PhD Opportunity Title Driving forward the future of magnetic materials for electric vehicles

The demand for high performance permanent magnets for clean energy applications such as the power systems in automotive applications, have increased enormously in recent years. These technologies require conversion of electricity to motion via a motor, as in hybrid or all-electric vehicles. These are usually sintered from powders to form solids that contain crystal grains ranging from sub-micrometre to low-micrometre in size. Materials based on the Nd-Fe-B class are usually used (90% permanent magnet market share) as these have the highest magnetic energy density (512 kJ.m-3). These materials typically contain a significant proportion of ‘rare earth’ elements. While these do improve the performance of the magnets, are expensive and have fluctuated in price significantly over recent years.

In many applications the magnetic materials are required to operate at elevated temperature. Though NdFeB shows excellent properties at room temperature, its Curie temperature is much lower than the alternative SmCo, and as such NdFeB based magnets’ anisotropy, and thus efficiency, falls quickly. The addition of some rare earth elements increase the operating range of the magnet, but typically any applications above 175°C would require a SmCo based magnet.

This project combines modelling with some experimental work. Primarily it will build up our in-house state-of-the-art microstructural generation software allowing fast generation of randomised, but controllable, realistic three-dimensional granular type structures. It provides us the ability to create microstructural features such as irregular shaped grains each with a core-shell structure as well as secondary phases, roughness, and porosity. This allows replication of realistic morphologies to be solved for their magnetic behaviour finite element modelling (FEM) computation of the magnetisation dynamics.

The focus of this work will look mainly at simulating the response from different magnetic materials and include effects such as diffusion, grain boundaries and grain shape. It will combine the predicted results with experimental verification of key designs and finally, look towards implementing larger, coarser scale simulations, using the results gather from the smaller, detailed ones, to identify at how these local properties effect in-situ performance.

The PhD is strongly aligned to other PhD students in our group, also supported by VW, who will be providing experimental support. They will be able to generate key input data for the models as well as test any predictions and design criteria the simulations generate results of which can be fed back into the models.