Skip to main content Skip to navigation

Unlocking their potential: Modelling Accelerated Degradation in Ni-rich Li-ion Batteries

FLORIANUSE

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

Summary:

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. 

Objectives:

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 

  1. Use Physics based surface diffusion models in the literature to derive continuum models which account for the growth of RS layers. 
  1. Integrate the RS layer equations into standard electrochemical cell models such as the Doyle-Fuller-Newman (DFN) model.  
  1. 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. Specifically, this step relies on the HetSys module PX912 (Multiscale modelling). The project will employ existing codes like PyBaMM to simulate the cell dynamics including RS layer growth. 

Are you interesting in applying for this project? Head over to our Study with Us page for information on the application process, funding, and the HetSys training programme

At the University of Warwick, we strongly value equity, diversity and inclusion, and HetSys will provide a healthy working environment, dedicated to outstanding scientific guidance, mentorship and personal development.

HetSys is proud to be a part of the Engineering Department which holds an Athena SWAN Silver award, a national initiative to promote gender equality for all staff and students.