameters for the model. If None, default parameters provided by PyBaMM are used.

  geometrydict, optional

  The geometry definitions for the model. If None, default geometry from PyBaMM is used.

  submesh_typesdict, optional

  The types of submeshes to use. If None, default submesh types from PyBaMM are used.

  var_ptsdict, optional

  The discretization points for each variable in the model. If None, default points from PyBaMM are used.

  spatial_methodsdict, optional

  The spatial methods used for discretization. If None, default spatial methods from PyBaMM are used.

  solverpybamm.Solver, optional

  The solver to use for simulating the model. If None, the default solver from PyBaMM is used.

  optionsdict, optional

  A dictionary of options to customise the behaviour of the PyBaMM model.

_check_params(inputs, parameter_set, allow_infeasible_solutions)

Check compatibility of the model parameters.

Parameters:

• inputs (Inputs) – The input parameters for the simulation.

• parameter_set (pybop.ParameterSet) – A PyBOP parameter set object or a dictionary containing the parameter values.

• allow_infeasible_solutions (bool, optional) – If True, infeasible parameter values will be allowed in the optimisation (default: True).

Returns:

A boolean which signifies whether the parameters are compatible.

Return type:

bool

_set_initial_state(initial_state: dict, inputs=None)

Set the initial state of charge for the grouped SPMe. Inputs are not used.

Parameters:

• initial_state (dict) – A valid initial state, e.g. the initial state of charge or open-circuit voltage.

• inputs (Inputs, optional) – The input parameters to be used when building the model.

class pybop.models.lithium_ion.MPM(name='Many Particle Model', eis: bool = False, **model_kwargs)

Bases: pybop.models.lithium_ion.base_echem.EChemBaseModel

Wraps the Multi-Particle-Model (MPM) model for simulating lithium-ion batteries, as implemented in PyBaMM.

The MPM represents lithium-ion battery dynamics using a distribution of spherical particles for each electrode. This model inherits the SPM class.

Parameters:

• name (str, optional) – The name for the model instance, defaulting to “Many Particle Model”.

• eis (bool, optional) – A flag to build the forward model for EIS predictions. Defaults to False.

• **model_kwargs (optional) –

  Valid PyBaMM model option keys and their values, for example: parameter_set : pybamm.ParameterValues or dict, optional

  The parameters for the model. If None, default parameters provided by PyBaMM are used.

  geometrydict, optional

  The geometry definitions for the model. If None, default geometry from PyBaMM is used.

  submesh_typesdict, optional

  The types of submeshes to use. If None, default submesh types from PyBaMM are used.

  var_ptsdict, optional

  The discretization points for each variable in the model. If None, default points from PyBaMM are used.

  spatial_methodsdict, optional

  The spatial methods used for discretization. If None, default spatial methods from PyBaMM are used.

  solverpybamm.Solver, optional

  The solver to use for simulating the model. If None, the default solver from PyBaMM is used.

  buildbool, optional

  If True, the model is built upon creation (default: False).

  optionsdict, optional

  A dictionary of options to customise the behaviour of the PyBaMM model.

class pybop.models.lithium_ion.MSMR(name='Multi Species Multi Reactions Model', eis: bool = False, **model_kwargs)

Bases: pybop.models.lithium_ion.base_echem.EChemBaseModel

Wraps the Multi-Species-Multi-Reactions (MSMR) model for simulating lithium-ion batteries, as implemented in PyBaMM.

The MSMR represents lithium-ion battery dynamics using a distribution of spherical particles for each electrode. This model inherits the DFN class.

Parameters:

• name (str, optional) – The name for the model instance, defaulting to “Multi Species Multi Reactions Model”.

• eis (bool, optional) – A flag to build the forward model for EIS predictions. Defaults to False.

• **model_kwargs (optional) –

  Valid PyBaMM model option keys and their values, for example: parameter_set : pybamm.ParameterValues or dict, optional

  The parameters for the model. If None, default parameters provided by PyBaMM are used.

  geometrydict, optional

  The geometry definitions for the model. If None, default geometry from PyBaMM is used.

  submesh_typesdict, optional

  The types of submeshes to use. If None, default submesh types from PyBaMM are used.

  var_ptsdict, optional

  The discretization points for each variable in the model. If None, default points from PyBaMM are used.

  spatial_methodsdict, optional

  The spatial methods used for discretization. If None, default spatial methods from PyBaMM are used.

  solverpybamm.Solver, optional

  The solver to use for simulating the model. If None, the default solver from PyBaMM is used.

  buildbool, optional

  If True, the model is built upon creation (default: False).

  optionsdict, optional

  A dictionary of options to customise the behaviour of the PyBaMM model.

class pybop.models.lithium_ion.SPM(name='Single Particle Model', eis: bool = False, **model_kwargs)

Bases: pybop.models.lithium_ion.base_echem.EChemBaseModel

Wraps the Single Particle Model (SPM) for simulating lithium-ion batteries, as implemented in PyBaMM.

The SPM is a simplified physics-based model that represents a lithium-ion cell using a single spherical particle to simulate the behaviour of the negative and positive electrodes.

Parameters:

• name (str, optional) – The name for the model instance, defaulting to “Single Particle Model”.

• eis (bool, optional) – A flag to build the forward model for EIS predictions. Defaults to False.

• **model_kwargs (optional) –

  Valid PyBaMM model option keys and their values, for example: parameter_set : pybamm.ParameterValues or dict, optional

  The parameters for the model. If None, default parameters provided by PyBaMM are used.

  geometrydict, optional

  The geometry definitions for the model. If None, default geometry from PyBaMM is used.

  submesh_typesdict, optional

  The types of submeshes to use. If None, default submesh types from PyBaMM are used.

  var_ptsdict, optional

  The discretization points for each variable in the model. If None, default points from PyBaMM are used.

  spatial_methodsdict, optional

  The spatial methods used for discretization. If None, default spatial methods from PyBaMM are used.

  solverpybamm.Solver, optional

  The solver to use for simulating the model. If None, the default solver from PyBaMM is used.

  buildbool, optional

  If True, the model is built upon creation (default: False).

  optionsdict, optional

  A dictionary of options to customise the behaviour of the PyBaMM model.

class pybop.models.lithium_ion.SPMe(name='Single Particle Model with Electrolyte', eis: bool = False, **model_kwargs)

Bases: pybop.models.lithium_ion.base_echem.EChemBaseModel

Represents the Single Particle Model with Electrolyte (SPMe) for lithium-ion batteries.

The SPMe extends the basic Single Particle Model (SPM) by incorporating electrolyte dynamics, making it suitable for simulations where electrolyte effects are non-negligible. This class provides a framework to define the model parameters, geometry, mesh types, discretization points, spatial methods, and numerical solvers for simulation within the PyBaMM ecosystem.

Parameters:

• name (str, optional) – A name for the model instance, defaults to “Single Particle Model with Electrolyte”.

• eis (bool, optional) – A flag to build the forward model for EIS predictions. Defaults to False.

• **model_kwargs (optional) –

  Valid PyBaMM model option keys and their values, for example: parameter_set : pybamm.ParameterValues or dict, optional

  The parameters for the model. If None, default parameters provided by PyBaMM are used.

  geometrydict, optional

  The geometry definitions for the model. If None, default geometry from PyBaMM is used.

  submesh_typesdict, optional

  The types of submeshes to use. If None, default submesh types from PyBaMM are used.

  var_ptsdict, optional

  The discretization points for each variable in the model. If None, default points from PyBaMM are used.

  spatial_methodsdict, optional

  The spatial methods used for discretization. If None, default spatial methods from PyBaMM are used.

  solverpybamm.Solver, optional

  The solver to use for simulating the model. If None, the default solver from PyBaMM is used.

  buildbool, optional

  If True, the model is built upon creation (default: False).

  optionsdict, optional

  A dictionary of options to customise the behaviour of the PyBaMM model.

class pybop.models.lithium_ion.WeppnerHuggins(name='Weppner & Huggins model', eis: bool = False, **model_kwargs)

Bases: pybop.models.lithium_ion.base_echem.EChemBaseModel

Represents the Weppner & Huggins model to fit diffusion coefficients to GITT data.

Parameters:

• name (str, optional) – A name for the model instance, defaults to “Weppner & Huggins model”.

• eis (bool, optional) – A flag to build the forward model for EIS predictions. Defaults to False.

• **model_kwargs (optional) –

  Valid PyBaMM model option keys and their values, for example: parameter_set : pybamm.ParameterValues or dict, optional

  The parameters for the model. If None, default parameters provided by PyBaMM are used.

  geometrydict, optional

  The geometry definitions for the model. If None, default geometry from PyBaMM is used.

  submesh_typesdict, optional

  The types of submeshes to use. If None, default submesh types from PyBaMM are used.

  var_ptsdict, optional

  The discretization points for each variable in the model. If None, default points from PyBaMM are used.

  spatial_methodsdict, optional

  The spatial methods used for discretization. If None, default spatial methods from PyBaMM are used.

  solverpybamm.Solver, optional

  The solver to use for simulating the model. If None, the default solver from PyBaMM is used.