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2x parameterised DFN cell models (NMC & LFP). In support the new open standard Battery Parameter eXchange (BPX), an outcome of the Faraday Institution Multi-scale Modelling project.

License: Creative Commons Attribution Share Alike 4.0 International

Python 2.44% Jupyter Notebook 97.56%

about-energy-bpx-parameterisation's Introduction

About:Energy NMC111|Graphite & LFP|Graphite Cell Parameterisations for Battery Parameter eXchange (BPX)

About:Energy Limited, UK: https://www.aboutenergy.io

This repository contains parameters and validation simulations for a Doyle-Fuller-Newman (DFN) model of two cells:

  1. NMC Cell - 12.5 Ah NMC111|Graphite Pouch Cell
  2. LFP Cell - 2 Ah LFP|Graphite Cylindrical 18650 Cell

The parameters are supplied by About:Energy to support the new open standard Battery Parameter eXchange (BPX), an outcome of the Faraday Institution Multi-scale Modelling project.

About:Energy develops battery parameter sets for physics-based models by combining information from cycling data with electrochemical and physical measurements on electrodes harvested by cell teardown. For these cells, electrolyte, separator and thermal properties are informed from literature. Advanced datasheets and physics-based models for a wider range of commercially available cells will be made available as an About:Energy product in 2023.

For the LFP cell, we note some discrepancies in voltage and capacity prediction at higher rates in the limit of low state-of-charge (SOC) - these are attributed to the use of a 1D+1D DFN model, which is not capable of accounting for inhomogeneity within the cylindrical cell. Additionally, by comparison to an NMC positive electrode, the LFP positive electrode material is relatively less well described by the Fick's law diffusion and Butler-Volmer equation approximations defined by the basic BPX standard. A more refined model in conjunction with extensions to the BPX standard could widen the applicability of this parameter set.

The simulations use the package PyBaMM (Python Battery Mathematical Modelling).

๐Ÿš€ Installation

In order to run the notebooks in this repository, you will need to install a number of packages. We recommend installing within a virtual environment in order to not alter any Python distribution files on your machine.

PyBaMM is available on GNU/Linux, MacOS and Windows. For more detailed instructions on how to install PyBaMM, see the PyBaMM documentation.

Linux/Mac OS

To install the requirements on Linux/Mac OS use the following terminal commands, replacing "XXX" with the repository name:

  1. Clone the repository
https://github.com/About-Energy-OpenSource/XXX.git
  1. Change into the XXX directory
cd XXX
  1. Create a virtual environment
virtualenv env
  1. Activate the virtual environment
source env/bin/activate
  1. Install the required packages
pip install -r requirements.txt

Windows

To install the requirements on Windows use the following terminal commands, replacing "XXX" with the repository name:

  1. Clone the repository
https://github.com/About-Energy-OpenSource/XXX.git
  1. Change into the XXX directory
cd XXX
  1. Create a virtual environment
virtualenv env
  1. Activate the virtual environment
\path\to\env\Scripts\activate

where \path\to\env is the path to the environment created in step 3 (e.g. C:\Users\'Username'\env\Scripts\activate.bat).

  1. Install the required packages
pip install -r requirements.txt

As an alternative, you can set up Windows Subsystem for Linux. This allows you to run a full Linux distribution within Windows.

Troubleshooting

Problem: ModuleNotFoundError: No module named 'wheel'.

Solution: Try pip install wheel before pip install -r requirements.txt.

๐Ÿ“ซ Get in touch

If you have any questions or would like more information on battery parameterisation services, please get in touch via email [email protected].

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