Supervisory Team: Dr Anil K Madhusudhanan
Project description
Significant reduction of carbon emissions is needed to mitigate the adverse effects of climate change. In 2019, the UK government passed a legislation that requires the UK to bring all carbon emissions to net zero by 2050. According the World Health Organisation, carbon emissions is also a major source of air pollution, which causes an estimated seven million death every year.
Widespread use of electric vehicles can help to reduce carbon emissions. However, there are two major issues: (1) range anxiety and (2) renewable electricity. The range of an electric vehicle is the distance it can travel from being fully charged before needing a recharge. Current electric vehicles have limited range due to the significantly lower energy density of current battery technologies compared to petrol and diesel. Another problem is availability of renewable electricity. In the first quarter of 2021, more than 50% of electricity generation in the UK was not from renewable sources. In the later quarters of 2021, the figure was worsened by the 2021 energy crisis. Although the production of renewable electricity has been on the rise, given the demand will significantly increase with increasing number of electric vehicles, meeting future demand will be a challenge. Because of these issues, improving energy efficiency of electric vehicles is an important research topic for our society.
Controlling an electric vehicle, considering the upcoming traffic signal and traffic ahead, can reduce its energy consumption. Such controllers were proposed in recent research projects, including the following journal article:
https://doi.org/10.1016/j.ejcon.2018.12.006
However, the previous projects did not consider the electric power train model and effect of queues, and lacked experimental analysis. In this project, the PhD student will address these issues by (1) designing and developing a control system considering the upcoming traffic signal, electric power train model and the traffic between the vehicle and upcoming traffic signal, and (2) experimentally testing the system using the instrumented test vehicle, available at the university’s Boldrewood Innovation Campus.
We are looking for a motivated student with a strong background in control systems, electrical engineering or mechanical engineering. This is an exciting interdisciplinary research project which will give you experience with design, testing and analysis of an autonomous driving module. As a PhD student, you will get opportunities to present your work at international conferences abroad. The knowledge and skills you learn during this project will be applicable to systems from different engineering fields such as electrical, mechanical, aerospace and chemical, and will be valuable to pursuing career paths in academia as well as industry.
Entry Requirements
A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent).
Closing date: 28 February 2022.
Funding: Tuition Fees and a stipend of £15,609 tax-free per annum for up to 3.5 years are available.
How To Apply
Applications should be made online. Select programme type (Research), 2022/23, Faculty of Physical Sciences and Engineering, next page select “PhD Engineering & Environment (Full time)”. In Section 2 of the application form you should insert the name of the supervisor Anil K Madhusudhanan
Applications should include:
Motivation Letter
Curriculum Vitae
Two reference letters
Degree Transcripts to date
Apply online: https://www.southampton.ac.uk/courses/how-to-apply/postgraduate-applications.page
For further information please contact: [Email Address Removed]
Continue with Facebook
