1 research outputs found

    A fast block structure preserving model order reduction for inverse inductance circuits

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    Most existing RCL βˆ’1 circuit reductions stamp inverse inductance L βˆ’1 elements by a second-order nodal analysis (NA). The NA formulation uses nodal voltage variables and describes inductance by nodal susceptance. This leads to a singular matrix stamping in general. We introduce a new circuit stamping for RCL βˆ’1 circuits using branch vector potentials. The new circuit stamping results in a first-order circuit matrix that is semi-positive definite and non-singular. We call this as vectorpotential based nodal analysis (VNA). It enables an accurate and passive reduction. In addition, to preserve the structure of state matrices such as sparsity and hierarchy, we represent the flat VNA matrix in a bordered-block diagonal (BBD) form. This enables us to build and simulate the macromodel efficiently. In experiments performed on several test cases, our method achieves up to 15X faster modeling building time, up to 33X faster simulation time, and as much as 67X smaller waveform error compared to SAPOR, the best existing second order RCL βˆ’1 reduction method
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