PhD Studentship in Active Wake Aerodynamics Using Machine Learning
|Published||December 16, 2022|
|Location||London, United Kingdom|
Applications are invited for a research studentship in the field of aerodynamics, leading to the award of a PhD degree. The post is supported by a bursary and fees (at the UK student rate) provided by the EPSRC through an iCASE studentship with Jaguar Land Rover. Candidates must demonstrate relevant connection with the UK, usually established by residence, as is standard for EPSRC funding.
Aerodynamic drag is the dominant source of driving resistance above 70km/h. For SUVs, over one-third of the total drag is caused by the wake behind the vehicle. The energy expended in overcoming this is wasted; it cannot be recovered by means such as regenerative braking. Reductions in aerodynamic drag therefore translate directly to increasing the range of battery electric vehicles.
Aerodynamic drag reductions can be achieved by changes to the vehicle design, but this can compromise the vehicle aesthetics. One way to overcome this is by using deployable aerodynamic devices such as spoilers, diffusers or strakes. Active aerodynamics would be an ambitious attempt to improve the effectiveness of deployable devices for rear wake control with Machine Learning (ML) algorithms. These would choose the deployment position or angle for optimum aerodynamic performance in response to sensing of vehicle driving conditions such as speed, pitch, and yaw angle.
The project will be simulation-based, performing simulations of the flow around a simplified benchmark vehicle, most likely the AeroSUV geometry. These will use the OpenFOAM CFD package. Geometry modifications will be implemented such as a diffuser and spoiler with variable angles. Machine Learning (ML) algorithms will be trained, employing methods suited to relatively sparse/small training data sets, such as reinforcement algorithms with model-free methods.
You will be an enthusiastic and self-motivated person who meets the academic requirements for enrolment for the PhD degree at Imperial College London. You will have a 1st class honours degree in mechanical engineering or related subject and demonstrate excellent project-work and communication skills. You will be interested in aerodynamics and computational fluid dynamics and in learning how to use machine learning algorithms. You will join a supportive and inclusive research group and benefit from co-supervision with the Jaguar Land Rover partner.
To find out more about research at Imperial College London in this area, go to:
For information on how to apply, go to:
For further details of the post contact Prof Aimee Morgans, email@example.com. Interested applicants should send an up-to-date curriculum vitae to Prof Morgans. Suitable candidates will be required to complete an electronic application form at Imperial College London in order for their qualifications to be addressed by College Registry.
Closing date: until post filled