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Multi-objective optimal design of a five-phase fault-tolerant axial flux PM motor

机译:五相容错轴流永磁电动机的多目标优化设计

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摘要

Electric motors used for traction purposes in electric vehicles (EVs) must meet several requirements, including high efficiency, high power density and faulttolerance. Among them, permanent magnet synchronous motors (PMSMs) highlight. Especially, five-phase axial flux permanent magnet (AFPM) synchronous motors are particularly suitable for in-wheel applications with enhanced fault-tolerant capabilities. This paper is devoted to optimally design an AFPM for in-wheel applications. The main geometric, electric and mechanical parameters of the designed AFPM are calculated by applying an iterative method based on a set of analytical equations, which is assisted by means of a reduced number of three-dimensional finite element method (3D-FEM) simulations to limit the computational burden. To optimally design the AFPM, a constrained multi-objective optimization process based on a genetic algorithm is applied, in which two objective functions are considered, i.e. the power density and the efficiency. Several fault-tolerance constraints are settled during the optimization process to ensure enhanced fault-tolerance in the resulting motor design. The accuracy of the best solution attained is validated by means of 3D-FEM simulations.
机译:电动汽车(EV)中用于牵引目的的电动机必须满足几个要求,包括高效率,高功率密度和容错能力。其中,永磁同步电动机(PMSM)是亮点。尤其是,五相轴向磁通永磁体(AFPM)同步电动机特别适合具有增强的容错能力的轮内应用。本文致力于针对轮毂应用优化设计AFPM。通过使用基于一组解析方程的迭代方法来计算所设计的AFPM的主要几何,电气和机械参数,并借助减少数量的三维有限元方法(3D-FEM)模拟来辅助限制了计算负担。为了优化设计AFPM,应用了基于遗传算法的约束多目标优化过程,其中考虑了两个目标函数,即功率密度和效率。在优化过程中会确定几个容错约束,以确保在最终的电机设计中提高容错能力。通过3D-FEM仿真验证了所获得的最佳解决方案的准确性。

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