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 Thévenin-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.

中文翻译：

---

汽车辐射抗扰度测试期间线束中感应的最大电流的黑盒建模

这封信提出了一种黑盒建模方法，用于预测汽车辐射抗扰度测试中一般线性负载上感应的最大电流的频谱。所提出的方法依赖于从一组有限的测量或模拟数据构建的基于参数戴维南的等效电路。通过将支持向量机 (SVM) 回归与正则化傅立叶核与简单的自适应算法相结合，通过元模型提供等效电压源的频域行为。后者允许定义针对激励场的不同方位角准确预测在通用线性负载上感应的电流的最大值所需的训练样本的最小数量。所提出的方法的准确性和强度通过一个例子来证明，