Python Battery Mathematical Modelling (PyBaMM)
By Valentin Sulzer, S. Marquis, Robert Timms, Martin Robinson, S. J. Chapman. Journal of Open Research Software, 2020
396 citations recorded by the source corpus.
As the UK battery modelling community grows, there is a clear need for software that uses modern software engineering techniques to facilitate cross-institutional collaboration and democratise research progress. The Python package PyBaMM aims to provide a flexible platform for implementation and comparison of new models and numerical methods. This is achieved by implementing models as expression trees and processing them in a modular fashion through a pipeline. Comprehensive testing provides robustness to changes and hence eases the implementation of model extensions. PyBaMM is open source and available on GitHub at https://github.com/pybamm-team/PyBaMM.
Subfields: Automotive Engineering, Computational Theory and Mathematics, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/47fb1982e907af188afd3645b46f2f34bc83fb16
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Automotive Engineering
- Widanalage Dhammika Widanage
- Xinhua Liu
- Shichun Yang
- Billy Wu
- Valentin Sulzer
- Anna G. Stefanopoulou
- David A. Howey
In Computational Theory and Mathematics
In Electrical and Electronic Engineering
- Widanalage Dhammika Widanage
- Xinhua Liu
- Shichun Yang
- Billy Wu
- Valentin Sulzer
- Anna G. Stefanopoulou
- David A. Howey
- Ferran Brosa Planella
Citations in the corpus
- The challenge and opportunity of battery lifetime prediction from field data (2021, background): “Advancing efficient physics-based models is one of the goals of the open-source battery modeling framework PyBaMM [94].”
- A continuum of physics-based lithium-ion battery models reviewed (2022, methodology): “The three models have been implemented in PyBaMM [118], and the code used can be found, jointly with some additional interactive examples, in the GitHub repository for this article (https://github.”
- Battery digital twins: Perspectives on the fusion of models, data and artificial intelligence for smart battery management systems (2020, methodology): “In recent years, the accessibility of these models has increased with the publication of open-source versions of these codes with notable examples including the Python Battery Mathematical Modelling platform (PyBaMM) [16] and LIONSIMBA [17] .”