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A Modified Model Predictive Current Control of Permanent Magnet Synchronous Motor Drive

Sagar Gajanan Petkar, Kusuma Eshwar, Vinay Kumar Thippiripati

2020IEEE Transactions on Industrial Electronics94 citationsDOI

Abstract

Model predictive current control (MPCC) is widely used and more popular control method for a permanent magnet synchronous motor (PMSM) drive. It is less complex and simple to understand as compared with other predictive control methods. MPCC involves the evaluation of a simpler cost function for selecting an optimal voltage vector (VV), which is based on the minimization of error between reference and sensed currents. For a two-level inverter with limited number of VV, MPCC gives poor steady-state performance as a single VV is applied over one sampling interval. In this article, for improving the steady-state performance of PMSM, an improved MPCC is proposed. In this proposed MPCC method, an active VV along with a zero VV is applied similar to the duty cycle control (DCC); however, the timings of active VV and zero VV are selected to decrease the q-axis current ripples. The method introduced in this article is based on the calculation of q-axis current slopes to calculate optimal timing for different VVs. The method introduced in this article is compared with conventional MPCC (C-MPCC) and MPCC with DCC. Simulation and experimentation is carried out for comparison and to confirm the effectiveness of introduced MPCC.

Topics & Concepts

Control theory (sociology)Duty cycleSynchronous motorInverterCurrent (fluid)Computer scienceVoltageModel predictive controlEngineeringControl (management)Electrical engineeringArtificial intelligenceMultilevel Inverters and ConvertersSensorless Control of Electric MotorsAdvanced DC-DC Converters
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