Optimal Voltage Level-Based Sequential Predictive Current Control With Reduced Complexity for Multilevel Inverters

The conventional Euler-based sequential predictive current control (SPCC) methods for multilevel inverters (MLIs) have aimed to minimize computational complexity, resulting in higher flying capacitor (FC) voltage ripples and poor transient response. These methods typically employ either cost function with weighting factors or offline selection of voltage vectors to reduce the common-mode voltage (CMV). However, improper weighting factor selection and the presence of CMV term in ac current models negatively impact MLI harmonic performance. To address these issues, a new SPCC formulation is proposed, enabling direct estimation of the optimal voltage level based on reference ac currents. This approach eliminates the need for a cost function in ac currents control and simultaneously reduces both computational complexity and CMV. By removing ac current model's dependency on CMV, the proposed formulation further enhances MLI harmonic performance. The mathematical formulation of the proposed SPCC is presented for a four-level inverter (FLI) with both passive and motor drive loads in this study. During the formulation, the Heun's integration method is employed to develop FLI's FC voltage discrete-time models. The performance of the proposed SPCC is demonstrated experimentally on a dSPACE-DS1103 controlled FLI with passive load laboratory prototype. It is further compared with the conventional SPCC methods and their performances are evaluated comprehensively on the laboratory prototype.

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Publication Details

Journal
IEEE Transactions on Power Electronics
Published
2024-10-16
DOI
https://doi.org/10.1109/tpel.2024.3481452
Primary Topic
Multilevel Inverters and Converters
Type
article
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article

Optimal Voltage Level-Based Sequential Predictive Current Control With Reduced Complexity for Multilevel Inverters

Apparao Dekka, Hoang Le
IEEE Transactions on Power Electronics
Multilevel Inverters and Converters
article

Optimal Voltage Level-Based Sequential Predictive Current Control With Reduced Complexity for Multilevel Inverters

Apparao Dekka, Hoang Le
article en

Abstract

The conventional Euler-based sequential predictive current control (SPCC) methods for multilevel inverters (MLIs) have aimed to minimize computational complexity, resulting in higher flying capacitor (FC) voltage ripples and poor transient response. These methods typically employ either cost function with weighting factors or offline selection of voltage vectors to reduce the common-mode voltage (CMV). However, improper weighting factor selection and the presence of CMV term in ac current models negatively impact MLI harmonic performance. To address these issues, a new SPCC formulation is proposed, enabling direct estimation of the optimal voltage level based on reference ac currents. This approach eliminates the need for a cost function in ac currents control and simultaneously reduces both computational complexity and CMV. By removing ac current model's dependency on CMV, the proposed formulation further enhances MLI harmonic performance. The mathematical formulation of the proposed SPCC is presented for a four-level inverter (FLI) with both passive and motor drive loads in this study. During the formulation, the Heun's integration method is employed to develop FLI's FC voltage discrete-time models. The performance of the proposed SPCC is demonstrated experimentally on a dSPACE-DS1103 controlled FLI with passive load laboratory prototype. It is further compared with the conventional SPCC methods and their performances are evaluated comprehensively on the laboratory prototype.

IEEE Transactions on Power ElectronicsVol. 40(1)
Lakehead University (CA)
Affordable and clean energy
Openalex Percentile: Top 84%
Multilevel Inverters and Converters
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Optimal Voltage Level-Based Sequential Predictive Current Control With Reduced Complexity for Multilevel Inverters — Apparao Dekka, Hoang Le · IEEE Transactions on Power Electronics (2024) | TGRS Research Map | TGRS