Enhanced Direct Torque Control Prediction for Torque Ripple Reduction in Switched Reluctance Motors.
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| Title: | Enhanced Direct Torque Control Prediction for Torque Ripple Reduction in Switched Reluctance Motors. |
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| Authors: | Jiang, Meiguang1,2 (AUTHOR), Li, Chuanwei2,3 (AUTHOR), Lv, Xiangwen1,2,3 (AUTHOR) xw_lv@chinalco.com.cn, Liu, Cheng4 (AUTHOR) |
| Source: | Energies (19961073). Apr2026, Vol. 19 Issue 8, p1840. 16p. |
| Subject Terms: | *Switched reluctance motors, *Torque control, *Hysteresis, *Predictive control systems, *Frequency changers, *Energy conversion |
| Abstract: | In this study, a novel direct torque control (DTC) strategy is proposed to mitigate the torque ripple issue inherent in switched reluctance motors (SRMs), which is caused by the double salient pole configuration and the pulse power supply mode. The strategy is based on the prediction and optimization of a long-time-domain model. Central to this method is the development of a multi-step predictive optimization framework. By incorporating hysteresis control, the conventional approach of minimizing instantaneous error in predictive control is shifted towards minimizing tracking error over an extended time frame. A dual-objective evaluation function is also introduced, which simultaneously optimizes both torque smoothness and switching frequency, ensuring their collaborative enhancement. To validate the proposed method, a 6/4-pole SRM simulation model was implemented using MATLAB/Simulink 2024B, and comparisons were made with traditional methods. The results demonstrate that this strategy significantly reduces torque pulsation and lowers the system's switching frequency, even under varying operational conditions such as different rotational speeds and sudden load variations. Consequently, this approach not only guarantees improved dynamic performance but also enhances the motor's efficiency and stability. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: enr DbLabel: Energy & Power Source An: 193438180 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Enhanced Direct Torque Control Prediction for Torque Ripple Reduction in Switched Reluctance Motors. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Jiang%2C+Meiguang%22">Jiang, Meiguang</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Chuanwei%22">Li, Chuanwei</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lv%2C+Xiangwen%22">Lv, Xiangwen</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> xw_lv@chinalco.com.cn</i><br /><searchLink fieldCode="AR" term="%22Liu%2C+Cheng%22">Liu, Cheng</searchLink><relatesTo>4</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. Apr2026, Vol. 19 Issue 8, p1840. 16p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Switched+reluctance+motors%22">Switched reluctance motors</searchLink><br />*<searchLink fieldCode="DE" term="%22Torque+control%22">Torque control</searchLink><br />*<searchLink fieldCode="DE" term="%22Hysteresis%22">Hysteresis</searchLink><br />*<searchLink fieldCode="DE" term="%22Predictive+control+systems%22">Predictive control systems</searchLink><br />*<searchLink fieldCode="DE" term="%22Frequency+changers%22">Frequency changers</searchLink><br />*<searchLink fieldCode="DE" term="%22Energy+conversion%22">Energy conversion</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In this study, a novel direct torque control (DTC) strategy is proposed to mitigate the torque ripple issue inherent in switched reluctance motors (SRMs), which is caused by the double salient pole configuration and the pulse power supply mode. The strategy is based on the prediction and optimization of a long-time-domain model. Central to this method is the development of a multi-step predictive optimization framework. By incorporating hysteresis control, the conventional approach of minimizing instantaneous error in predictive control is shifted towards minimizing tracking error over an extended time frame. A dual-objective evaluation function is also introduced, which simultaneously optimizes both torque smoothness and switching frequency, ensuring their collaborative enhancement. To validate the proposed method, a 6/4-pole SRM simulation model was implemented using MATLAB/Simulink 2024B, and comparisons were made with traditional methods. The results demonstrate that this strategy significantly reduces torque pulsation and lowers the system's switching frequency, even under varying operational conditions such as different rotational speeds and sudden load variations. Consequently, this approach not only guarantees improved dynamic performance but also enhances the motor's efficiency and stability. [ABSTRACT FROM AUTHOR] |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=193438180 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/en19081840 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 16 StartPage: 1840 Subjects: – SubjectFull: Switched reluctance motors Type: general – SubjectFull: Torque control Type: general – SubjectFull: Hysteresis Type: general – SubjectFull: Predictive control systems Type: general – SubjectFull: Frequency changers Type: general – SubjectFull: Energy conversion Type: general Titles: – TitleFull: Enhanced Direct Torque Control Prediction for Torque Ripple Reduction in Switched Reluctance Motors. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Jiang, Meiguang – PersonEntity: Name: NameFull: Li, Chuanwei – PersonEntity: Name: NameFull: Lv, Xiangwen – PersonEntity: Name: NameFull: Liu, Cheng IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 04 Text: Apr2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 19961073 Numbering: – Type: volume Value: 19 – Type: issue Value: 8 Titles: – TitleFull: Energies (19961073) Type: main |
| ResultId | 1 |
