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• W4213247785 abstract "This article proposes a robust optimization method for hybrid permanent magnet (HPM) machines, aiming to eliminate the influence of permanent magnets (PMs) asymmetric uncertainties. Exemplified by a 12-slots/10-poles (12s10p) HPM machine, the optimization method is specifically clarified. First, uncertainties of two types of PMs are comprehensively analyzed and the worst combination of these uncertainties are estimated. Then, the design of experiments (DOEs) technique is utilized to take samples, and the corresponding performance of samples with and without consideration about uncertainties are simulated by finite element analysis (FEA), respectively. After that, a dual-level kriging surrogate model is constructed. And the difference of the two levels, as a quantitative index of robustness, is added as an additional optimization objective. Finally, a multi-objective optimization algorithm non-dominated sorting genetic algorithm (NSGA-II) is carried out. The optimization results indicate that the proposed method can effectively reduce the additional torque tipple brought from asymmetric uncertainties of PMs. In addition, a prototype is manufactured and tested to further verify the method." @default.
• W4213247785 created "2022-02-24" @default.
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• W4213247785 date "2022-08-01" @default.
• W4213247785 modified "2023-10-17" @default.
• W4213247785 title "A Robust Optimization Design Approach for Hybrid PM Machine Considering Asymmetric Uncertainties of PMs" @default.
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• W4213247785 doi "https://doi.org/10.1109/tmag.2022.3152500" @default.
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