Gain-Scheduled Internal Model Control of Full-Bridge CLLC Resonant Converters for Wide-Range CC/CV Regulation: A Simulation-Based Study

This paper proposes a gain-scheduled internal model control (GS-IMC) strategy for wide-range constant-voltage (CV) and constant-current (CC) regulation of a full-bridge CLLC resonant converter. The symmetric CLLC resonant network inherently enables zero-voltage switching (ZVS) of the primary-side switches; the contribution of this work lies in the control-oriented modeling and regulation of the converter under pulse-frequency modulation (PFM). Traditional first-harmonic approximation (FHA) models neglect the dominant pole formed by the output capacitance and load resistance and lose accuracy far from resonance, which limits their usefulness for closed-loop design. To overcome these limitations, the nonlinear voltage-gain and frequency-sensitivity characteristics of the converter are characterized over the full range of switching frequency and load using Piecewise Linear Electrical Circuit Simulation (PLECS). The resulting small-signal sensitivities are stored in two-dimensional (2D) lookup tables, from which the parameters of the internal plant model are scheduled according to the measured operating point, without online parameter estimation. The IMC controller is then derived from the scheduled model, so a single filter time constant sets the closed-loop response at all operating points. Simulation results on a 750-V/11-kW converter show that, for CV regulation from 330 V to 900 V and CC regulation from 5 A to 14 A over a load range of 25–150 Ω, the proposed GS-IMC achieves a settling time of 12 ms, eliminates the tracking plateaus, and reduces the overshoot compared with a fixed-gain IMC.

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Publication Details

Journal
Electronics
Published
2026-10-13
DOI
https://doi.org/10.3390/electronics15204705
Primary Topic
Advanced DC-DC Converters
Type
article
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article

Gain-Scheduled Internal Model Control of Full-Bridge CLLC Resonant Converters for Wide-Range CC/CV Regulation: A Simulation-Based Study

Shyr-Long Jeng, Chieng Wei-Hua
Electronics
Advanced DC-DC Converters
article

Gain-Scheduled Internal Model Control of Full-Bridge CLLC Resonant Converters for Wide-Range CC/CV Regulation: A Simulation-Based Study

Shyr-Long Jeng, Chieng Wei-Hua
article en

Abstract

This paper proposes a gain-scheduled internal model control (GS-IMC) strategy for wide-range constant-voltage (CV) and constant-current (CC) regulation of a full-bridge CLLC resonant converter. The symmetric CLLC resonant network inherently enables zero-voltage switching (ZVS) of the primary-side switches; the contribution of this work lies in the control-oriented modeling and regulation of the converter under pulse-frequency modulation (PFM). Traditional first-harmonic approximation (FHA) models neglect the dominant pole formed by the output capacitance and load resistance and lose accuracy far from resonance, which limits their usefulness for closed-loop design. To overcome these limitations, the nonlinear voltage-gain and frequency-sensitivity characteristics of the converter are characterized over the full range of switching frequency and load using Piecewise Linear Electrical Circuit Simulation (PLECS). The resulting small-signal sensitivities are stored in two-dimensional (2D) lookup tables, from which the parameters of the internal plant model are scheduled according to the measured operating point, without online parameter estimation. The IMC controller is then derived from the scheduled model, so a single filter time constant sets the closed-loop response at all operating points. Simulation results on a 750-V/11-kW converter show that, for CV regulation from 330 V to 900 V and CC regulation from 5 A to 14 A over a load range of 25–150 Ω, the proposed GS-IMC achieves a settling time of 12 ms, eliminates the tracking plateaus, and reduces the overshoot compared with a fixed-gain IMC.

ElectronicsVol. 15(20)
National Yang Ming Chiao Tung University (TW), Lunghwa University of Science and Technology (TW)
Openalex Percentile: Top 23%
Advanced DC-DC Converters
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