LAPSE:2023.31236
Published Article

LAPSE:2023.31236
Advanced Torque Ripple Minimization of Synchronous Reluctance Machine for Electric Vehicle Application
April 18, 2023
Abstract
The electric machine and the control system determine the performance of the electric vehicle drivetrain. Unlike rare-earth magnet machines such as permanent magnet synchronous machines (PMSMs), synchronous reluctance machines(SynRMs) are manufactured without permanent magnets. This allows them to be used as an alternative to rare-earth magnet machines. However, one of the main drawbacks of this machine is its high torque ripple, which generates significant acoustic noise. The most typical method for reducing this torque ripple is to employ an optimized structural design or a customized control technique. The objective of this paper is the use of a control approach to minimize the torque ripple effects issue in the SynRM. This work is performed in two steps: Initially, the reference current calculation bloc is modified to reduce the torque ripple of the machine. A method for calculating the optimal reference currents based on the stator joule loss is proposed. The proposed method is compared to two methods used in the literature, the FOC and MTPA methods. A comparative study between the three methods based on the torque ripple rate shows that the proposed method allows a significant reduction in the torque ripple. The second contribution to the minimization of the torque ripple is to propose a sliding mode control. This control suffers from the phenomenon of “Chattering” which affects the torque ripple. To solve this problem, a second-order sliding mode control is proposed. A comparative study between the different approaches shows that the second-order sliding mode provides the lowest torque ripple rate of the machine.
The electric machine and the control system determine the performance of the electric vehicle drivetrain. Unlike rare-earth magnet machines such as permanent magnet synchronous machines (PMSMs), synchronous reluctance machines(SynRMs) are manufactured without permanent magnets. This allows them to be used as an alternative to rare-earth magnet machines. However, one of the main drawbacks of this machine is its high torque ripple, which generates significant acoustic noise. The most typical method for reducing this torque ripple is to employ an optimized structural design or a customized control technique. The objective of this paper is the use of a control approach to minimize the torque ripple effects issue in the SynRM. This work is performed in two steps: Initially, the reference current calculation bloc is modified to reduce the torque ripple of the machine. A method for calculating the optimal reference currents based on the stator joule loss is proposed. The proposed method is compared to two methods used in the literature, the FOC and MTPA methods. A comparative study between the three methods based on the torque ripple rate shows that the proposed method allows a significant reduction in the torque ripple. The second contribution to the minimization of the torque ripple is to propose a sliding mode control. This control suffers from the phenomenon of “Chattering” which affects the torque ripple. To solve this problem, a second-order sliding mode control is proposed. A comparative study between the different approaches shows that the second-order sliding mode provides the lowest torque ripple rate of the machine.
Record ID
Keywords
electric vehicle, field-oriented control, maximum torque per ampere, optimal current calculation, sliding mode control, synchronous reluctance machine, torque ripple minimization
Subject
Suggested Citation
Aladetola OD, Ouari M, Saadi Y, Mesbahi T, Boukhnifer M, Adjallah KH. Advanced Torque Ripple Minimization of Synchronous Reluctance Machine for Electric Vehicle Application. (2023). LAPSE:2023.31236
Author Affiliations
Aladetola OD: Laboratoire de Conception, Optimisation et Modélisation des Systèmes, Université de Lorraine, 57000 Metz, France [ORCID]
Ouari M: Laboratoire de Conception, Optimisation et Modélisation des Systèmes, Université de Lorraine, 57000 Metz, France
Saadi Y: ICube, CNRS (UMR 7357) INSA Strasbourg, University of Strasbourg, 67000 Strasbourg, France
Mesbahi T: ICube, CNRS (UMR 7357) INSA Strasbourg, University of Strasbourg, 67000 Strasbourg, France [ORCID]
Boukhnifer M: Université de Lorraine, LCOMS, 57000 Metz, France [ORCID]
Adjallah KH: Laboratoire de Conception, Optimisation et Modélisation des Systèmes, Université de Lorraine, 57000 Metz, France [ORCID]
Ouari M: Laboratoire de Conception, Optimisation et Modélisation des Systèmes, Université de Lorraine, 57000 Metz, France
Saadi Y: ICube, CNRS (UMR 7357) INSA Strasbourg, University of Strasbourg, 67000 Strasbourg, France
Mesbahi T: ICube, CNRS (UMR 7357) INSA Strasbourg, University of Strasbourg, 67000 Strasbourg, France [ORCID]
Boukhnifer M: Université de Lorraine, LCOMS, 57000 Metz, France [ORCID]
Adjallah KH: Laboratoire de Conception, Optimisation et Modélisation des Systèmes, Université de Lorraine, 57000 Metz, France [ORCID]
Journal Name
Energies
Volume
16
Issue
6
First Page
2701
Year
2023
Publication Date
2023-03-14
ISSN
1996-1073
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Original Submission
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PII: en16062701, Publication Type: Journal Article
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LAPSE:2023.31236
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https://doi.org/10.3390/en16062701
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