PROJECT TITLE :

Model Predictive Control Methods to Reduce Common-Mode Voltage for Three-Phase Voltage Source Inverters

ABSTRACT:

In this paper, we tend to propose model predictive control strategies to reduce the common-mode voltage of 3-section voltage source inverters (VSIs). In the reduced common-mode voltage-model predictive management (RCMV-MPC) methods proposed in this paper, solely nonzero voltage vectors are utilised to scale back the common-mode voltage and to manage the load currents. Additionally, two nonzero voltage vectors are selected from the value function at every sampling amount, rather than using only one optimal vector during one sampling period. The 2 selected nonzero vectors are distributed in one sampling period in such a approach as to reduce the error between the measured load current and the reference. While not utilizing the zero vectors, the common-mode voltage controlled by the proposed RCMV-MPC algorithms can be restricted within ±Vdc/six. Furthermore, application of the two nonzero vectors with optimal time sharing between them can yield satisfactory load current ripple performance while not using the zero vectors. Thus, the proposed RCMV-MPC methods can scale back the common-mode voltage also management the load currents with fast transient response and satisfactory load current ripple performance compared with the traditional model predictive management method. Simulation and experimental results are included to verify the effectiveness of the proposed RCMV-MPC ways.


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