bpx 0.1.0

BPX schema and parsers

BPX

An implementation of the Battery Parameter eXchange (BPX) format in Pydantic. BPX, an outcome of the Faraday Institution Multi-scale Modelling project, is an open standard for physics-based Li-ion battery models that has been developed to reduce costs and time-to-market through a common definition of physics-based battery models that can be used widely across industry. To find out more, visit the BPX website.

This repository features a Pydantic-based parser for JSON files in the BPX format, which validates your file against the schema.

To support the new open standard, About:Energy have supplied two parameters sets for an NMC and LFP cell. The BPX files and associated examples and information can be found on the A:E BPX Parameterisation repository.

To see how to use BPX with PyBaMM, check out the BPX example repository.

Prerequisites

• Python 3+

Installation

Create a new virtual environment, or activate an existing one (this example uses the python venv module, but you could use Anaconda and a conda environment)

python3 -m venv env
source env/bin/activate

Install the BPX module from the repository on GitHub

pip install git+https://github.com/pybamm-team/BPX.git

Usage

Create a python script similar to that below

import bpx

filename = 'path/to/my/file.json'
my_params = bpx.parse_bpx_file(filename)

my_params will now be of type BPX, which acts like a python dataclass with the same attributes as the BPX format. For example, you can print out the initial temperature of the cell using

print('Initial temperature of cell:', my_params.parameterisation.cell.initial_temperature)

Alternatively, you can export the BPX object as a dictionary and use the string names (aliases) of the parameters from the standard

my_params_dict = my_params.dict(by_alias=True)
print('Initial temperature of cell:', my_params_dict["Parameterisation"]["Cell"]["Initial temperature [K]"])

If you want to pretty print the entire object, you can use the devtools package to do this (remember to pip install devtools)

from devtools import pprint
pprint(my_params)

You can convert any Function objects in BPX to regular callable Python functions, for example:

positive_electrode_diffusivity = my_params.parameterisation.positive_electrode.diffusivity.to_python_function()
diff_at_one = positive_electrode_diffusivity(1.0)
print('positive electrode diffusivity at x = 1.0:', diff_at_one)

If you want to output the complete JSON schema in order to build a custom tool yourself, you can do so:

print(bpx.BPX.schema_json(indent=2))

According to the pydantic docs, the generated schemas are compliant with the specifications: JSON Schema Core, JSON Schema Validation and OpenAPI.