Discrete Space Vector Modulation Based Model Predictive Flux Control With Reduced Switching Frequency for IM Drive
| Autor: | Margarita Norambuena, Ilham Osman, Muhammed Fazlur Rahman, Jose Rodriguez, Dan Xiao |
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| Rok vydání: | 2021 |
| Předmět: |
Computer science
020208 electrical & electronic engineering Energy Engineering and Power Technology 02 engineering and technology Reduction (complexity) Sampling (signal processing) Control theory Control system 0202 electrical engineering electronic engineering information engineering Inverter Commutation Transient (oscillation) Electrical and Electronic Engineering Induction motor Voltage |
| Zdroj: | IEEE Transactions on Energy Conversion. 36:1357-1367 |
| ISSN: | 1558-0059 0885-8969 |
| Popis: | This article presents an optimal model predictive flux control (MPFC) for a two-level inverter fed induction motor. Integrating discrete SVM into FCS-MPFC enhances the performance of the IM drive. However, conventional DSVM-MPFC requires to enumerate and evaluate a higher number of virtual vectors in the prediction loop. In this paper, a high-efficient and low complexity voltage selection method is proposed to reduce the number of candidate voltage vectors from 38 to 15 without any suboptimality. Both steady-state and transient performances of the proposed method remain the same as the 38-vector based conventional DSVM-MPFC, producing the same cost-function values in all operating conditions. Furthermore, an online switching frequency reduction technique is proposed to achieve a minimum commutation per inverter vector change within each sampling cycle and between adjacent cycles. By appropriately arranging the sequence of real voltage vectors in each sampling cycle, a lower average switching frequency is achieved. The proposed switching frequency reduction method decreases the switching losses without compromising the performance of DSVM-MPFC as only the applied sequences of the real voltage vectors are optimized. Experimental studies are conducted to verify the effectiveness of the proposed algorithm. |
| Databáze: | OpenAIRE |
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