FEIT Research Project Database

Methods to improve maritime energy efficiency


Project Leader: Chris Manzie
Collaborators: Michael Brear
Sponsors: DST Group
Primary Contact: Chris Manzie (manziec@unimelb.edu.au)
Keywords: applied control theory; artificial intelligence; autonomous systems; machine learning; maritime engineering
Disciplines: Electrical & Electronic Engineering,Mechanical Engineering
Domains:

Model Predictive Control and Energy Efficiency for Maritime Platform HV AC Systems

This project will examine Naval Platform heating and cooling requirements with the aim of minimising the energy required while maintaining full operational capability. This will improve both the operating range of the platform and reduce the environmental footprint, and will be achieved through optimal scheduling of systems to maintain operability within desired constraints.

Both equipment type and system control will be considered, with application of advanced control techniques (model predictive control) and advanced naval platform heating and cooling equipment and systems to be undertaken. There is the opportunity to involve AI or machine learning techniques in predicting the oncoming demands, which can then be used to schedule loads effectively.

A $10,000 stipend top up is available.

Students must be Australian citizens and have undertaken a degree in Electrical, Mechanical or cognate discipline.