The optimisation of operational strategies for CO2 heat pumps through advanced computational methodologies represents a pioneering endeavour in the realm of sustainable heating and cooling technologies. CO2 heat pumps, utilizing carbon dioxide as a refrigerant, offer significant advantages in terms of environmental impact and energy efficiency compared to traditional systems. However, unlocking their full potential requires precise control and optimization of operational parameters. By leveraging advanced computational methodologies this project aims to enhance the operational strategies of CO2 heat pumps across a broader operating range for greener and more sustainable heating/cooling applications.
We are offering a PhD opportunity focused on applying machine learning methods to develop optimal operational strategies for trans-critical CO2 heat pumps. This project is based within the Department of Mechanical and Aerospace Engineering.
The student will have a great opportunity to collaborate with our industry partner isentra Ltd to have access to their substantial dataset of operational parameters from real heat pump for model validation and optimisation.