Asymptotic Waveform Evaluation (AWE) [1, 2] is an efficient and general technique for simulating linear(ized) circuits. This paper discusses strategies for macromodeling nonlinear circuits with AWE. One approach, multi-region AWE macromodels, represents an extension of piecewise linear models, with the addition of internal states. Each region represents an AWE approximation to a linearization (at some bias point) of the nonlinear circuit of interest. In addition a technique is presented for initializing the internal states when the model transitions from one linearization to another during a transient simulation. The second approach is to treat nonlinearity as a second order effect that is superimposed on a linear solution as a post-processing step. A relaxation algorithm that exploits the reuseable AWE solution is employed to modify the linear solution so that it accounts for the macromodel nonlinearity.
KeywordsReduce Order Model Linear Solution Nonlinear Element Dominant Pole Bias Point
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