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PhD Lithium-Ion Battery Degradation and Performance Prediction in 2nd-Life Applications

PhD in Lithium-Ion Battery Degradation and Performance Prediction in 2nd-Life Applications

Project Overview

This project represents a unique opportunity to undertake a fully funded PhD studentship, sponsored by BP (subject to contract) in the broad area of electric vehicle (EV) battery sustainability and circular economy.

The concept of reusing EV batteries in a “2nd-life” - extending their useful life before being recycled is well established and seen as a vital part of sustainable EV adoption. It is well understood that lithium-ion batteries degrade, as they are used and over time. In their first years of service, this degradation is largely well understood. However, considerable uncertainty exists in how EV batteries will age during 2nd-life operation.

The aim of this PhD is to better define the underpinning ageing mechanisms that drive degradation within batteries during extended periods of use. One focus area will be the prediction of the onset of non-linear degradation later in battery life where battery capacity reduces more rapidly, which often indicates the battery is close to the end of its usable life: also known as the “knee-point”. In addition, this PhD will seek to identify if the trajectory of battery degradation can be significantly changed through different thermal management strategies or different electrical cycling strategies.

The focus of this PhD is primarily on experimental research to be conducted within the WMG Energy Innovation Centre with agreed periods of on-site work at BP (UK). The researcher will be required to design, implemented, and manage novel multidisciplinary experiments to generate the data required to underpin their recommendations and conclusions.


Essential and desirable criteria

The ideal candidate will have a background in engineering (electrical/mechanical/electrochemical), achieving a 1st or 2(1) in their undergraduate studies with a focus on engineering design and numerical analysis. A good understanding of sensor selection and instrumentation is essential. You will need to be pro-active, organised, and able to work well with technicians and laboratory support staff. Experience of software packages such as MATLAB and COMSOL are desirable.

Funding and Eligibility

Standard PhD at UKRI rates: £16,062 plus industrial top up £3000 per annum

Funding is available to eligible Home fee statusLink opens in a new window and UK domicile EU students.

To apply

To apply please complete our online enquiry form and upload your CV.

Please ensure you meet the minimum requirements before filling in the online form.

Key Information:

Funding Source: EPSRC iCASE

Stipend: £19,062

Supporting company: BP

Supervisor: Prof James Marco

Available to UK nationals and Home fees students

Start date: October 2022