In the context of time-domain simulation of integrated circuits, one often encounters large systems of coupled differential-algebraic equations. Simulation costs of these systems can become prohibitively large as the number of components keeps increasing. In an effort to reduce these simulation costs a twofold approach is presented in this paper. We combine maximum entropy snapshot sampling method and a nonlinear model order reduction technique, with multirate time integration. The obtained model order reduction basis is applied using the Gauß-Newton method with approximated tensors reduction. This reduction framework is then integrated using a coupled-slowest-first multirate integration scheme. The convergence of this combined method is verified numerically. Lastly it is shown that the new method results in a reduction of the computational effort without significant loss of accuracy.

在集成电路的时域仿真环境中，人们经常会遇到耦合微分代数方程的大型系统。随着组件数量的不断增加，这些系统的仿真成本可能会变得非常高。为了降低这些模拟成本，本文提出了一种双重方法。我们将最大熵快照采样方法和非线性模型降阶技术与多速率时间积分相结合。使用具有近似张量约简的 Gauß-Newton 方法应用获得的模型阶数约简基础。然后使用耦合最慢优先多速率集成方案来集成此缩减框架。这种组合方法的收敛性得到了数值验证。