Primary/2nd Supervisor: Eleni Kaplani
Primary/2nd Supervisor: Oscar Hui
2nd Supervisor: Chris Atkin
This project will support further development of a new and high-precision condition monitoring system for wind turbine drivetrain which is capable of detecting both electrical and mechanical faults in the drivetrain by processing only the available electrical signals from the generator terminals, leading to improving the overall reliability and availability of the drivetrain systems and hence reducing the cost of wind energy. Improved reliability and cost-effectiveness will inherently lead to wider adoption of wind power generation, especially offshore, which will boost the low-carbon economy, reduce CO2 emissions and increase energy security for the UK and globally.
The successful candidate will be based at the School of Engineering of the University of East Anglia. Depending on how eligibility criteria are met, Home/EU candidates may be entitled to full award (stipend and full fees) and international candidates may be entitled to a partial award (full or partial PhD tuition fees). The successful candidate is expected to be highly motivated, and to have a First or Upper Second-class degree in Electrical or Electronics. The successful candidate will also need to carry out an analytical study, computer simulation and Finite Element (FE) analysis, and experimental development and verifications during the project's 3-year time scale to achieve the project main aims and objectives.
The successful candidate is also expected to have the below skills and knowledge:
- Knowledge and/or experience in the subject
- Good knowledge of electrical machines and power electronics
- Experimental, modelling or analytical experience rated to Electrical machines and power electronics
- Experience of or a willingness to quickly learn about Finite Element (FE) analysis software and Matlab/Simulink