Boosting battery life with hybrid machine learning of degradation mechanisms
Boosting battery life with hybrid machine learning of degradation mechanisms
Battery degradation is a major obstacle in the global effort to decarbonize the economy. Achieving electric vehicle targets over the next decade will require innovative design strategies to extend battery lifetimes. This project offers an exciting opportunity to quantitatively investigate the mechanisms trapping Li-ions behind atomically thin surface layers caused by oxygen loss, using advanced machine learning techniques applied to high-quality X-ray data. The goal is to identify surface physics models that align with experimental measurements, contributing to the development of longer-lasting batteries.
Supervisors
Primary: Prof. Louis Piper, Warwick Manufacturing Group
Dr Florian Theil, Maths
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Project Overview
This project is mathematical in nature, focusing on minimizing discrepancies between model predictions and experimental data. It involves:
- Modeling and Equations: Working with coupled systems of partial differential equations, such as the Doyle-Fuller-Newman equations, widely used in battery modeling.
- Numerical Challenges: Addressing computational complexities by constructing reduced-order models using operator learning methods, simplifying the evaluation process compared to solving the full PDE system.
- Flexible Approach: Tailoring the focus to the background and interests of the PhD student. Whether the expertise is in mathematical theory (e.g. partial differential equations) or computational applications, this project can accommodate the strengths.
How to apply
This is a fully-funded 4-year PhD position based in the HetSys Centre for Doctoral Training at the University of Warwick. All applications must be made through the University's postgraduate application form with a deadline of 20 January 2025. Please see our How to ApplyLink opens in a new window page for further details on the application process. For further information about student funding, the integrated HetSys training programme and what life is like in the HetSys CDT, please visit the Study with Us page.