Deadbeat Model-Predictive Torque Control With Discrete Space-Vector Modulation for PMSM Drives

This paper proposes an alternative strategy of finite-control-set model-predictive torque control (MPTC) to reduce the computational burden and the torque ripple and decouple the switching frequency from the controller sampling time. An improved discrete space-vector modulation (DSVM) technique is u...

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Bibliographic Details
Published in:IEEE transactions on industrial electronics (1982) 2017-05, Vol.64 (5), p.3537-3547
Main Authors: Wang, Yuanlin, Wang, Xiaocan, Xie, Wei, Wang, Fengxiang, Dou, Manfeng, Kennel, Ralph M., Lorenz, Robert D., Gerling, Dieter
Format: Article
Language:English
Subjects:
Couplings
Deadbeat (DB)
discrete space-vector modulation (DSVM)
Electric potential
Mathematical analysis
Mathematical model
model-predictive torque control (MPTC)
Modulation
permanent-magnet synchronous machine (PMSM)
Predictive control
Stators
Switches
Torque
Torque control
Vectors (mathematics)
Voltage
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Summary:This paper proposes an alternative strategy of finite-control-set model-predictive torque control (MPTC) to reduce the computational burden and the torque ripple and decouple the switching frequency from the controller sampling time. An improved discrete space-vector modulation (DSVM) technique is utilized to synthesize a large number of virtual voltage vectors. The deadbeat (DB) technique is used to optimize the voltage vector selection process, avoiding enumerating all the feasible voltage vectors. With this proposed method, only three voltage vectors are tested in each predictive step. Based on the improved DSVM method, the three candidate voltage vectors are calculated by using a novel algebraic way. This new strategy has the benefits of both the MPTC method and the DB method. The effectiveness of the proposed strategy is validated based on a test bench.
ISSN:0278-0046
1557-9948
DOI:10.1109/TIE.2017.2652338