battmo 0.2.3

Battery simulation with BattMo in Python.

---

PyBattMo

PyBattMo is a Python wrapper around the Julia-based BattMo.jl. The Battery Modelling Toolbox (BattMo) is a resource for continuum modelling of electrochemical devices. The initial development features a pseudo X-dimensional (PXD) framework for the Doyle-Fuller-Newman model of lithium-ion battery cells. This is currently a early release that implements a subset of features from the MATLAB version of BattMo.

BattMo Family

BattMo can be used through several interfaces:

• MATLAB
• Julia
• Python
• Web app

Installation

To install PyBattMo, use the following pip command:

pip install battmo

Quick start

Run examples using our internal library, for example the cell parameters from Chen et al.

Important tip: run the examples within a notebook or using cells in VSCode to make use of the high performance of Julia. Julia compiles the functions and objects that you use when you first run a code. Because of this, the second time you run the same code it is super fast! But to make use of this, you need to have a kernel that keeps running in between code executions. Therefore, it does work with jupytor notebooks.

P2D example

Here are a few examples to get you started:

from battmo import *
import plotly.express as px
import pandas as pd
import numpy as np

# Initialize the model
model = LithiumIonBattery()

# Load cell parameters and cycling protocol
cell_parameters = load_cell_parameters(from_default_set = "chen_2020")
cycling_protocol = load_cycling_protocol(from_default_set = "cc_discharge")

# Have a quick look into what kind of cell we're dealing with
quick_cell_check(cell_parameters)

# Set up the simulation
sim = Simulation(model, cell_parameters, cycling_protocol)

# Run the simulation
output = solve(sim)

# Have a look into which output quantities are available
print_info(output)

# Plotting using Plotly
df = to_pandas(output.time_series)
fig = px.line(df, x="Time", y="Voltage", title="Voltage curve")
fig.show()

# Use BattMo internal plotting functions
plot_dashboard(output, plot_type="contour")

Run a 3D simulation

from battmo import *

# Load parameter sets and settings
cell_parameters = load_cell_parameters(from_default_set="chen_2020")
cycling_protocol = load_cycling_protocol(from_default_set="cc_discharge")
model_settings = load_model_settings(from_default_set="p4d_cylindrical")
simulation_settings = load_model_settings(from_default_set="p4d_cylindrical")

# We adjust the parameters so that the simulation in this example is not too long

cell_parameters["Cell"]["OuterRadius"]                                   = 0.004
cell_parameters["NegativeElectrode"]["CurrentCollector"]["TabFractions"] = [0.5]
cell_parameters["PositiveElectrode"]["CurrentCollector"]["TabFractions"] = [0.5]
cell_parameters["NegativeElectrode"]["CurrentCollector"]["TabWidth"]     = 0.002
cell_parameters["PositiveElectrode"]["CurrentCollector"]["TabWidth"]     = 0.002
simulation_settings["AngularGridPoints"]                                 = 8

# Setup model and simulation
model = LithiumIonBattery(model_settings=model_settings)
sim = Simulation(model, cell_parameters, cycling_protocol, simulation_settings = simulation_settings)
output = solve(sim)

# Plot interative 3D results
plot_interactive_3d(output)

Documentation

Some additional examples are be found in the BattMo.jl documentation as well as a comprehensive documentation on the API and architecture of BattMo.jl.

Acknowledgements

BattMo has received funding from the European Union’s Horizon 2020 innovation program under grant agreement numbers:

• 875527 HYDRA
• 957189 BIG-MAP
• 101104013 BATMAX
• 101103997 DigiBatt