Machine learning and cloud computing in the dynamic optimisation of energy efficient autonomous vehicles PhD

Department(s):
Aeronautical and Automotive Engineering
Entry requirements:
2:1+
Full-time:
3 years
Part-time:
not available
Reference number:
AAE-DZ-1804
Start date:
July 2018
Is funding available?
Yes
UK/EU fees:
N/A
International fees:
TBC
Location:
Loughborough
Application deadline:
10 March 2018

Achievements

3rd

nationally for research quality

REF 2014

New

£17m STEMLab facility

8th

in the UK for Aeronautical and Automotive Engineering

The Complete University Guide 2018

Overview

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. 

Project detail

The Department of Aeronautical and Automotive Engineering of Loughborough University is seeking a highly motivated graduate to undertake an exciting 3-year PhD project entitled “Machine learning and cloud computing in the dynamic optimisation of energy efficient autonomous vehicles”. 

There is an ongoing revolution in developing autonomous vehicles to greatly improve safety and traffic efficiency. This general trend is greatly impacted by advances in powertrains for improved vehicle fuel economy. The intersection of autonomy and green powertrain will shape the future of the automotive industry. Most leading automotive companies have announced strategic partnerships with IT companies to explore this area including Ford and Google; Toyota and Microsoft; General Motors and Lyft; and Volvo and Uber.

This PhD project aims to develop innovative methods on sensing, modelling, control, optimisation and computing for energy efficient autonomous vehicles. The project falls into a rapidly growing area and focuses on a class of far-reaching scientific and technical problems. Autonomous vehicles use perception of the environment to make decisions and realise unmanned driving. Low carbon vehicles strongly rely on the dynamic optimisation of powertrain behaviour. We aim to update the powertrain model with information about the driving environment, thus breaking down a wall that currently exists between research in autonomous driving and powertrain control.

In this project you will develop machine-learning-based modelling and dynamic optimisation methods. To tackle computational pressures, a cloud-computing-based framework is to be designed.

Through this project you will join one of the largest University-based automotive research groups in the world. You will have access to world-class vehicles and powertrains research facilities. You will also receive supports from experienced researchers and practitioners in the field.

Supervisors

Primary supervisor: Dr Dezong Zhao

Secondary supervisor: Dr Byron Mason

Find out more

For further project details email Dr Dezong Zhao or register your interest and ask us a question.

Entry Requirements

Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in Control Engineering, Electrical & Electronic Engineering, Computer Science, Mechatronics, Mechanical Engineering, Vehicle Engineering or a related subject.

A relevant Master’s degree and/or experience in one or more of the following will be an advantage: Artificial Intelligence, Programming skills (e.g. Matlab, C, C++ and Python).

Applicants must meet the minimum English Language requirements, details available on the website.

Fees and funding

UK/EU:
N/A
International:
TBC

Tuition fees cover the cost of your teaching, assessment and operating University facilities such as the library, IT equipment and other support services. University fees and charges can be paid in advance and there are several methods of payment, including online payments and payment by instalment. Special arrangements are made for payments by part-time students.

The 3-year studentship provides a tax-free stipend of £14,553 per annum plus tuition fees at the UK/EU rate. International students may apply however the studentship will cover the international tuition fee only.

How to apply

All applications should be made online.  Under programme name, select ‘Aeronautical and Automotive Engineering’

Please quote reference number: AAE-DZ-1804

Application details

Reference number: AAE-DZ-1804
Application deadline: 10 March 2018
Start date: July 2018

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