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Towards Automated Extraction of EMC-Aware Trajectory-Based Macromodels for Analog Circuits

机译:致力于自动提取基于EMC的基于轨迹的模拟电路宏模型

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摘要

In this paper a new methodology is proposed forautomated generation of EMC-aware behavioral models. Tightening EMC regulations require elaborate testing and simulation of EMC susceptibility of analog circuits during the design stage. A classification strategy detects EMC-sensitive devices which allows us to incorporate a more elaborate device model when accuracy is needed due to rectification effects. In addition, trajectory-based models are used for efficient modeling of nonlinear dynamical systems. Trajectory methods sample the state space trajectory of a circuit while exciting the circuit with a representative training input. The macromodel is generated by reduction and interpolation of linearizations among the sampled trajectory points, in which the validity of the model is defined. Without relevant loss of accuracy, the simulation time of larger systems for EMC can be reduced with an order of magnitude. The method is verified on a single-stage opamp with rectifying bias current mirror, a circuit exhibiting EMC distortion.
机译:本文提出了一种新的方法,用于自动生成对EMC敏感的行为模型。严格的EMC法规要求在设计阶段对模拟电路的EMC敏感性进行详尽的测试和仿真。分类策略检测对EMC敏感的设备,这使我们可以在由于整流效应而需要精度时合并更精细的设备模型。另外,基于轨迹的模型用于非线性动力学系统的有效建模。轨迹方法对电路的状态空间轨迹进行采样,同时用有代表性的训练输入来激励电路。通过对采样轨迹点之间的线性化进行缩减和内插来生成宏模型,其中定义了模型的有效性。在不损失准确性的情况下,可以将大型系统用于EMC的仿真时间减少一个数量级。该方法在具有整流偏置电流镜的单级运算放大器上得到验证,该电路表现出EMC失真。

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