Bath Engineering & Design Studentships: Enabling Physics-Based Battery Models for Next-Generation Battery Management

An alternative start date may be possible if agreed with your intended supervisors and the Doctoral College.

Project Background:

The transition to battery electrification requires battery management systems (BMS) that are computationally efficient while retaining sufficient physical fidelity to predict cell behaviour, limitations and degradation. Physics-based electrochemical models, particularly the Doyle–Fuller–Newman (DFN), or pseudo-two-dimensional (P2D) model, provide a rigorous description of coupled lithium transport, electrochemical kinetics and electrical behaviour, but their computational complexity can limit their use in embedded real-time applications.

This PhD project will address a key challenge: how to retain the predictive capability of P2D-class models while making them suitable for microcontroller-based BMS, particularly under high-rate and dynamic operating conditions.

The project will build on recent advances in analytical and semi-analytical solutions of lithium transport. In particular, closed-form solutions for lithium diffusion within spherical active-material particles can substantially reduce the computational cost associated with resolving the solid-phase diffusion equations. Combined with efficient representations of electrolyte transport, these approaches offer a promising route towards analytical or semi-analytical P2D model suitable for real-time implementation.

The research will develop an embedded-ready P2D framework and an adaptive model hierarchy linking computationally efficient reduced-order models, such as the single-particle model with electrolyte dynamics (SPMe), to higher-fidelity P2D formulations. Model selection will be governed by physically motivated validity indicators, such as electrolyte concentration gradients, reaction-rate limitations, overpotential and dimensionless transport/kinetic criteria, rather than by fixed operating thresholds.

The project will further investigate descriptions of degradation, including SEI growth, lithium plating, mechanical cracking, and electrolyte depletion to enable physics-informed estimation of state of health (SOH), capacity and resistance fade. Parameter identification will combine physics-based inference with computationally efficient optimisation while explicitly considering identifiability, uncertainty and embedded resource constraints.

Models will be implemented in embedded C/C++ and assessed in terms of accuracy, stability, memory usage and execution time. Validation will combine high-fidelity P2D/DFN simulations with experimental data from commercial lithium-ion cells under high-rate and dynamic drive cycles, including UDDS and WLTP, with appropriate consideration of temperature and ageing.

Candidate requirements:

Applicants must have, or be about to obtain, a UK Honours degree 1st or 2.1, or international equivalent. A master’s level qualification would also be advantageous.

Non-UK applicants, who are not currently studying in the UK, must meet the programme’s English language requirement before the application deadline – no exceptions will be considered.

The successful candidate should have demonstrable experience in mathematical modelling of partial differential equations, electrochemical modelling, parameter identification, embedded implementations, and high performance computing.

Enquiries and Applications

Informal enquiries are encouraged. Direct these to Dr Hao Yuan - hy310@bath.ac.uk

Please follow the below instructions carefully.

You must make a formal application via the University of Bath’s online application form for a PhD in Mechanical Engineering

Please note that you can apply for a maximum of two PhD projects on this programme.

In the ‘Funding Your Studies’ section, you must select ‘University of Bath URSA’ from one of the drop-down menus.

In the ‘Your PhD project’ section, you must quote the project title in the PhD project title field, and you must quote the lead supervisor’s name in the field ‘Name of intended supervisor at University of Bath.’

If you are applying for two projects, you must quote the project title for your second choice project in the field ‘Project 2 Title’ and the lead supervisor’s name in ‘Name of intended supervisor for 2nd choice project at University of Bath.

You must ensure that you follow the above steps correctly. Failure to complete these steps will cause errors in the automated processing of your application and may mean that you are not considered for a particular project.

Equality, Diversity and Inclusion

We value a diverse research environment and strive to be an inclusive university, where difference is celebrated and respected. We encourage applications from under-represented groups.

If you have circumstances that you feel we should be aware of that have affected your educational attainment, then please feel free to tell us about it in your application form. The best way to do this is a short paragraph at the end of your personal statement.

The Disability Service ensures that individuals with disabilities are provided the support that they need. If you state if your application that you have a disability, the Disability Service will contact you as part of this process to discuss your needs.

Keywords

Physics-based battery modelling; Electrochemical modelling; Battery management; Parameter identification; Embedded systems; High performance computing

Funding Notes

Applicants will be considered for a studentship. The Faculty of Engineering and Design at the University of Bath has studentships available for Home and Overseas students. However, in line with UKRI policy, the number of studentships available to Overseas students are capped. Studentships cover tuition fees, provide a £1k per annum training support fee, and a maintenance stipend (£21,805 2026/27 rate). International students will be required to cover the cost of a Student visa and Immigration Health Surcharge from personal funds.