AI-Enhanced Battery Management and Safety for Battery Energy Storage Systems

This project will develop advanced battery management and safety technologies for next-generation energy storage systems, with a focus on improving performance, reliability, and lifespan. Working with industry partners, it will integrate artificial intelligence, physics-based modelling, and real-time sensing to accurately assess battery health, predict failures, and optimise operation under diverse conditions.

The research addresses critical challenges in deploying large-scale and second-life batteries for renewable energy integration, electric mobility, and grid stability. By detecting faults early and enhancing control strategies, the project aims to reduce downtime, improve safety, and lower lifecycle costs.

Outcomes include validated algorithms, prototype systems, and guidelines for industry adoption. This work will accelerate Australia's transition to a cleaner, more resilient energy system, strengthen local manufacturing and recycling capabilities, and create commercial opportunities in global energy storage markets.

This project is in colaboration with Advanced United Technologies. The successful candidate will have the opportunity to be embeded with the company during the candidature. 

Scholarship
~$49,206 per annum (UNSW main award + industry top-up)

Eligibility Criteria
Open to domestic and international candidates.

Further information:
For more information about this project please contact A/Prof Huadong Mo huadong.mo@unsw.edu.au

How to apply:
Please contact A/Prof Mo for your Expression of Interest, with a copy of your CV and academic transcripts. 

Information on the application process can be found here HDR Application Process

Application deadline: Open until filled