For electromagnetic devices, there exist many uncertainty sources during design stage, performance simulation, components manufacturing and assembling. These uncertainties may deteriorate the practical operation performance of electrical machines from the designed one or result in violation of constraint conditions to a certain extent. To improve robust performance of a permanent magnet synchronous machine (PMSM), uncertainties should be taken into account in its whole life cycle. To manage uncertainties in the design stage of electrical machines, this paper makes some explorations of reliability-based optimal design. Firstly, the basic knowledge of reliability based algorithm is reviewed. Then the efficient adaptive sampling strategy and the surrogate model construction approach are introduced to reliability analysis. Based on these strategies, the new reliability analysis approach is named adaptive Kriging assisted weight index Monte Carlo simulation method. Finally, the new approach is applied to reliability-based optimal design of permanent magnet synchronous motor for cogging torque reduction.

中文翻译：

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自适应克里金辅助权重指数蒙特卡罗模拟方法管理永磁同步电机不确定度

对于电磁器件，在设计阶段、性能仿真、元件制造和装配过程中存在许多不确定源。这些不确定性可能会在一定程度上使电机的实际运行性能从设计上恶化或导致违反约束条件。为了提高永磁同步电机 (PMSM) 的稳健性能，应在其整个生命周期中考虑不确定性。为了管理电机设计阶段的不确定性，本文对基于可靠性的优化设计进行了一些探索。首先，回顾了基于可靠性算法的基础知识。然后将高效自适应抽样策略和代理模型构建方法引入可靠性分析中。基于这些策略，新的可靠性分析方法被命名为自适应克里金辅助权重指数蒙特卡罗模拟方法。最后，将新方法应用于基于可靠性的永磁同步电机优化设计，以降低齿槽转矩。