PhD Research Studentships

Machine learning model development for oil cooling optimisation for traction motors

Supervisor: Amin PAYKANI
Apply by:28 January 2026
Start in:September (Semester 1)

Description

As electric vehicles (EVs) continue to evolve, their traction motors are required to deliver ever-increasing power densities while maintaining safe operating temperatures. Efficient thermal management has become a critical enabler for motor reliability, performance, and lifespan. This PhD project will focus on developing machine learning-based models to optimise direct oil cooling systems for next-generation traction motors.

This project will explore a novel cooling architecture directly targeting the key heat sources. The research will involve:

  • Experimental characterisation of oil flow and thermal performance within custom-designed winding geometries.

  • High-fidelity CFD simulations to investigate the coupled thermal–fluid behaviour of the system.

  • Development of machine learning surrogate models trained on simulation and experimental data, capable of accurately predicting cooling performance across a wide design space.

The outcome will be a validated digital framework for the design of smaller, cooler, and more efficient traction motors, supporting the transition towards sustainable electric mobility.

A strong background in one or more of the following areas is desirable:

  • Computational Fluid Dynamics (CFD)

  • Machine Learning / AI modelling

  • Thermal–fluid systems or heat transfer

  • Programming (Python, MATLAB, or similar)

Funding

Funded by: China Scholarship Council
Candidate will need to secure a CSC scholarship.
Under the scheme, Queen Mary will provide scholarships to cover all tuition fees, whilst the CSC will provide living expenses and one return flight ticket to successful applicants.

Eligibility

  • The minimum requirement for this studentship opportunity is a good honours degree (minimum 2(i) honours or equivalent) or MSc/MRes in a relevant discipline.
  • If English is not your first language, you will require a valid English certificate equivalent to IELTS 6.5+ overall with a minimum score of minimum score of 6.0 in each of Writing, Listening, Reading and Speaking).
  • Candidates are expected to start in September (Semester 1).

Contact

For informal enquiries about this opportunity, please contact Amin PAYKANI.

Apply

Start an application for this studentship and for entry onto the PhD Mechanical Engineering full-time programme (Semester 1 / September start):

Apply Now »

Please be sure to quote the reference "SEMS-PHD-677" to associate your application with this studentship opportunity.

Related website:https://www.sems.qmul.ac.uk/staff/a.paykani
SEMS Research Centre:
Intelligent Transport
Keywords:Machine Learning, Aerospace Engineering, Automotive Engineering, Electrical Engineering, Electronic Engineering, Energy Technologies, Fluid Mechanics, Mechanical Engineering, Mathematical Modelling