A number of our PhD students are self-funded, but funded studentships and Doctoral Training awards are also an option and details of those currently available are shown on this page.
Entry qualifications for funded PhD studentships vary and can be found in specific listings, for self funded students the requirement is a good degree(2:1 or higher) or relevant experience.
Search for current funded PhD studentships »
Centre for Doctoral Training in Digital Vehicle Engineering
We are recruiting four PhD students to complement our current team of five post-docs working on a £39million research project running in collaboration with Ford Motor Company. The objective of the programme is to develop new digital capabilities for use in the automotive product development process for electric vehicles. When applying candidates should list two or three projects from the following list in order of preference. We will run the projects that attract the best candidates.
Applicants should have, or expect to achieve, at least a good 2:1 Honours degree (or equivalent) in a relevant engineering discipline or a related subject at Bachelor or Masters level.
The studentship are co-funded with Ford and provides a tax-free stipend of £16,500 per annum for three and a half years plus tuition fees at the UK/EU rate. International (non-EU) students may apply however the total value of the studentship will cover the International Tuition Fee Only. In addition, the studentships are supported with funds for conference travel and consumables.
How to apply:
All applications should be made online at http://www.lboro.ac.uk/study/apply/research/. As academic contact name please include Professor Martin Passmore to ensure speedy processing of the application and please quote reference number: CDT-DVE
1. Thermal management of electric vehicles under rapid charging.
Dr Ashley Fly A.Fly@lboro.ac.uk
Fast charging of battery electric vehicles is an essential requirement to overcome range anxiety and increase widespread market adoption of emission free vehicles. Combining numerical modelling and experimental analysis, this project will investigate the limiting rate at which electric vehicles can be charged with an ideal thermal management system, explore what such a thermal management system would look like and how it would function.
2. Whole Vehicle ThermalManagement for Battery Electric Vehicles
Professor Gary Page firstname.lastname@example.org
This project will investigate a coupled high fidelity simulation of the complete electric vehicle thermal management system, including batteries, power electronics, motors, cabin and HVAC to allow modelling of bespoke thermal management strategies based on the customer and available external data. The project will involve multi physics CFD/heat transfer simulations, and in addition will investigate low order models for use in real time simulation.
3. Dry coupled ultrasonic guided wave characterisation of battery conditioning
Dr Dan O’Boy D.J.Oboy@lboro.ac.uk
This project will investigate the use of ultrasonic waves to identify individual cell conditioning in a battery pack without the need to cycle the battery. Guided waves with multiple time of arrivals corresponding to each cell will be used to minimise sensors and a validated model of the battery structure with the battery arrangement including cooling channels developed.
4. Data mining for accidentcausation applied to ADAS
Using the extensive Loughborough accident database critical driving scenarios that show similarities in accident causation will be identified using data mining techniques such as clustering and association rule mining to construct nominal driving use-cases essential for the interrogation of ADAS systems such as emergency braking. The use-cases will be implemented in simulation with vehicle models including ADAS sensors/algorithms and driver model to develop a framework for virtually assessing the operation of ADAS.
5. RDX tyre and suspension losses emulation in Vehicle in the Loop testing
The aim will be to develop or expand existing tyre/suspension loss models so that they can be used in real-time and implemented in a ViL hub-mounted dyno. This will improve the ViL to real-driving correlation and thus would be applicable to any RDX test. Emphasis will be placed on accurately replicating the real-driving tyre and suspension losses on different terrains during ViL testing.
6. Prediction of Traffic States with Stochastic Uncertainty
Dr Will Midgley W.J.Midgley@lboro.ac.uk
This project will employ recently developed uncertainty formulations to predict the energy usage of a vehicle due to the traffic state in real time. These predictions will include real-time predictions of current traffic, current intended route, past driver behaviour and the uncertainties in each of these (e.g. changing traffic conditions). These will be combined to develop an optimal control strategy to minimise the vehicle’s energy consumption.
7. EfficiencyImprovements for ADAS on Hybrid Vehicles
This project will look at the optimal control of hybrid powertrains under adaptive cruise control (ACC). Traditionally, the hybrid power split and the adaptive cruise control are considered separately, here a new optimal approach will be pursued, that projects the demand into the future based on ADAS sensors, navigation, and connectivity, and provides both the best vehicle speed trajectory and the best power split based on the projection. As a result, the ACC can predict the route ahead, and proactively select a suitable course of action (like lift and coast, followed by efficient regeneration) to get the best possible vehicle efficiency.
Centre for Doctoral Training in Future Propulsion and Power
Applications are invited for PhD study in the Centre for Doctoral Training in Future Propulsion and Power located within the Rolls-Royce University Technology Centre at Loughborough University.
The CDT in Future Propulsion and Power is a four year programme. Year one comprises of study at the University of Cambridge for a Master’s degree in Future Propulsion and Power. This is followed by a three-year industrially-focussed PhD project at Loughborough University. PhD topics will be developed during the first year but will be relevant to current and future technologies being developed by, for example, Rolls-Royce. See more details.
Centre for Doctoral Training in Embedded Intelligence
Applications are invited for PhD study in the Centre for Doctoral Training in Embedded Intelligence located within Loughborough University. We offer fully funded studentships to eligible candidates in the areas of autonomous products, functional materials, high performance connected systems, data-to-knowledge solutions, and engineering for industry, life and health. Successful candidates will follow our unique 4 year full-time programme which enables them to develop their research skills whilst working with industrial partners. Research training is complemented by non-technical subjects e.g. leadership, enterprise and social responsibility. See more details. Enquiries to Dr Donna Palmer, email@example.com
Speculative PhD enquiries
Funded research studentships become available throughout the year across a range of Aeronautical and Automotive topics, funded by UK research councils, industry and Loughborough University. We also welcome enquiries from individuals who have their own funding or would be interested in a part funded PhD opportunity. If you do not have funding, you may still apply, however Institutional funding is not guaranteed. You can view more information about the research centres and groups within the department using the links below.
- Rolls Royce University Technology Centre (UTC)
- Caterpillar Innovation and research centre (IRC)
- National Centre for Combustion and Aerothermal Technology (NCCAT)
- Vehicle Aerodynamics
- Intelligent Mobility and Autonomous Systems
- Hybrid Vehicles and Advanced Propulsion
- Risk and Reliability
Our academic staff are very pleased to help prospective students develop their research proposals as part of the application process. We are also very happy for prospective research students to visit the Department to see the facilities and to meet academic staff and research students.
For some ideas as to the types of projects we are currently interested in running please see our list of Indicative projects
General Enquiries relating to applications, please contact:
Miss June Lennie
Tel: +44 (0)1509 223331