This paper aims to show a complete optimization tool that can be used for the design of coaxial magnetic gears. In the first part, the paper deals with the semi-analytic modelling of these machines and also discusses how to reduce the computational efforts. In the second part, an optimization algorithm is adopted for finding the Pareto optimal geometries.
The machine is subdivided into a set of domains according to their physical and geometrical properties, and the potential distribution is found semi-analytically in them under some simplifying hypothesis. A loss estimation is performed for both ferromagnetic and permanent magnet regions. A stochastic differential evolution (DE) algorithm for multi-objective constrained problems is then applied.
It is shown that the presented design tool gives results in accordance to finite element method (FEM)-based analysis keeping the advantages of robustness and simplicity of the analytical methods. The DE-based strategy performs well on the magnetic gear optimization problem.
The proposed tool appears to be a good starting point when designing coaxial magnetic gears. The optimal Pareto points can be used as initial seeds of FEM-based optimizations, resulting in a cheaper computational method with respect to a full FEM optimization.
This paper takes inspiration from recent works on magnetic gear modelling and completes the design procedure with a suitable efficiency estimation. The paper also shows how to use mature optimization strategies to solve the constrained multi-objective magnetic gear design problem.
