A Time-Decoupled PWM Implementation Architecture Based on Predictive Duty-Cycle Sequences for High-Switching-Frequency Three-Phase Buck Rectifiers

High-switching-frequency operation substantially reduces the available time for sampling, control computation, modulation mapping, PWM-register updating, and auxiliary interrupt operations in digitally controlled three-phase buck rectifiers. Given this, this paper presents a time-decoupled PWM implementation architecture (TD-PWM) based on predictive duty-cycle sequences that enables sufficient computational redundancy. In the proposed architecture, the sampled information is used to generate an N-element duty-cycle sequence for the following control period. The generated sequence is stored in a buffer and subsequently loaded into the PWM registers one element per switching period. Consequently, prediction, control calculation, and SVPWM mapping are performed at the control frequency, whereas the duty-cycle values are updated at the switching frequency. A two-timescale execution structure is implemented in which the control-period task performs sampling and sequence generation, while the high-priority switching-period task performs sequence indexing and PWM-register loading. Experimental validation is conducted on a 400 W three-phase buck-rectifier prototype with a switching frequency of 100 kHz, a control frequency of 20 kHz, and N = 5. Under the investigated operating conditions, the proposed architecture achieves an input-current THD of 2.06% and shorter measured settling times than the two reference implementations. The results demonstrate the feasibility of the proposed implementation architecture.

Authors

Institutions

Publication Details

Journal
Energies
Published
2026-09-06
DOI
https://doi.org/10.3390/en19174213
Primary Topic
Multilevel Inverters and Converters
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Time-Decoupled PWM Implementation Architecture Based on Predictive Duty-Cycle Sequences for High-Switching-Frequency Three-Phase Buck Rectifiers

Jianxiao Zou, Li Ding, Dehong Zhou, Siping Feng
Energies
Multilevel Inverters and Converters
article

A Time-Decoupled PWM Implementation Architecture Based on Predictive Duty-Cycle Sequences for High-Switching-Frequency Three-Phase Buck Rectifiers

Jianxiao Zou, Li Ding, Dehong Zhou, Siping Feng
article en

Abstract

High-switching-frequency operation substantially reduces the available time for sampling, control computation, modulation mapping, PWM-register updating, and auxiliary interrupt operations in digitally controlled three-phase buck rectifiers. Given this, this paper presents a time-decoupled PWM implementation architecture (TD-PWM) based on predictive duty-cycle sequences that enables sufficient computational redundancy. In the proposed architecture, the sampled information is used to generate an N-element duty-cycle sequence for the following control period. The generated sequence is stored in a buffer and subsequently loaded into the PWM registers one element per switching period. Consequently, prediction, control calculation, and SVPWM mapping are performed at the control frequency, whereas the duty-cycle values are updated at the switching frequency. A two-timescale execution structure is implemented in which the control-period task performs sampling and sequence generation, while the high-priority switching-period task performs sequence indexing and PWM-register loading. Experimental validation is conducted on a 400 W three-phase buck-rectifier prototype with a switching frequency of 100 kHz, a control frequency of 20 kHz, and N = 5. Under the investigated operating conditions, the proposed architecture achieves an input-current THD of 2.06% and shorter measured settling times than the two reference implementations. The results demonstrate the feasibility of the proposed implementation architecture.

EnergiesVol. 19(17)
University of Electronic Science and Technology of China (CN), Shenzhen Institutes of Advanced Technology (CN)
Openalex Percentile: Top 20%
Multilevel Inverters and Converters
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.