Rob Dwyer-Joyce




Professor Rob Dwyer-Joyce is director of the Leonardo Centre for Tribology at the University of Sheffield. He has a first degree in Mechanical Engineering and did his PhD in Tribology at Imperial college. He pioneered the use of ultrasound for tribological machine elements, to measure of oil film, contact load, and viscosity. He has published over 150 papers in international journals. He was director of the Centre for Doctoral Training in Integrated Tribology, an EPRSC Advanced Career Fellow, Fellow of the Royal Academy of Engineering, and past editor of the IMechE Journal of Tribology.

Abstract:
Wind to Wheels – efficiency of the all-electric powertrain

Prof Rob Dwyer-Joyce
Leonardo Centre for Tribology
University of Sheffield

There is an imperative to combust less fossil fuel for energy and transportation requirements, both to combat climate change and reduce pollution. The world is seeing an unprecedented change in both our energy and transportation sectors.

Wind to wheels expresses how the kinetic energy of the wind is captured, converted to electric energy, transported, stored, and converted back to the kinetic energy of an electric vehicle. There is a ‘power-train’ of mechanical, electrical, and electro-mechanical components to achieve this. This starts with the turbine blades, main bearing, gearbox, generator, and power converters. The efficiency of these components varies with rotational speed and hence wind loading. The electricity distribution system consists of a series of cables at various ratings and transformers; energy losses depend on the grid current loading. An electric vehicle is charged, energy is stored in a battery, and then transferred to the wheels through a generator, electric motor, and gearbox. Efficiency of these components varies with charging rate and vehicle speed.

This talk breaks the full power-train into sub-components and identifies from published data or models the energy efficiency of each stage. As an example, a 3MW turbine in the London Array wind farm is used to charge a Tesla Model 3 EV at home in central London. The resulting data is assembled into a Sankey diagram to identify power flow at each stage. We then use a Simulink model of the powertrain to explore different transmission scenarios. Whilst there are many simplifications and assumptions it is interesting to display the data graphically in this way. It becomes possible to compare the magnitude of mechanical losses with electrical losses, and to see how mature technologies compare with newer ones.


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