HDR Scholarship - AI-enabled battery health management systems

Project Supervisor

Dr Samson S. Yu

Additional Supervisor

A/Prof Wei Luo

Dr. Shuaifei Zhao

Institute

School of Engineering

Faculty

Faculty of Science, Engineering and Built Environment

Location

Deakin Burwood Campus

Research topic

This project aims to develop artificial intelligence (AI)-based monitoring and estimation models for battery maintenance in Australian heavy industries. Xcel Tech provides next-generation technological solutions to electric trucks for the mining industry, the research team will develop novel and application-based models for specific batteries used in Australian heavy industries, such as mining and agriculture, for the purpose of battery health monitoring, optimal charging and fault diagnosis.

Successful candidate will be supervised by Dr. Samson Yu at School of Engineering and Associate Professor Wei Luo at School of Information Technology. This multidisciplinary team will provide expertise necessary for the candidate to succeed in theoretical and applied research in this project. Industry partner Xcel Tech will provide batteries used in heavy industries for testing and possible implementation of the developed software models, improving battery efficiency and prolonging battery life and contributing to the decarbonization of Australian industry.

This PhD project is in collaboration with Xcel Tech. The project supports the research towards clean energy and battery storage technology.

Project aim

Due to the uniqueness of Australia’s mining sites - such as high temperature, low humidity and poor internet connection, a new plug-and-play software model and/or hardware device is needed to provide real-time monitoring and fault diagnosis for batteries used in these harsh conditions. These hardware devices and software models can help provide a range of features and functions, including but not limited to

(i) predictive maintenance, i.e., to predict when maintenance is due;

(ii) condition monitoring, i.e., detecting abnormalities such as temperature fluctuations, voltage variations, or electrolyte levels;

(iii) optimal charging strategies, i.e., dynamically adjusting charging schedules based on demand and battery health; and

(iv) energy management integration, i.e., working with control algorithms to collaboratively manage battery usage.

Important dates

Applications will remain open until a candidate has been appointed

Benefits

This scholarship is available over 3 year with possibility of up to 6 months extension:

Stipend of $45,550 per annum tax exempt (2025 rate)
Relocation allowance of $500-1500 (for single to family) for students moving from interstate.
Contribution to research purposes including travel: $1,500 per annum for three years
International students only: Tuition fees offset for the duration of 4 years. Single Overseas Student Health Cover policy for the duration of the student visa.

Eligibility criteria

To be eligible you must:

be a domestic or international candidate. Domestic includes candidates with Australian Citizenship, Australian Permanent Residency or New Zealand Citizenship.
meet Deakin's PhD entry requirements
be enrolling full time and hold an honours degree (first class) or an equivalent standard master's degree with a substantial research component.

Additional desirable criteria:

knowledge of electrical engineering or information technology, with background knowledge in circuits and systems, artificial intelligence, battery operations, and/or broad knowledge in electronics or machine learning
industry work experience in battery industry or energy industry, with a deep understanding of industry practices
possess strong oral and written communication skills as they will be required to meet with their academic and industry stakeholders on a regular basis
ability to travel between Deakin and the industry partner at least once a year for research finding communication and presentation.

Please refer to the research degree entry pathways page for further information.

How to apply

Please email a CV and cover letter (including your interest in the project) to Dr. Samson Yu. The CV should highlight your skills, education, publications and relevant work experience. If you are successful, you will then be invited to submit a formal application.