Grant: Alliance Grants

In this research project, we aim to develop next-generation electrical drive system (EDS) simulation tools that are more accurate, more user-friendly, less time-consuming, and have more powerful optimizing capabilities. A smart library of electrical machines will be established, which will artfully categorize all the major machine topologies into several general forms that allow flexible adjustment of the winding connections and the geometric parameters of the stator, the rotor, and the permanent magnets (PM). This library will include templates of radial-flux electrical machines, axial-flux electrical machines, magnetic gears, and linear electrical machines, which will provide a straightforward solution for the geometric modeling of various electrical machines and make it easier for users to develop electrical machine models with complex structures. Based on this library, the templates in the existing radial-flux motor wizard of EMWorks will be greatly enriched, and new axial-flux motor wizard, magnetic gear wizard and linear motor wizard will be developed. These newly developed software packages will significantly increase the advantages of EMWorks over its competitors that usually only have templates of traditional radial-flux motors. Another important part of this research project is to establish fast and accurate analytical models, with a full consideration of the nonlinear characteristics caused by saturation. These models will be used to simulate torque, power, efficiency, electromagnetic force, and thermal distribution of potential electrical machines. Since the existing electromagnetic solvers are mainly based on time-consuming finite element method (FEM), fast analytical methods will be gamechangers in the field of electromagnetic simulation. New multi-physics and system-level optimization tools will also be developed through the use of machine learning (ML) technologies to improve the optimization efficiency and accuracy.