This work introduces a novel data-driven modified nodal analysis (MNA) circuit solver. The solver is capable of handling circuit problems featuring elements for which solely measurement data are available. Rather than utilizing hard-coded phenomenological model representations, the data-driven MNA solver reformulates the circuit problem such that the solution is found by minimizing the distance between circuit states that fulfill Kirchhoff's laws, to states belonging to the measurement data. In this way, the previously inevitable demand for model representations is abolished, thus avoiding the introduction of related modeling errors and uncertainties. The proposed solver is applied to linear and nonlinear RC-circuits and to a half-wave rectifier.

翻译：本文提出了一种新颖的基于数据驱动的改进节点分析法(MNA)电路求解器。该求解器能够处理仅可获取测量数据的电路元件问题。与采用硬编码现象学模型表示的方法不同，该数据驱动型MNA求解器对电路问题进行重新建模，使得求解过程通过最小化满足基尔霍夫定律的电路状态与归属于测量数据的状态之间的距离来实现。通过这种方式，以往对模型表示的必然需求被消除，从而避免了引入相关的建模误差与不确定性。所提出的求解器被应用于线性和非线性RC电路以及半波整流器。