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  Low Carbon Powertrain with Flywheel Energy Storage


   School of Engineering and Computer Science

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  Dr M Herfatmanesh, Dr L Li  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

The scientific excellence of this project is related to the development of an advanced powertrain with flywheel energy storage to improve the fuel economy and reduce the exhaust emissions. Flywheel offers an onboard energy recovery and storage system which is durable, efficient and environmentally friendly. This technology allows for the design of energy efficient vehicles without the need for batteries which often use toxic chemicals which cannot be recycled at the end of their life, posing serious damage to the environment. This technology can improve the fuel economy of light-duty passenger vehicles by up to 5% which would in turn reduce the harmful emissions in particular CO2 emission. This technology could make a substantial contribution to the UK government CO2 emission reduction target. In this study the aerodynamic performance of a flywheel energy storage at different operating conditions will be investigated using commercial CFD software to develop an optimised geometrical configuration to achieve maximum energy recovery and storage with minimal losses.

The aim of this research is to develop low carbon powertrain with flywheel energy storage. The aerodynamic loss of a flywheel is directly linked to the operating conditions and its geometrical configuration. This study will investigate the aerodynamic performance of a flywheel energy storage at different operating conditions. The initial findings are then used to develop an optimisation algorithm to identify optimum geometrical configuration and operating condition for application in the automotive industry, in particular light-duty vehicles

Application Web Page
Applicants must apply using the online form on the University Alliance website at https://unialliance.ac.uk/dta/cofund/how-to-apply/. Full details of the programme, eligibility details and a list of available research projects can be seen at https://unialliance.ac.uk/dta/cofund/


The final deadline for application is 12 April 2019.

Funding Notes

DTA3/COFUND participants will be employed for 36 months with a minimum salary of (approximately) £20,989 per annum. Tuition fees will waived for DTA3/COFUND participants who will also be able to access an annual DTA elective bursary to enable attendance at DTA training events and interact with colleagues across the Doctoral Training Alliance(s).

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 801604.