volume | PIER Journals

Abstract

Non-embedded uncertainty analysis methods are widely used in the field of electromagnetic compatibility (EMC). Their essence is to construct a surrogate model to simulate the actual electromagnetic simulation process and obtain the desired uncertainty simulation results through exhaustive sampling. However, when performing complex electromagnetic compatibility simulations, non-embedded uncertainty analysis methods face an inherent problem. This problem arises from the excessive number of deterministic simulations, which leads to computational inefficiency. In this paper, an active sampling strategy based on Bayesian optimization is proposed. By selecting the locations of deterministic simulation sampling points in a more reasonable manner, the overall number of sampling points required for the uncertainty simulation can be minimized, thereby improving the computational efficiency. Finally, the effectiveness of the sampling strategy proposed in this paper was verified using a typical parallel cable crosstalk example and a lightning electromagnetic pulse electromagnetic interference simulation example.

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Dr. Jinjun Bai

Dr. Jiasheng Wang

Dr. Xiangrui Ji

Dr. Yujia Song

Dr. Haichuan Cao