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Black-Box Modeling of the Maximum Currents Induced in Harnesses During Automotive Radiated Immunity Tests

机译:在汽车辐射免疫检测期间利用线束引起的最大电流的黑匣子建模

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This letter presents a black-box modeling approach for the prediction of the spectrum of the maximum currents induced on a generic linear load in an automotive radiated immunity test. The proposed approach relies on a parametric Thevenin-based circuit equivalent built from a limited set of measured or simulated data. The frequency-domain behavior of the equivalent voltage source is provided via a metamodel by combining the support vector machine (SVM) regression with a regularized Fourier kernel with a simple adaptive algorithm. The latter allows defining the minimum number of training samples needed to accurately predict the maximum values of the currents induced on a generic linear load for different azimuth directions of the excitation field. The accuracy and the strength of the proposed approach are demonstrated for an example, by comparing the model predictions with the results of a parametric full-wave electromagnetic simulation.
机译:这封信显示了一种黑匣子建模方法,用于预测汽车辐射免疫检测中通用线性负载上的最大电流的频谱。所提出的方法依赖于从有限的测量或模拟数据集内建立的基于参数的基于Vircuinin的电路。通过使用简单的自适应算法将支持向量机(SVM)回归组合通过与正则化的傅里叶内核组合来通过元模型提供等效电压源的频域行为。后者允许定义精确地预测所需的训练样本数,以预测激励场的不同方位方向上的通用线性负载所引起的电流的最大值。通过将模型预测与参数全波电磁模拟结果进行比较,对示例进行了准确性和强度。

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