While developing new products, companies struggle with the fact that there are significant gaps between design tool predictions (even with virtual prototyping 3D). These gaps are typically addressed by including empirical ‘build factors’ in modelling tools. This requires prototyping for calibration of the models. Induced emf, iron loss, AC losses, end-winding length, equivalent contact thermal resistance and impregnation goodness are some of the properties which are difficult to predict. These unknowns expand dramatically development time, costs and risks.
Our vision is that electric machine design tools should optimally include manufacturing processes influence. WMG has a unique position of understanding how materials, manufacturing and design interact to affect electric machine performance. Our activities aim at suppressing the need of complete motor prototyping to identify design tool build factors.
Our current focus is the effect of manufacturing on e-steel and e-machine performance. With a portfolio of projects, we investigate electric steel properties and the impact of stress on local characteristics. We consider a wide range of manufacturing processes (cutting and assembly processes) and develop specific experiments to validate models from materials to samples with simple shapes, parts, sub-assemblies and electric machines. These activities are carried on in collaboration with steel processes research group, led by Professor Claire Davis.
We have also started activities to increase our understanding of the impregnation goodness build factor for a wide range of manufacturing processes.