volume | PIER Journals

Abstract

In recent years, uncertainty analysis is a hot topic in the field of electromagnetic compatibility simulation. The actual electromagnetic environment is simulated by considering the randomness of the model input parameters. However, there are currently two key issues that have not been resolved. One is the curse of dimensionality problem that occurs when there are many random variables. The other is how to establish a random input model with generality and portability. In order to address these issues, this paper proposes a new random input modeling method called random variable black box model. When applying to the Stochastic Collocation Method with dimensionality reduction sparse grid strategy, the applicability of this uncertainty analysis method can be extended to any probability density function, then enabling efficient electromagnetic compatibility simulation uncertainty analysis of high-dimensional random variable models and fundamentally solving the curse of dimensionality problem. Finally, this paper implements a joint simulation technology of the MATLAB software and the COMSOL software to verify the strong portability of the random variable black box model, ensuring that advanced uncertainty analysis methods can be smoothly introduced into commercial electromagnetic simulation software and expanding the application scope of uncertainty analysis.

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Dr. Jinjun Bai

Dr. Bing Hu

Dr. Shenghang Huo

Dr. Ming Li