Welcome to pybamm-param’s documentation!

Python Battery Mathematical Modelling (PyBaMM) Parameter Optimisation package is developed for optimising battery parameters of PyBaMM model parameters using various optimisation methods and error functions.

pybamm-param is hosted on Github. This page provides the API, or developer documentation for ‘’pybamm-param’’.

• Index

• Module Index

• Search Page

Quickstart

pybamm-param is available on GNU/Linux, MacOS and Windows.

Using pip

GNU/Linux and Windows

pip install pybamm-param

macOS

brew install sundials && pip install pybamm-param

Using conda

PyBaMM is available as a conda package through the conda-forge channel.

conda install -c conda-forge pybamm-param

API documentation

Contents:

• Cost Functions
  • Base Cost Function
  • Root Mean Square Error
  • Maximum Likelihood Estimation
• Optimisation Problems
  • Base Optimisation Problem
  • Data Fit
  • OCP Balance
• Optimisers
  • Base Optimiser
  • Scipy Minimize
  • Scipy Differential Evolution
• Optimisation Result
  • OptimisationResult

Indices and tables

• Index

• Module Index

• Search Page

Examples

Detailed examples can be viewed on the GitHub examples page, and run locally using jupyter notebook, or online through Google Colab.

Contributing

Contributions to pybamm-param and its development are welcome! If you have ideas for features, bug fixes, models, spatial methods, or solvers, we would love to hear from you.

Before contributing, please read the Contribution Guidelines.