Lead-Acid Models API

Electrochemical lead-acid battery models available in pybamm.lead_acid.

The pybamm.lead_acid module provides porous-electrode models for lead-acid batteries based on the asymptotic and full porous electrode frameworks.

Lead-acid models do not use particles (the "particle shape" option is fixed to "no particles"). Porosity changes during cycling are central to the lead-acid chemistry and are included automatically.

Available models

Class	Description
Full	Full porous electrode model (Newman-Tiedemann)
LOQS	Leading-Order Quasi-Static model
BasicFull	Simplified educational implementation of the full model

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pybamm.lead_acid.Full

Full porous electrode model for lead-acid, based on the Newman-Tiedemann framework. Resolves the full electrolyte concentration, potential, and porosity distributions.

pybamm.lead_acid.Full(options=None, name="Full model", build=True)

options · dict

Model options. See Options reference below.

name · str · default: "Full model"

Human-readable model name.

build · bool · default: "true"

Build the model on instantiation. Pass False to modify sub-models first.

Default parameter set: pybamm.ParameterValues("Sulzer2019")

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pybamm.lead_acid.LOQS

Leading-Order Quasi-Static model — an asymptotic reduction of the full model. Much faster than Full, valid at low C-rates.

pybamm.lead_acid.LOQS(options=None, name="LOQS model", build=True)

Default parameter set: pybamm.ParameterValues("Sulzer2019")

Default solver: pybamm.CasadiSolver()

LOQS uses the Jacobian disabled by default (use_jacobian = False) when dimensionality = 0 because the system is small enough that this is faster.

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pybamm.lead_acid.BasicFull

A simplified, single-file educational implementation of the full lead-acid model. Not intended for research — use Full instead.

pybamm.lead_acid.BasicFull(name="Basic Full model", build=True)

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Options reference

Lead-acid models accept the same base BatteryModelOptions dictionary as lithium-ion models, with the following notable options:

Option	Valid values	Default	Notes
"hydrolysis"	"false", "true"	"false"	Include oxygen evolution (hydrolysis). Requires "surface form" != "false".
"convection"	"none", "uniform transverse", "full transverse"	"none"	Electrolyte convection effects.
"surface form"	"false", "differential", "algebraic"	"false"	Surface potential formulation.
"operating mode"	"current", "voltage", "power", callable	"current"	External circuit operating mode.
"thermal"	"isothermal", "lumped", "x-lumped", "x-full"	"isothermal"	Thermal model.
"current collector"	"uniform", "potential pair", "potential pair quite conductive"	"uniform"	Current collector model.
"dimensionality"	0, 1, 2	0	Current collector dimensionality.

"hydrolysis": "true" requires "surface form" to be set to "differential" or "algebraic". Setting it alongside "surface form": "false" raises an error.

Default mesh points

The default var_pts for lead-acid models are:

{"x_n": 25, "x_s": 41, "x_p": 34, "y": 10, "z": 10}

Examples

Basic LOQS discharge

import pybamm

model = pybamm.lead_acid.LOQS()
param = pybamm.ParameterValues("Sulzer2019")

sim = pybamm.Simulation(model, parameter_values=param)
sim.solve([0, 3600])

sol = sim.solution
print(sol["Terminal voltage [V]"].entries)