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Synchronous reluctance motors (SynRMs) have gained considerable attention in the field of electric vehicles as they reduce the need for permanent magnets in the rotor, resulting in less material and manufacturing costs. However, their lower average torque and torque ripple vibrations have been identified as key issues that require resolution. In this study, we present a SynRM design framework employing the cardinal basis functions (CBF)-based parametric level set method. The SynRms design problem is recast as a variational problem constrained by Maxwell's equations which describe the behavior of electric and magnetic fields in the SynRM. A continuum shape sensitivity analysis is carried out using the material derivative and adjoint method. A distance regularization energy function is employed to maintain the level set function as a signed distance function during the optimization. The parametric topology optimization problem is computationally solved using the Method of Moving Asymptotes (MMA). To demonstrate the effectiveness of our approach, we present a numerical example that compares the torque characteristics of the optimal design with those of a reference design. Preliminary results show that the optimized SynRM has a 30.30% increase in average torque, along with a slight increase in torque ripple, compared to the reference model. 

This paper proposes a density-based topology optimization scheme to design a heat sink for the application of a 3D integrated SIC-based 75 kVA Intelligent Power Stage (IPS). The heat sink design considers the heat conduction and convection effects with forced air cooling. The objective function is to minimize the thermal compliance of the whole structure. A volume constraint is imposed to reduce the overall volume of the designed heat sink to make it conformal to the underlying power devices. Some numerical techniques like filtering and projection schemes are employed to render a crisp design. Some 2D benchmarks examples are first provided to demonstrate the effectiveness of the proposed method. Then a 3D heat sink, especially designed for the 3D IPS, is topologically optimized. The classic tree-like structure is reproduced to reinforce the convection effect. Some comparisons with the intuitive baseline designs are made through numerical simulation. The optimized heat sinks are shown to provide a more efficient cooling performance for the 3D integrated power converter assembly. 

Generators are considered as the core application of electromagnetic machines, which require high-cost rare-earth-based permanent magnets. The development of generators is moving toward high efficiency and increased environmental friendliness. Minimizing the use of rare earth materials such as magnetic materials under the premise of machine performance emerges as a challenging task. Topology optimization has been promisingly applied to many application areas as a powerful generative design tool. It can identify the optimal distribution of magnetic material in the defined design space. This paper employs the level-set-based topology optimization method to design the permanent magnet for generators. The machine under study is a simplified 2D outer rotor direct-drive wind power generator. The dynamic and static models of this generator are studied, and the magnetostatic system is adopted to conduct the topology optimization. The optimization goals in this study mainly focused on two aspects, namely the maximization of the system magnetic energy and the generation of a target magnetic field in the region of the air gap. The continuum shape sensitivity analysis is derived by using the material time derivative, the Lagrange multiplier method, and the adjoint variable method. Two numerical examples are investigated, and the effectiveness of the proposed design framework is validated by comparing the performance of the original design against the optimized design.