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Simple three-level neutral point voltage balance control strategy based on SVPWM

Authors: Bo Gong; Shanmei Cheng; Yi Qin;

Simple three-level neutral point voltage balance control strategy based on SVPWM

Abstract

Abstract The unbalance of the neutral point voltage is an inherent problem of three-level neutral-point-clamped (NPC) inverter, the effect of neutral point voltage balancing which is caused by voltage vector is analyzed, and the relationship of the voltage offset and neutral point voltage is studied in this paper. This paper proposes a novel neutral point balance strategy for three-level NPC inverter based on space vector pulse width modulation (SVPWM). A voltage offset is added to the modulation wave, and a closed-loop neutral point voltage balance control system is designed. In the control system, the dwelling time of synthesis voltage vectors for SVPWM is varied to solve the problem of the unbalance of the neutral point voltage, the sequence of the voltage vectors maintains unchanging. Simulation and experimental results show the neutral point voltage balancing control strategy based on SVPWM is effective.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Average
Top 10%
Average
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