PhD Studentship: Unlocking their potential: Modelling Accelerated Degradation in Ni-rich Li-ion Batteries - #48872

University of Warwick

Date: 2 weeks ago
City: Coventry
Contract type: Full time



UK Students, EU Students, International Students

Fully funded

Full Time

7th February 2024

29th February 2024



Supervisors: Prof. Louis Piper (Warwick Manufacturing Group (WMG), Dr. Florian Theil (Maths)


Electric vehicles employ Ni-rich layered oxides for their Li-ion batteries that offer high energy densities but also accelerated degradation. To avoid this degradation, < 3/4 of the available lithium is used. To reach electric vehicle targets for the next decade, design strategies are needed to increase battery cycle lifetimes. Recent battery studies have revealed the Li-ions can get trapped behind atomically thin surface layers formed by the oxygen loss. Modelling the transport properties across these boundaries is critical for identifying and evaluating engineering solutions.

This PhD project will have access to unique battery studies at Warwick to test their models. This PhD project is multi-disciplinary in nature; the goal is to quantitatively account for the formation of reduced surface (RS) layers on cathode particles starting from operando x-ray data for industry grade, full cells. The key steps of the project are to use Physics based surface diffusion models in the literature to derive continuum models which account for the growth of RS layers, to integrate the RS layer equations into standard electrochemical cell models such as the Doyle-Fuller-Newman (DFN) model and to calibrate the augmented DFN model against operando X-ray data of pouch cells built on the pilot line at WMG.

The overall aim is to augment well-established Physics based continuum models like the DFN model with components that account for the evolution of RS layers. A substantial literature on SEI layer growth (on anode particles) already exists, however the physics of RS layer growth is quite different. Several RS layer growth model types with varying complexity, starting from simple phenomenological growth models and potentially ending with surface diffusion models will be compared.

The development of the models spans disciplinary barriers as it involves the analysis of experimental data, identification of the most plausible model, and the derivation of the corresponding partial differential equations. The project will employ existing codes like PyBaMM to simulate the cell dynamics including RS layer growth.

Additional Funding Information

Awards for both UK residents and international applicants pay a stipend to cover maintenance as well as paying the university fees and a research training support. The stipend is at the standard UKRI rate.

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