Digital tools
PyBOP
The Python Battery Optimisation and Parameterisation (PyBOP) package provides methods for estimating and optimising battery model parameters, offering both deterministic and stochastic approaches with example workflows to assist users.
The modelling package, co-supported by the IntelLiGent project, enables parameter identification from data for various battery models, including the electrochemical and equivalent circuit models provided by the popular open-source PyBaMM package. Using the same approaches, PyBOP can also be used for design optimisation under user-defined operating conditions across a variety of model structures and design goals.
PyBOP facilitates optimisation with a range of methods, with diagnostics for examining optimiser performance and convergence at the cost and corresponding parameteres. Identified parameters can be used for prediction, on-line estimation and control, and design optimisation, accelerating battery research and development.
PyBOP emphasises clear and informative diagnostics and workflows to support users with varying levels of domain expertise, and provides access to a wide range of optimisation and sampling algorithms, whether you are conducting academic research, working in industry, are a student or simply just interested in battery technology and modelling.
IntelLiGent Battery Knowledge Navigator
The IntelLiGent Battery Knowledge Navigator is an advanced platform designed for battery data management and analysis. Developed within the IntelLiGent project, it employs semantic technologies such as RDF, SPARQL, and the BattINFO ontology, along with an SQL database infrastructure, to streamline storage and analysis of battery research data.
Key features include semantic integration for intricate data linkages, efficient management of large-scale battery datasets, and an interactive user interface adhering to FAIR principles. The platform also has integration potential with the Galvanalyser platform for seamless data exchange. Requirements for using the platform include Python, Blazegraph, and PostgreSQL.
The project is licensed under the MIT License, and acknowledgments are given to the EU H2020 project BIG-MAP for the BattINFO ontology and all contributors to the IntelLiGent project.
