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Modulated Model Predictive Torque Control for Fault-Tolerant Inverter-Fed Induction Motor Drives With Single DC-Link Voltage Sensor
Indexado
WoS WOS:001045167800077
Scopus SCOPUS_ID:85153516623
DOI 10.1109/TPEL.2023.3267078
Año 2023
Tipo artículo de investigación

Citas Totales

Autores Afiliación Chile

Instituciones Chile

% Participación
Internacional

Autores
Afiliación Extranjera

Instituciones
Extranjeras


Abstract



Four-switch three-phase inverter (FSTPI) is widely used as a cost-effective fault-tolerant topology of six-switch three-phase inverter with an open-phase fault. To solve the inherent dc-link capacitor voltage offset (CVO) issue of FSTPI, two dc-link capacitor voltage sensors are required in conventional model predictive torque control (MPTC) strategies. To improve the reliability and reduce the cost of induction motor (IM) drives, a modulated MPTC (M-MPTC) for FSTPI-fed IM with single dc-link voltage sensor is proposed in this article. Therein, the relationship of the CVO and the load current is established to obtain the fundamental component of CVO. The two capacitor voltages are reconstructed by single dc-link voltage sensor and the fundamental component of CVO. To suppress the CVO, a cost function that only contains the output voltage vector is designed. The inner relationship between the proposed M-MPTC with single dc-link voltage sensor and the conventional M-MPTC with two dc-link voltage sensors is derived. To retain the load current within the allowed range, a current constraint scheme is proposed and integrated into the M-MPTC. Various simulation and experimental studies are carried out to verify the effectiveness of the proposed strategy.

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Disciplinas de Investigación



WOS
Engineering, Electrical & Electronic
Scopus
Electrical And Electronic Engineering
SciELO
Sin Disciplinas

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Publicaciones WoS (Ediciones: ISSHP, ISTP, AHCI, SSCI, SCI), Scopus, SciELO Chile.

Colaboración Institucional



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Autores - Afiliación



Ord. Autor Género Institución - País
1 Li, Ze - Hebei University - China
Hebei Univ - China
2 Xia, Jinhui - Southeast University - China
College of Control Science and Engineering, Zhejiang University - China
Southeast Univ - China
Zhejiang Univ - China
3 Gao, Xiaonan - Technische Universität München - Alemania
TECH UNIV MUNICH - Alemania
4 RODRIGUEZ-PEREZ, JOSE RAMON Hombre Universidad San Sebastián - Chile
5 Guo, Yuanbo - Dalian University of Technology - China
Dalian Univ Technol - China
6 Zhang, Xiaohua - Dalian University of Technology - China
Dalian Univ Technol - China

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Financiamiento



Fuente
National Natural Science Foundation of China
Agencia Nacional de Investigación y Desarrollo
High-level Talent Research Startup Project of Hebei University

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Agradecimientos



Agradecimiento
This work was supported in part by High-level Talent Research Startup Project of Hebei University under Grant 521100222019 and in part by the National Natural Science Foundation of China under Grant 62103367. The work of J. Rodriguez was supported by ANID through Projects FB0008, 1210208, and 1221293
This work was supported in part by High-level Talent Research Startup Project of Hebei University under Grant 521100222019 and in part by the National Natural Science Foundation of China under Grant 62103367. The work of J. Rodriguez was supported by ANID through Projects FB0008, 1210208, and 1221293. Recommended for publication by Associate Editor N. R. N. Idris. (Corresponding author: Jinhui Xia.)

Muestra la fuente de financiamiento declarada en la publicación.