Method for steady-state simulation of strongly nonlinear circuits in the time domain

Author(s):  
A. Brambilla ◽  
D. D'Amore
2021 ◽  
Vol 7 (3) ◽  
pp. 12-16
Author(s):  
A. Brambilla ◽  
◽  
G. Storti-Gajani ◽  

Time domain methods, while well suited to compute the steady state behaviour of strongly nonlinear non-autonomous electrical circuits, are inefficient if the periods of the forcing signals have a very large minimum common multiple. The solution of the periodicity constraint requires to integrate the differential algebraic equation (DAE) describing the circuit along the T period and this can be a CPU time consuming task. Literature reports several attempts to extend the SH method to simulate circuits driven by multi-tone signals [2] [4] [5]. However, as far as we know, all they suffer of limitations and it is our opinion that an efficient and general extension has not been found, yet. In this paper we present a possible extension that takes its origin from the previous approach reported in [2]. In this paper a modification of the conventional shooting method is presented that tries to overcome the above drawback.


2003 ◽  
Vol 13 (11) ◽  
pp. 3395-3407 ◽  
Author(s):  
F. A. SAVACI ◽  
M. E. YALÇIN ◽  
C. GÜZELIŞ

In this paper, nonlinearly coupled identical Chua's circuits, when driven by sinusoidal signal have been analyzed in the time-domain by using the steady-state analysis techniques of piecewise-linear dynamic systems. With such techniques, it has become possible to obtain analytical expressions for the transfer functions in terms of the circuit parameters. The proposed system under consideration has also been studied by analog simulations of the overall system on a hardware realization using off-the-shelf components as well as by a time-domain analysis of the synchronization error.


1996 ◽  
Vol 06 (01) ◽  
pp. 43-57 ◽  
Author(s):  
NICOLA GUGLIELMI

In this paper numerical problems arising from steady state analysis of nonlinear circuits with quasiperiodic excitation are discussed. The approach we consider is based on the piecewise harmonic balance techniques8,9 (HB), a methodology which has its theoretical foundations in Galerkin's procedure (see the paper by Urabe12). The original problem, which can be expressed in the form of a system of integro-differential equations in the time domain, is changed into a nonlinear algebraic system through a natural projection technique. Thus, one of the main issues we have investigated consists in the numerical solution of the specific nonlinear algebraic problem.


2015 ◽  
Vol 35 (1Sup) ◽  
pp. 58-64
Author(s):  
Yulieth Jimenez ◽  
Cesar Duarte ◽  
Johann Petit ◽  
Jan Meyer ◽  
Peter Schegner ◽  
...  

<p class="Abstractandkeywordscontent"><span lang="ES-CO"><span><span><span style="font-family: OptimaLTStd-DemiBold; font-size: 10pt; color: #231f20; font-style: normal; font-variant: normal;"><span style="font-family: OptimaLTStd; font-size: 9pt; color: #231f20; font-style: normal; font-variant: normal;">Smart Grid paradigm promotes advanced load monitoring applications to support demand side management and energy savings. Recently, considerable attention has been paid to Non-Intrusive Load Monitoring to estimate the individual operation and power consumption of the residential appliances, from single point electrical measurements. This approach takes advantage of signal processing<span style="font-family: OptimaLTStd; font-size: 9pt; color: #231f20; font-style: normal; font-variant: normal;"> in order to reduce the hardware effort associated to systems with multiple dedicated sensors. Discriminative characteristics of the <span style="font-family: OptimaLTStd; font-size: 9pt; color: #231f20; font-style: normal; font-variant: normal;">appliances, namely load signatures, could be extracted from the transient or steady state electrical signals. In this paper the effect of <span style="font-family: OptimaLTStd; font-size: 9pt; color: #231f20; font-style: normal; font-variant: normal;">impact factors that can affect the steady state load signatures under realistic conditions are investigated: the voltage supply distortion, <span style="font-family: OptimaLTStd; font-size: 9pt; color: #231f20; font-style: normal; font-variant: normal;">the network impedance and the sampling frequency of the metering equipment. For this purpose, electrical measurements of several <span style="font-family: OptimaLTStd; font-size: 9pt; color: #231f20; font-style: normal; font-variant: normal;">residential appliances were acquired and processed to obtain some indices in the time domain. Results include the comparison of<br /><span style="font-family: OptimaLTStd; font-size: 9pt; color: #231f20; font-style: normal; font-variant: normal;">distinct scenarios, and the evaluation of the suitability and discrimination capacity of the steady state information.</span></span></span></span></span></span></span><br style="font-style: normal; font-variant: normal; font-weight: normal; letter-spacing: normal; line-height: normal; orphans: 2; text-align: -webkit-auto; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px;" /><br class="Apple-interchange-newline" /></span></span></span></span></p>


2020 ◽  
Author(s):  
Keno L. Krewer ◽  
Mischa Bonn

AbstractDifficulties assessing and predicting the current outbreak of the severe acute respiratory syndrome coronavirus 2 can be traced, in part, to the limitations of a static description of a dynamic system. Fourier transforming the time-domain data of infections and fatalities into the frequency domain makes the dynamics easily accessible. Defining a quantity like the “case fatality” as a spectral density allows a more sensible comparison between different countries and demographics during an ongoing outbreak. Such a case fatality informs not only how many of the confirmed cases end up as fatalities, but also when. For COVID-19, knowing this time and using the entire case fatality spectrum allows determining that an outbreak had entered a steady-state (most likely its end) about 14 days before this is obvious from time-domain data. The lag between confirmations and deaths also helps to estimate the effectiveness of contact management: The larger the lag, the less time the average confirmed person had to infect people before quarantine.


Sign in / Sign up

Export Citation Format

Share Document