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Randomly Guided Mesh Adaptive Direct Search Algorithm Applied for Optimal Design of Electric Machines based on FEA

机译:基于FEA的电机最优设计随机引导网格自适应直接搜索算法

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摘要

Optimal design of electric machine based on FEM (Finite Element Method) calls for much longer computation time. In this paper, optimal design is implemented with randomly guided MADS (Mesh Adaptive Direct Search) and FEA (Finite Element Analysis) to compensate the excessive computation time. In addition, the proposed MADS coupled with FEA has been forwarded to Optimal design of Interior PM Synchronous Machine for Maximum Torque Per Ampere (MTPA). In particular, Randomly guided MADS has contributed to reducing the excessive computing time for the optimization process when compared with conventional MADS.
机译:基于FEM(有限元方法)的电机最优设计呼叫更长的计算时间。在本文中,用随机引导的MADS(网格自适应直接搜索)和FEA(有限元分析)来实现最佳设计以补偿过多的计算时间。此外,已拟议的疯子与FEA相结合,已转发为内部PM同步机的最佳设计,用于每个安培的最大扭矩(MTPA)。特别是,随机引导的MADS有助于减少与传统MADS相比的优化过程的过度计算时间。

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