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This brief presents a frequency-domain approach for the steady-state analysis of pulsewidth-modulated converters and switched circuits with nonideal switching behavior. The proposed strategy generalizes recent methodologies based on the Fourier expansion of the steady-state responses of a periodically switching circuit and on the simulation of an augmented linear-time-invariant system. This system is now also given an interpretation in terms of an equivalent circuit, which is simulated at a single frequency point to solve for all the harmonics. The method offers a modular topological approach that is combined with standard tools for circuit analysis and enables the simulation of networks with an arbitrary number of switches and driving mechanisms. Single, multiple, and possibly nonideal commutation events within the switching period are handled in the same framework, without additional complexity. The technique allows for the full frequency-domain characterization of both the functional and the noisy behavior of the circuit responses. The feasibility and strength are demonstrated via comparisons with simulations and measurements on two application examples, i.e., a full-bridge single-phase inverter and a dc–dc boost converter. [ABSTRACT FROM AUTHOR]

This paper delivers a considerable improvement in the framework of the statistical simulation of highly nonlinear devices via polynomial chaos-based circuit equivalents. Specifically, a far more efficient and “black-box” approach is proposed that reduces the model complexity for nonlinear components. Based on recent literature, the “stochastic testing” method is used in place of a Galerkin approach to find the pertinent circuit equivalents. The technique is demonstrated via the statistical analysis of a low-noise power amplifier and its features in terms of accuracy and efficiency are highlighted. [ABSTRACT FROM AUTHOR]

This letter addresses the simulation of the steady-state response of switching power converters. The proposed approach is based on the interpretation of the voltage and current variables of a periodically switched linear circuit in terms of a series expansion and on the generation of augmented time-invariant constitutive relations of the circuit elements. The circuit solution is obtained from an augmented time-invariant nodal equation generated from topological information and circuit inspection only. The feasibility and strength of the approach are demonstrated on a dc-dc boost converter. [ABSTRACT FROM AUTHOR]

This letter addresses the stochastic analysis of nonlinear switching power converters via an augmented circuit equivalent and a single deterministic SPICE simulation. The proposed approach is based on the expansion of the constitutive relations of the circuit elements in terms of orthonormal polynomials within the well-established framework of polynomial chaos. The feasibility and strength of the method are demonstrated on a dc-dc boost converter described by either detailed nonlinear components or via its averaged linear circuit. Excellent modeling accuracy as well as remarkable speed-ups compared to traditional sampling-based approaches are achieved. [ABSTRACT FROM AUTHOR]

This paper presents an alternative modeling strategy for the stochastic analysis of high-speed interconnects. The proposed approach takes advantage of the polynomial chaos framework and a fully SPICE-compatible formulation to avoid repeated circuit simulations, thereby alleviating the computational burden associated with traditional sampling-based methods such as Monte Carlo. Nonetheless, the technique offers very good accuracy and the opportunity to easily simulate complex interconnect topologies which include lossy and dispersive transmission lines, thus overcoming the limitations of previous formulations. Application examples involving the stochastic analysis of on-chip and on-board interconnects validate the methodology proposed. [ABSTRACT FROM AUTHOR]

This paper addresses the generation of an enhanced stochastic model of a carbon nanotube interconnect including the effects of process variation. The proposed approach is based on the expansion of the constitutive relations of state-of-the-art deterministic models of nanointerconnects with uncertain parameters in terms of orthogonal polynomials. The method offers comparable accuracy and improved efficiency with respect to conventional methods like Monte Carlo in predicting the statistical behavior of the electrical performance of next-generation data links. An application example involving both the frequency- and time-domain analysis of a realistic nanointerconnect concludes this paper. [ABSTRACT FROM AUTHOR]

This paper focuses on the derivation of an enhanced transmission-line model allowing the stochastic analysis of a realistic multiconductor interconnect. The proposed model, which is based on the expansion of the well-known telegraph equations in terms of orthogonal polynomials, includes the variability of geometrical or material properties of the interconnect due to uncertainties like fabrication process or temperature. A real application example involving the frequency-domain analysis of a coupled microstrip and the computation of the parameters variability effects on the transmission-line response concludes this paper. [ABSTRACT FROM PUBLISHER]

This paper provides an effective solution for the simulation of cables and interconnects with the inclusion of the effects of parameter uncertainties. The problem formulation is based on the telegraphers equations with stochastic coefficients, whose solution requires an expansion of the unknown parameters in terms of orthogonal polynomials of random variables. The proposed method offers accuracy and improved efficiency in computing the parameter variability effects on system responses with respect to the conventional Monte Carlo approach. The approach is validated against results available in the literature, and applied to the stochastic analysis of a commercial multiconductor flat cable. [ABSTRACT FROM AUTHOR]

This letter proposes a general and effective decoupled technique for the stochastic simulation of nonlinear circuits via polynomial chaos. According to the standard framework, stochastic circuit waveforms are still expressed as expansions of orthonormal polynomials. However, by using a point-matching approach instead of the traditional stochastic Galerkin method, a transformation is introduced that renders the polynomial chaos coefficients decoupled and therefore obtainable via repeated non-intrusive simulations and an inverse linear transformation. As discussed throughout the letter, the proposed technique overcomes several limitations of state-of-the-art methods. In particular, the scalability is hugely improved and tens of random parameters can be simultaneously treated within the polynomial chaos framework. Validating application examples are provided that concern the statistical analysis of microwave amplifiers with up to 25 random parameters. [ABSTRACT FROM PUBLISHER]