
Model predictive control with a novel cost function evaluation scheme for OW‐PMSM drives
Author(s) -
Zheng Zhihao,
Sun Dan,
Wang Mingze,
Nian Heng
Publication year - 2020
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2020.0883
Subject(s) - control theory (sociology) , inverter , dual (grammatical number) , function (biology) , model predictive control , process (computing) , computer science , scheme (mathematics) , voltage , control (management) , engineering , mathematics , art , literature , electrical engineering , operating system , mathematical analysis , artificial intelligence , evolutionary biology , biology
In open‐winding permanent magnet synchronous motor (OW‐PMSM) system, the voltage vectors (VVs) produced by the dual‐inverter are abundant and one VV may correspond to different switching states. It is time‐consuming for model predictive control strategy to evaluate the cost function with all VVs and select the optimal switching states. A novel cost function evaluation scheme is proposed in this Letter and the evaluation times of the cost function is significantly reduced. The optimal switching states of each phase are decided by evaluating the cost function with six virtual vectors and a zero vector and the switching states of each phase are directly decided without additional evaluation process. The calculation time is significantly reduced with the proposed strategy and the steady‐state performance of the OW‐PMSM system is maintained similar to the conventional strategy. Experimental results have validated the effectiveness of the proposed strategy.