A novel membrane-free flow battery for renewable energy storage: Prototype Design by Simulation

PROJECT REFERENCE NUMBER

Please select SCEBE-22SF-NMFFB-Chen from the drop-down list or add this to your proposal writeup.

BACKGROUND

The greatest challenge for renewable energy utilisation is the severe mismatch between energy demand and energy supply. Energy storage technologies is a promising way to address this challenge. Flow batteries, as a new large-scale energy storage method, have attracted increasing attention. The biggest problem for available flow battery prototypes is their high cost due to the expensive membranes inside them. It is urgent to develop novel membrane-free flow batteries to commercialise the flow battery technology. Accordingly, this PhD project deals with this critical issue for future large-scale energy storage systems. More specifically, the fundamental of heat and mass transfer are expected to be investigated by comprehensive simulation using CFD (computational fluid dynamics). The study is also expected to use machine learning to improve prediction. Based on such exploration, a novel flow battery prototype is expected to be designed and optimised.

AIMS

In this research study, the candidate is expected to:

-       Conduct a literature review on flow batteries and recognise the challenges and gaps in large-scale energy storage.

-       Numerical simulation, data analysis, and ML/AI for developing an advanced online prediction platform.

-       Develop and validate a novel prototype of a membrane-free flow battery for energy storage, considering flow optimisation.

REQUIREMENTS

The candidate is expected to write a detailed proposal, not more than 2000 words, clearly stating how any of the points above can be executed.

The successful candidate has:

• The candidate needs a Master's Degree in relevant Engineering and Science subjects with numerical simulation skills.

• Knowledge of energy storage systems, fluid dynamics, heat & mass transfer and machine learning techniques.

• Strong mathematical, analytical, and programming skills using MATLAB and ANSYS FLUENT.

• Excellent communication skills in spoken and written English and teamwork skills.

• Creativity, positive attitude, and perseverance.

A bench fee of £4000 is required for attendance of relevant conferences and training.

How to Apply

This project is available as a 3 years full-time or 6 years part-time PhD study programme. 

Candidates are encouraged to contact the research supervisors for the project before applying. 

Please note that emails to the supervisory team or enquires submitted via this project advert do not constitute formal applications; applicants should apply using our Application Process page, choosing Mechanical Engineering and their preferred intake date.  

Please send any other enquires regarding your application to: [Email Address Removed]