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PhD Studentship: Adaptive Online Optimisation for Improved Powertrain Performance

Project Description

Application details:

Reference number: AAE-JK-1903
Start date: July 2019
Closing date: 29 April 2019


Primary supervisor: Dr James Knowles
Secondary supervisor: Dr Byron Mason

Loughborough University

Loughborough University is a top-ten rated university in England for research intensity (REF2014) and an outstanding 66% of the work of Loughborough’s academic staff who were eligible to be submitted to the REF was judged as ‘world-leading’ or ‘internationally excellent’, compared to a national average figure of 43%.

In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career.

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Project Detail

Current engine controllers are optimised for performance at steady-state operating points (constant speed/load); typical real-world driving involves transient dynamics as the engine moves between operating points. Adapting powertrain control parameters online will provide improvements in transient powertrain performance. The proposed project, which is funded by a University Research Program (URP) award by Ford, will demonstrate the opportunities of online self-adapting and learning control algorithms both in simulation and on hardware.

The successful applicant will work within the Powertrains research group in the Aeronautical and Automotive Engineering Department at Loughborough University and benefit from an extensive range of facilities, including engine test cells and high-performance computing facilities. The successful applicant will have the opportunity to spend up to 3 months working with experts within Ford and attend international conferences and workshops.

Entry requirements

Applicants should:
• Have a first-class honours or good upper second class degree in automotive/mechanical engineering or a related discipline (e.g. other engineering disciplines, physics, mathematics).
• Demonstrate knowledge or experience applicable to one or more of the following areas: optimisation; control; engine calibration; machine learning.
• Experience of programming in MATLAB/Simulink is desirable but not essential.
• Meet the minimum English Language requirements, details available on the website:

Contact details

Name: Dr James Knowles or Dr Byron Mason
Email address: or
Telephone number: +44 (0)1509 227223 or +44 (0)1509 227273

How to apply

All applications should be made online at Under programme name, select: ‘Automotive Engineering’

Please quote reference number: AAE-JK-1903

Funding Notes

The project is funded by Ford. The studentship provides a tax-free stipend of £18,000 per annum for three years plus tuition fees at the UK/EU rate. International students will need to fund the difference between the UK fees and international fees.

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