Predictive Current Control for Multilevel Cascaded H-Bridge Inverters Based on a Deadbeat Solution

Finite-set predictive current control (FS-PCC) is advantageous for power converters due to its high dynamic performance and has received increasing interest in multilevel inverters. Among multilevel inverter topologies, the cascaded H-bridge (CHB) inverter is popular and mature in the industry. Howe...

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Main Authors: Qi, Chen, Tu, Pengfei, Wang, Peng, Zagrodnik, Michael
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2017
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Online Access:https://hdl.handle.net/10356/85213
http://hdl.handle.net/10220/43685
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-852132020-03-07T13:57:25Z Predictive Current Control for Multilevel Cascaded H-Bridge Inverters Based on a Deadbeat Solution Qi, Chen Tu, Pengfei Wang, Peng Zagrodnik, Michael School of Electrical and Electronic Engineering Computational burden Deadbeat solution Finite-set predictive current control (FS-PCC) is advantageous for power converters due to its high dynamic performance and has received increasing interest in multilevel inverters. Among multilevel inverter topologies, the cascaded H-bridge (CHB) inverter is popular and mature in the industry. However, a main drawback of FS-PCC is its large computational burden, especially for the application of CHB inverters. In this paper, an FS-PCC method based on a deadbeat solution for three-phase zero-common-mode-voltage CHB inverters is proposed. In the proposed method, an inverse model of the load is utilized to calculate the reference voltage based on the reference current. In addition, a cost function is directly expressed in the terms of the voltage errors. An optimal control actuation is selected by minimizing the cost function. In the proposed method, only three instead of all of the control actuations are used for the calculations in one sampling period. This leads to a significant reduction in computations. The proposed method is tested on a three-phase 5-level CHB inverter. Simulation and experimental results show a very similar and comparable control performance from the proposed method compared with the traditional FS-PCC method which evaluates the cost function for all of the control actuations. NRF (Natl Research Foundation, S’pore) Published version 2017-09-05T02:18:00Z 2019-12-06T15:59:35Z 2017-09-05T02:18:00Z 2019-12-06T15:59:35Z 2017 Journal Article Qi, C., Tu, P., Wang, P., & Zagrodnik, M. (2017). Predictive Current Control for Multilevel Cascaded H-Bridge Inverters Based on a Deadbeat Solution. Journal of Power Electronics, 17(1), 76-87. 1598-2092 https://hdl.handle.net/10356/85213 http://hdl.handle.net/10220/43685 10.6113/JPE.2017.17.1.76 en Journal of Power Electronics © 2017 Korean Institute of Power Electronics (KIPE). This paper was published in Journal of Power Electronics and is made available as an electronic reprint (preprint) with permission of Korean Institute of Power Electronics (KIPE). The published version is available at: [http://dx.doi.org/10.6113/JPE.2017.17.1.76]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. 12 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Computational burden
Deadbeat solution
spellingShingle Computational burden
Deadbeat solution
Qi, Chen
Tu, Pengfei
Wang, Peng
Zagrodnik, Michael
Predictive Current Control for Multilevel Cascaded H-Bridge Inverters Based on a Deadbeat Solution
description Finite-set predictive current control (FS-PCC) is advantageous for power converters due to its high dynamic performance and has received increasing interest in multilevel inverters. Among multilevel inverter topologies, the cascaded H-bridge (CHB) inverter is popular and mature in the industry. However, a main drawback of FS-PCC is its large computational burden, especially for the application of CHB inverters. In this paper, an FS-PCC method based on a deadbeat solution for three-phase zero-common-mode-voltage CHB inverters is proposed. In the proposed method, an inverse model of the load is utilized to calculate the reference voltage based on the reference current. In addition, a cost function is directly expressed in the terms of the voltage errors. An optimal control actuation is selected by minimizing the cost function. In the proposed method, only three instead of all of the control actuations are used for the calculations in one sampling period. This leads to a significant reduction in computations. The proposed method is tested on a three-phase 5-level CHB inverter. Simulation and experimental results show a very similar and comparable control performance from the proposed method compared with the traditional FS-PCC method which evaluates the cost function for all of the control actuations.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Qi, Chen
Tu, Pengfei
Wang, Peng
Zagrodnik, Michael
format Article
author Qi, Chen
Tu, Pengfei
Wang, Peng
Zagrodnik, Michael
author_sort Qi, Chen
title Predictive Current Control for Multilevel Cascaded H-Bridge Inverters Based on a Deadbeat Solution
title_short Predictive Current Control for Multilevel Cascaded H-Bridge Inverters Based on a Deadbeat Solution
title_full Predictive Current Control for Multilevel Cascaded H-Bridge Inverters Based on a Deadbeat Solution
title_fullStr Predictive Current Control for Multilevel Cascaded H-Bridge Inverters Based on a Deadbeat Solution
title_full_unstemmed Predictive Current Control for Multilevel Cascaded H-Bridge Inverters Based on a Deadbeat Solution
title_sort predictive current control for multilevel cascaded h-bridge inverters based on a deadbeat solution
publishDate 2017
url https://hdl.handle.net/10356/85213
http://hdl.handle.net/10220/43685
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