An Adaptive Strategy to Compensate Nonlinear Effects of Voltage Source Inverters Based on Artificial Neural Networks
In motor drives, distortions of phase voltages and currents are often caused by nonlinear effects of inverters such as dead time, turn-on delay, turn-off delay and voltage drop of power devices. To eliminate these distortions, the dead-time compensation voltage is usually investigated. Furthermore,...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9139967/ |
| _version_ | 1818727501164183552 |
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| author | Tao Liu Qidong Li Qiaoling Tong Qiao Zhang Kan Liu |
| author_facet | Tao Liu Qidong Li Qiaoling Tong Qiao Zhang Kan Liu |
| author_sort | Tao Liu |
| collection | DOAJ |
| description | In motor drives, distortions of phase voltages and currents are often caused by nonlinear effects of inverters such as dead time, turn-on delay, turn-off delay and voltage drop of power devices. To eliminate these distortions, the dead-time compensation voltage is usually investigated. Furthermore, the relationship between the dead-time compensation voltage and phase currents is nonlinear, which is related to not only the parameters mentioned above, but also the snubber and parasitic capacitance of inverters. A nonlinear function is constructed to model the nonlinear relationship in this paper. To identify the nonlinear function, a method based on artificial neural networks is proposed without inverter parameters. According to the criterion that the trajectory of voltage vector in α-β coordinate system is a circle, an adaptive law is constructed to modify the parameters of the nonlinear function. Therefore, the nonlinear dead-time compensation voltage model is obtained accurately, where the distortions of voltages and currents are reduced without any additional hardware. Applying this method to the current predictive control, the bandwidth of a current loop is increased by 500Hz. Effectiveness of the method is verified by experiments. |
| first_indexed | 2024-12-17T22:15:06Z |
| format | Article |
| id | doaj.art-5824d2ad7d964f75bb5e4459d2f759b1 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-17T22:15:06Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-5824d2ad7d964f75bb5e4459d2f759b12022-12-21T21:30:38ZengIEEEIEEE Access2169-35362020-01-01812999213000210.1109/ACCESS.2020.30092679139967An Adaptive Strategy to Compensate Nonlinear Effects of Voltage Source Inverters Based on Artificial Neural NetworksTao Liu0Qidong Li1Qiaoling Tong2https://orcid.org/0000-0002-9888-0426Qiao Zhang3Kan Liu4https://orcid.org/0000-0002-3998-7194School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Automation, Wuhan University of Technology, Wuhan, ChinaCollege of Mechanical and Vehicle Engineering, Hunan University, Changsha, ChinaIn motor drives, distortions of phase voltages and currents are often caused by nonlinear effects of inverters such as dead time, turn-on delay, turn-off delay and voltage drop of power devices. To eliminate these distortions, the dead-time compensation voltage is usually investigated. Furthermore, the relationship between the dead-time compensation voltage and phase currents is nonlinear, which is related to not only the parameters mentioned above, but also the snubber and parasitic capacitance of inverters. A nonlinear function is constructed to model the nonlinear relationship in this paper. To identify the nonlinear function, a method based on artificial neural networks is proposed without inverter parameters. According to the criterion that the trajectory of voltage vector in α-β coordinate system is a circle, an adaptive law is constructed to modify the parameters of the nonlinear function. Therefore, the nonlinear dead-time compensation voltage model is obtained accurately, where the distortions of voltages and currents are reduced without any additional hardware. Applying this method to the current predictive control, the bandwidth of a current loop is increased by 500Hz. Effectiveness of the method is verified by experiments.https://ieeexplore.ieee.org/document/9139967/Inverter nonlinear effectsartificial neural networknonlinear dead-time compensation model |
| spellingShingle | Tao Liu Qidong Li Qiaoling Tong Qiao Zhang Kan Liu An Adaptive Strategy to Compensate Nonlinear Effects of Voltage Source Inverters Based on Artificial Neural Networks IEEE Access Inverter nonlinear effects artificial neural network nonlinear dead-time compensation model |
| title | An Adaptive Strategy to Compensate Nonlinear Effects of Voltage Source Inverters Based on Artificial Neural Networks |
| title_full | An Adaptive Strategy to Compensate Nonlinear Effects of Voltage Source Inverters Based on Artificial Neural Networks |
| title_fullStr | An Adaptive Strategy to Compensate Nonlinear Effects of Voltage Source Inverters Based on Artificial Neural Networks |
| title_full_unstemmed | An Adaptive Strategy to Compensate Nonlinear Effects of Voltage Source Inverters Based on Artificial Neural Networks |
| title_short | An Adaptive Strategy to Compensate Nonlinear Effects of Voltage Source Inverters Based on Artificial Neural Networks |
| title_sort | adaptive strategy to compensate nonlinear effects of voltage source inverters based on artificial neural networks |
| topic | Inverter nonlinear effects artificial neural network nonlinear dead-time compensation model |
| url | https://ieeexplore.ieee.org/document/9139967/ |
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