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arxiv: 2604.18810 · v1 · submitted 2026-04-20 · 📡 eess.SY · cs.SY

Simulation of Switching Converters on the Level of Averaged Voltages and Currents

Aleksandra Leki\'c , Predrag Pejovi\'c This is my paper

Pith reviewed 2026-05-10 03:31 UTC · model grok-4.3

classification 📡 eess.SY cs.SY
keywords switching convertersaveraged modelssimulation algorithmswitching cellcontinuous conduction modediscontinuous conduction modepower electronicsquasi-steady-state approximation
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The pith

An algorithm simulates switching converters on averaged voltages and currents then reconstructs instantaneous waveforms using quasi-steady-state and linear ripple approximations.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper presents an algorithm that first solves an averaged circuit model of switching converters built around the switching cell concept. Instantaneous values of voltages and currents are then constructed from that averaged solution by applying quasi-steady-state and linear ripple approximations. The method is shown to work for both continuous and discontinuous conduction modes and is demonstrated on the buck, boost, buck-boost, and flyback converters, the last requiring only a minor generalization of the switching cell. A sympathetic reader would care because the approach supplies both average quantities and detailed ripple information without requiring a full time-step simulation of every switching event.

Core claim

By simulating the averaged circuit model that uses the switching cell concept and then applying quasi-steady-state and linear ripple approximations, both the averaged and the instantaneous waveforms of voltages and currents can be obtained for switching converters operating in continuous or discontinuous conduction mode, as verified by simulations of buck, boost, buck-boost, and flyback topologies.

What carries the argument

The switching cell concept, which replaces the switching elements with an averaged equivalent circuit whose solution is then post-processed with quasi-steady-state and linear ripple approximations to recover instantaneous waveforms.

If this is right

  • The same averaged-model simulation plus reconstruction steps apply directly to buck, boost, and buck-boost converters in both continuous and discontinuous conduction.
  • A small generalization of the switching cell permits the method to cover the flyback converter as well.
  • Both averaged dc values and the superimposed ripple waveforms are produced from a single averaged simulation run.
  • The approach supplies an efficient alternative to cycle-by-cycle switching simulation while still delivering the instantaneous waveform details needed for design.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The method could shorten design cycles for power supplies by letting engineers quickly estimate peak currents and voltage ripple before running full-detail simulations.
  • Further generalization of the switching cell might allow the same framework to handle more complex isolated or resonant topologies.
  • Because the core computation stays at the averaged level, the technique could be embedded inside optimization loops that tune converter parameters for efficiency or size.
  • The linear-ripple step may also yield simple closed-form expressions for ripple amplitude that designers could use without any numerical simulation.

Load-bearing premise

The quasi-steady-state and linear ripple approximations remain accurate across the operating range, and the switching cell concept can be generalized to additional topologies without loss of fidelity.

What would settle it

A side-by-side comparison in which the reconstructed instantaneous waveforms deviate substantially from a full switching simulation or from laboratory measurements on a buck-boost converter in discontinuous mode would show the approximations are not sufficient.

Figures

Figures reproduced from arXiv: 2604.18810 by Aleksandra Leki\'c, Predrag Pejovi\'c.

Figure 1
Figure 1. Figure 1: Averaged model of a switching cell. a) b) [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: The buck converter: a) with synchronized bidirectional switches; b) with a switch and a diode [PITH_FULL_IMAGE:figures/full_fig_p002_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: , where the capacitor is replaced by its discretized equivalent according to the trapezoidal integration formula. All of the currents and voltages in the circuit shown in [PITH_FULL_IMAGE:figures/full_fig_p002_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Simulation results of the example 1 : converter of [PITH_FULL_IMAGE:figures/full_fig_p004_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Simulated flyback converters, a) with bidirectional switches and the inductor and b) with switch, diode and inductor [PITH_FULL_IMAGE:figures/full_fig_p004_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Simulation results of the example 2: converter of [PITH_FULL_IMAGE:figures/full_fig_p005_6.png] view at source ↗
read the original abstract

An algorithm for simulation of switching converters is proposed in the paper. The algorithm is based on simulation of averaged circuit model applying "switching cell" concept, and construction of instantaneous values of the waveforms using quasi steady state and linear ripple approximation. Simulation covers converters operating both in the continuous and the discontinuous conduction mode. Application of the algorithm is demonstrated by simulation results of all three of the basic converters: buck, boost and buckboost, as well as a flyback converter, which required slight generalization of the switching cell concept.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 2 minor

Summary. The manuscript proposes an algorithm for simulating switching converters by first solving an averaged circuit model that employs a 'switching cell' abstraction, then reconstructing instantaneous voltage and current waveforms via quasi-steady-state and linear-ripple approximations. The approach is asserted to cover both continuous and discontinuous conduction modes and is illustrated on the buck, boost, buck-boost, and flyback topologies, the last requiring a minor generalization of the switching cell.

Significance. If the reconstruction step can be shown to remain accurate across operating regimes, the method would supply a computationally lighter alternative to cycle-by-cycle simulation for long-horizon studies or parameter optimization. The explicit treatment of DCM and the flyback extension are welcome, yet the absence of any quantitative error assessment or comparison against a reference simulator leaves the practical utility unestablished.

major comments (3)
  1. [DCM operation and reconstruction] DCM section: the linear-ripple assumption is applied even though the inductor current reaches zero for a finite interval; no derivation of the modified ripple slopes or analytic error bound is supplied, leaving the central reconstruction claim unsupported for DCM.
  2. [Flyback converter example] Flyback demonstration: the 'slight generalization' of the switching cell is introduced without re-deriving the averaged equations or the quasi-steady-state ripple expressions from first principles; the effect on accuracy is therefore unquantified.
  3. [Simulation results] Results and validation: no RMS error, peak deviation, or side-by-side comparison against cycle-by-cycle reference waveforms is reported for any topology or operating point, so the claim that the reconstructed instantaneous values are 'usable' cannot be evaluated.
minor comments (2)
  1. [Abstract] Abstract: a single sentence on achieved accuracy or computational speedup would help readers gauge the method's value.
  2. [Throughout] Notation: averaged versus instantaneous quantities should be distinguished by consistent symbols or subscripts throughout.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for the constructive and detailed review. The comments highlight important areas where the manuscript can be strengthened, particularly regarding explicit derivations for DCM and the flyback generalization, as well as quantitative validation of the reconstruction accuracy. We address each major comment below and will incorporate revisions accordingly.

read point-by-point responses

  1. Referee: DCM section: the linear-ripple assumption is applied even though the inductor current reaches zero for a finite interval; no derivation of the modified ripple slopes or analytic error bound is supplied, leaving the central reconstruction claim unsupported for DCM.

    Authors: We acknowledge that the DCM analysis applies the linear-ripple approximation without a dedicated derivation of the modified slopes that account for the zero-current interval. The switching-cell model in the manuscript sets the inductor current to zero during the discontinuous phase, with reconstruction proceeding from the averaged values, but this was not accompanied by explicit slope derivations or error bounds. In the revised manuscript we will add a step-by-step derivation of the ripple slopes for the three DCM intervals (switch on, switch off with nonzero current, and zero-current) together with an analytic error estimate under the quasi-steady-state assumption. This will directly support the reconstruction claim for DCM operation. revision: yes

  2. Referee: Flyback demonstration: the 'slight generalization' of the switching cell is introduced without re-deriving the averaged equations or the quasi-steady-state ripple expressions from first principles; the effect on accuracy is therefore unquantified.

    Authors: The flyback example extends the switching-cell concept to incorporate transformer isolation and secondary-side rectification. While the manuscript presents the modified cell and resulting waveforms, we agree that a complete re-derivation from first principles is needed to make the generalization transparent. The revised version will include the full derivation of the averaged equations and quasi-steady-state ripple expressions for the flyback topology, explicitly showing the changes relative to the non-isolated cells. We will also discuss the expected impact on reconstruction accuracy. revision: yes

  3. Referee: Results and validation: no RMS error, peak deviation, or side-by-side comparison against cycle-by-cycle reference waveforms is reported for any topology or operating point, so the claim that the reconstructed instantaneous values are 'usable' cannot be evaluated.

    Authors: The referee correctly identifies the absence of quantitative error metrics. The original manuscript illustrates the algorithm through waveform plots for the four topologies but does not report RMS errors, peak deviations, or direct numerical comparisons with cycle-by-cycle reference simulations. In the revision we will augment the results section with these quantitative measures for representative operating points in both CCM and DCM, including side-by-side waveform overlays and tabulated error statistics. This will allow an objective assessment of the practical accuracy of the reconstructed instantaneous values. revision: yes

Circularity Check

0 steps flagged

No circularity: forward construction of simulation algorithm from averaged models and standard approximations

full rationale

The paper proposes a simulation algorithm that first solves an averaged circuit model (via the switching-cell concept) and then reconstructs instantaneous waveforms using quasi-steady-state and linear-ripple approximations. These steps are constructive modeling choices applied to the averaged solution; no parameters are fitted to a data subset and then re-used as a 'prediction' of a closely related quantity, no self-citation chain is invoked to justify a uniqueness theorem or ansatz, and no known empirical pattern is merely renamed. The derivation chain therefore remains self-contained and does not reduce to its inputs by construction.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Abstract-only review supplies no explicit free parameters, axioms, or invented entities; the linear ripple and quasi-steady-state assumptions are implicit but not quantified.

pith-pipeline@v0.9.0 · 5385 in / 1056 out tokens · 47333 ms · 2026-05-10T03:31:50.854785+00:00 · methodology

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Reference graph

Works this paper leans on

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    INTRODUCTION Motivation for this research lies in the fact that the most of available circuit simulators is general-purpose oriented [6] and apply unnecessarily complex device models, characterized by continuous and differentiable functions. On the other hand, the most important components of power electronics are switches, characterized by discontinuitie...

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    APPLIED SWITCHING CELL In this section, switc hing cell, used to describe both the CCM and DCM operating modes, is presented. Switching cells are treated as a three terminal devices. In this paper, two families of the switching cells are described: for all three of the basic converters (buck, boost, and buck-boost), switching cells classified as cell A fa...

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