Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/658050
Title: A Digital Hysteresis Current Controller for Three-Level Neural-Point-Clamped Inverter With Mixed-Levels and Prediction-Based Sampling
Authors: Hao Yi;Fang Zhuo;Feng Wang;Zhenxiong Wang
subject: Three-level NPC inverter|Mixed-level|prediction-based sampling|Digital hysteresis controller
Year: 2016
Publisher: IEEE
Abstract: For a grid-tied three-level neural-point-clamped (NPC) inverter, fully digital hysteresis controller with simple variable hysteresis band is insufficient to stabilize switching frequency (f<sub>s</sub>). The challenge mainly comes from the restriction of analogue-to-digital converter (ADC) sampling frequency, which leads to inaccurate current-boundary-touching capture. As a result, f<sub>s</sub> jitter appears. This phenomena becomes much more serious around grid voltage zero-crossing points due to zero-approaching hysteresis band, where obvious f<sub>s</sub> variation happens. To stabilize f<sub>s</sub> in a fully digital manner, two techniques are proposed in this paper: the mixed-level scheme and the prediction-based sampling method. The former one is used to cope with the obvious f<sub>s</sub> variation around grid voltage zero-crossing points. It switches operating status from three-level state into two-level state around grid voltage zero-crossing points to enlarge the hysteresis band for digital implementation. The latter one is used to resolve f<sub>s</sub> jitter. It makes the sampling and switching to happen at the moment of current boundary-touching to achieve the most effective boundary-comparing with the lowest ADC sampling frequency. With these two techniques, f<sub>s</sub> of the grid-tied three-level NPC inverter could be well stabilized with a fully digital hysteresis controller, and therefore, high-quality grid-side could be achieved.
URI: http://localhost/handle/Hannan/161675
http://localhost/handle/Hannan/658050
ISSN: 0885-8993
1941-0107
volume: 31
issue: 5
Appears in Collections:2016

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Title: A Digital Hysteresis Current Controller for Three-Level Neural-Point-Clamped Inverter With Mixed-Levels and Prediction-Based Sampling
Authors: Hao Yi;Fang Zhuo;Feng Wang;Zhenxiong Wang
subject: Three-level NPC inverter|Mixed-level|prediction-based sampling|Digital hysteresis controller
Year: 2016
Publisher: IEEE
Abstract: For a grid-tied three-level neural-point-clamped (NPC) inverter, fully digital hysteresis controller with simple variable hysteresis band is insufficient to stabilize switching frequency (f<sub>s</sub>). The challenge mainly comes from the restriction of analogue-to-digital converter (ADC) sampling frequency, which leads to inaccurate current-boundary-touching capture. As a result, f<sub>s</sub> jitter appears. This phenomena becomes much more serious around grid voltage zero-crossing points due to zero-approaching hysteresis band, where obvious f<sub>s</sub> variation happens. To stabilize f<sub>s</sub> in a fully digital manner, two techniques are proposed in this paper: the mixed-level scheme and the prediction-based sampling method. The former one is used to cope with the obvious f<sub>s</sub> variation around grid voltage zero-crossing points. It switches operating status from three-level state into two-level state around grid voltage zero-crossing points to enlarge the hysteresis band for digital implementation. The latter one is used to resolve f<sub>s</sub> jitter. It makes the sampling and switching to happen at the moment of current boundary-touching to achieve the most effective boundary-comparing with the lowest ADC sampling frequency. With these two techniques, f<sub>s</sub> of the grid-tied three-level NPC inverter could be well stabilized with a fully digital hysteresis controller, and therefore, high-quality grid-side could be achieved.
URI: http://localhost/handle/Hannan/161675
http://localhost/handle/Hannan/658050
ISSN: 0885-8993
1941-0107
volume: 31
issue: 5
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7185425.pdf3.14 MBAdobe PDFThumbnail
Preview File
Title: A Digital Hysteresis Current Controller for Three-Level Neural-Point-Clamped Inverter With Mixed-Levels and Prediction-Based Sampling
Authors: Hao Yi;Fang Zhuo;Feng Wang;Zhenxiong Wang
subject: Three-level NPC inverter|Mixed-level|prediction-based sampling|Digital hysteresis controller
Year: 2016
Publisher: IEEE
Abstract: For a grid-tied three-level neural-point-clamped (NPC) inverter, fully digital hysteresis controller with simple variable hysteresis band is insufficient to stabilize switching frequency (f<sub>s</sub>). The challenge mainly comes from the restriction of analogue-to-digital converter (ADC) sampling frequency, which leads to inaccurate current-boundary-touching capture. As a result, f<sub>s</sub> jitter appears. This phenomena becomes much more serious around grid voltage zero-crossing points due to zero-approaching hysteresis band, where obvious f<sub>s</sub> variation happens. To stabilize f<sub>s</sub> in a fully digital manner, two techniques are proposed in this paper: the mixed-level scheme and the prediction-based sampling method. The former one is used to cope with the obvious f<sub>s</sub> variation around grid voltage zero-crossing points. It switches operating status from three-level state into two-level state around grid voltage zero-crossing points to enlarge the hysteresis band for digital implementation. The latter one is used to resolve f<sub>s</sub> jitter. It makes the sampling and switching to happen at the moment of current boundary-touching to achieve the most effective boundary-comparing with the lowest ADC sampling frequency. With these two techniques, f<sub>s</sub> of the grid-tied three-level NPC inverter could be well stabilized with a fully digital hysteresis controller, and therefore, high-quality grid-side could be achieved.
URI: http://localhost/handle/Hannan/161675
http://localhost/handle/Hannan/658050
ISSN: 0885-8993
1941-0107
volume: 31
issue: 5
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7185425.pdf3.14 MBAdobe PDFThumbnail
Preview File