pybop.models.lithium_ion.echem

Classes

DFN	Wraps the Doyle-Fuller-Newman (DFN) model for simulating lithium-ion batteries, as implemented in PyBaMM.
GroupedSPM	Represents the grouped-parameter version of the Single Particle Model.
GroupedSPMe	Represents the grouped-parameter version of the Single Particle Model with Electrolyte (SPMe).
MPM	Wraps the Many Particle Model (MPM) for simulating lithium-ion batteries, as implemented in PyBaMM.
MSMR	Wraps the Multi-Species Multi-Reaction (MSMR) model for simulating lithium-ion batteries, as implemented in PyBaMM.
SPDiffusion	Represents the Single Particle Diffusion Model for GITT pulses.
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 for GITT pulses.

Module Contents

class pybop.models.lithium_ion.echem.DFN(name='Doyle-Fuller-Newman Model', 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) – A name for the model instance, defaulting to “Doyle-Fuller-Newman 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.echem.GroupedSPM(name='Grouped Single Particle Model', eis=False, **model_kwargs)

Bases: pybop.models.lithium_ion.base_echem.EChemBaseModel

Represents the grouped-parameter version of the Single Particle Model.

Parameters:

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

• **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.

apply_parameter_grouping()

class pybop.models.lithium_ion.echem.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 Single Particle Model with Electrolyte (SPMe).

Parameters:

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

• **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.

apply_parameter_grouping()

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

Bases: pybop.models.lithium_ion.base_echem.EChemBaseModel

Wraps the Many Particle Model (MPM) 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) – A 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.echem.MSMR(name='Multi-Species Multi-Reaction Model', eis: bool = False, **model_kwargs)

Bases: pybop.models.lithium_ion.base_echem.EChemBaseModel

Wraps the Multi-Species Multi-Reaction (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) – A name for the model instance, defaulting to “Multi-Species Multi-Reaction 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.echem.SPDiffusion(name='Single Particle Diffusion Model', eis: bool = False, **model_kwargs)

Bases: pybop.models.lithium_ion.base_echem.EChemBaseModel

Represents the Single Particle Diffusion Model for GITT pulses.

Parameters:

• name (str, optional) – A name for the model instance, defaulting to “Single Particle Diffusion 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.

  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.

apply_parameter_grouping(electrode)

class pybop.models.lithium_ion.echem.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) – A 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.echem.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, defaulting 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.echem.WeppnerHuggins(name='Weppner & Huggins Model', eis: bool = False, **model_kwargs)

Bases: pybop.models.lithium_ion.base_echem.EChemBaseModel

Represents the Weppner & Huggins model for GITT pulses.

Parameters:

• name (str, optional) – A name for the model instance, defaulting 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.

  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

apply_parameter_grouping(electrode)