Open AccessTwo‐vector based low‐complexity model predictive flux control for current‐source inverter‐fed induction motor drive
Author(s) -
Gao Hang,
Wu Bin,
Xu Dewei,
Zargari Navid R.
Publication year - 2020
Publication title -
iet electric power applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.815
H-Index - 97
eISSN - 1751-8679
pISSN - 1751-8660
DOI - 10.1049/iet-epa.2019.0870
Subject(s) - control theory (sociology) , induction motor , robustness (evolution) , inverter , model predictive control , vector control , computer science , power (physics) , engineering , voltage , control (management) , physics , chemistry , electrical engineering , biochemistry , quantum mechanics , artificial intelligence , gene
Model predictive control is an effective approach to achieve high performance on electric motor drives. In this study, a two‐vector based low‐complexity model predictive flux control (TVLC‐MPFC) is proposed and introduced for low power current‐source inverter (CSI)‐fed induction motor (IM) drive. In contrast to conventional two‐vector based model predictive flux control (TV‐MPFC), TVLC‐MPFC is a more simplified scheme with a lower calculation burden, which eliminates the requirement on the iteration procedures to obtain the results of the optimal current vector combination with optimal dwell time. Moreover, since TVLC‐MPFC avoids the possibility of selecting the wrong vector combination in some cases, which would happen with conventional TV‐MPFC, it presents better output performance than TV‐MPFC. The robustness of TVLC‐MPFC under parameter uncertainty is discussed as well. Experimental tests are carried out on a low power CSI‐fed IM drive (5 kW/208 V/14.3 A) and verify the effectiveness of the proposed scheme.