Source code for pybamm.models.submodels.electrode.ohm.base_ohm

#
# Base class for Ohm's law submodels
#
import pybamm
from pybamm.models.submodels.electrode.base_electrode import BaseElectrode




class BaseModel(BaseElectrode):
    """A base class for electrode submodels that employ
    Ohm's law.

    Parameters
    ----------
    param : parameter class
        The parameters to use for this submodel
    domain : str
        Either 'negative' or 'positive'
    options : dict, optional
        A dictionary of options to be passed to the model."""

    def __init__(self, param, domain, options=None, set_positive_potential=True):
        super().__init__(param, domain, options, set_positive_potential)

    def _get_electrode_stoichiometry(self, variables, x_averaged=False):
        """
        Surface stoichiometry over the electrode, used for stoichiometry-dependent
        electrode conductivity. Returns None when unavailable (e.g. lead-acid or a
        planar lithium-metal electrode), in which case the conductivity falls back to
        a function of temperature only.
        """
        domain, Domain = self.domain_Domain
        if x_averaged:
            template = f"X-averaged {domain} {{}}particle surface stoichiometry"
        else:
            template = f"{Domain} {{}}particle surface stoichiometry"
        for phase in ("", "primary "):
            name = template.format(phase)
            if name in variables:
                return variables[name]
        return None



    def set_boundary_conditions(self, variables):
        Domain = self.domain.capitalize()

        if self.options.electrode_types["negative"] == "planar":
            return

        if self.domain == "negative":
            phi_s_cn = variables["Negative current collector potential [V]"]
            lbc = (phi_s_cn, "Dirichlet")
            rbc = (pybamm.Scalar(0), "Neumann")

        elif self.domain == "positive":
            lbc = (pybamm.Scalar(0), "Neumann")
            i_boundary_cc = variables["Current collector current density [A.m-2]"]
            T_p = variables["Positive electrode temperature [K]"]
            sto_p = self._get_electrode_stoichiometry(variables)
            sigma_eff = (
                self.param.p.sigma(sto_p, T_p)
                * variables["Positive electrode transport efficiency"]
            )
            rbc = (
                i_boundary_cc / pybamm.boundary_value(-sigma_eff, "right"),
                "Neumann",
            )

        phi_s = variables[f"{Domain} electrode potential [V]"]
        self.boundary_conditions[phi_s] = {"left": lbc, "right": rbc}