Multiple-Voltage-Vector Model Predictive Control with Reduced Complexity for Multilevel Inverters

Yong Yang, Huiqing Wen, Mingdi Fan, Liqun He, Menxi Xie, Rong Chen, Margarita Norambuena, Jose Rodriguez

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

5 Citas (Scopus)

Resumen

Conventional model predictive control (MPC) suffers from unfixed switching frequency, heavy computational burden, and cumbersome weighting factors' tuning, especially for multilevel inverter applications due to a large number of voltage vectors. To address these concerns, this article proposes multiple-voltage-vector (MVV) MPC algorithms with reduced complexity and fixed switching frequency for T-type three-phase three-level inverters. First, MMVs are adopted during each control period, and their execution times are set according to the predefined cost functions. Second, weighting factors for balancing the neutral point (NP) voltage in the cost function are eliminated by utilizing redundant voltage vectors, which simplifies the control implementation. Third, through mapping the reference voltage in the first large sector, the calculation complexity for the execution times of voltage vectors in different large sectors becomes much lower. Finally, main experimental results were presented to validate the effectiveness of the proposed algorithms.

Idioma originalInglés
Número de artículo8990089
Páginas (desde-hasta)105-117
Número de páginas13
PublicaciónIEEE Transactions on Transportation Electrification
Volumen6
N.º1
DOI
EstadoPublicada - mar 2020
Publicado de forma externa

Áreas temáticas de ASJC Scopus

  • Ingeniería automovilística
  • Transporte
  • Ingeniería energética y tecnologías de la energía
  • Ingeniería eléctrica y electrónica

Huella

Profundice en los temas de investigación de 'Multiple-Voltage-Vector Model Predictive Control with Reduced Complexity for Multilevel Inverters'. En conjunto forman una huella única.

Citar esto