Alex graduated from the University of Brighton with a First Class Honours in Automotive Engineering and has recently completed an MSc in Automotive Engineering at Loughborough University. During this time his passion for the automotive industry has grown exponentially, with a deep interest into advancing current internal combustion engine feasibility.
As an undergraduate, Alex' final year project looked at the fluid dynamics of the human cochlea using CFD techniques. This was aimed at modelling processes inside the cochlea channel with relation to acoustic oscillations in comparison to pure mixing. This was an exploratory study for a larger scale collaboration between the Advanced Engineering centre and the Sensory Neuroscience Research Group.
In terms of potential areas in which to conduct his research project, Alex would love to amalgamate his passion of internal combustion engines with the more recently gained interest in fluid dynamics. Through his experience at AAPS, Alex hopes to broaden his knowledge in the automotive propulsion industry and gain a more complete understanding of how we can tackle the emissions crisis in the current climate.
The aim of the PhD project is to develop, validate and parametrise a fuel cell model virtually using given software in alignment with what AVL is currently using. Initially, a fuel cell stack model will be developed, building on what is available to AVL and in the literature. following this a Balance of Plant model (systems external to the stack) will be developed encompassing the main components in the system, again building on what is already currently available. Particular focus will be paid to the humidifier model as this has been identified as a component which requires further work from AVL. These models will run in real time so they can be used for hardware in the loop and virtual testbed applications.
To improve accuracy of the model in comparison to the hardware, the model will be validated against test data, iteratively improving the accuracy until a satisfactory small value has been achieved.
This then leads to the development of an automated parametrisation process using design of experiment methods, to evaluate individual parameters impacts on the system. This allows for increased efficiency and accessibility in the model as well as a reduction in costs when carrying out experimental testing further in the process.
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