Analyzing modeled configuration using finite element analysis for performance prediction of LSRM
Abstract Due to high precision, high speed, and high fault tolerance capability, the linear switched reluctance motor (LSRM) is applied in digital control technologies as well as electronic switching devices. The LSRM is considered as a good substitute for conventional linear drive systems for long-...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Murty, V. Shirish [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
Linear switched reluctance motor |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Übergeordnetes Werk: |
Enthalten in: Neural computing & applications - London : Springer, 1993, 34(2022), 23 vom: 11. Aug., Seite 21175-21189 |
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| Übergeordnetes Werk: |
volume:34 ; year:2022 ; number:23 ; day:11 ; month:08 ; pages:21175-21189 |
| Links: |
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| DOI / URN: |
10.1007/s00521-022-07598-3 |
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| Katalog-ID: |
SPR048551805 |
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| 520 | |a Abstract Due to high precision, high speed, and high fault tolerance capability, the linear switched reluctance motor (LSRM) is applied in digital control technologies as well as electronic switching devices. The LSRM is considered as a good substitute for conventional linear drive systems for long-way transportation. In this paper, a single-stator and double-stator longitudinal flux-type LSRM for high-speed transit system is proposed. Since the flux in the longitudinal arrangement is in the same alignment as the motion of the translator, the proposed system is easier to construct, mechanically stable with minimum eddy current loss. It also produces the magnetic flux along the direction of motion, which makes it highly suitable for high-speed linear transit application. The proposed conceptual LSRM differs from the conventional LSRM, in such a way that the active stator holds the excitation windings, while at the same time it acts as a translational body that moves over the stationary translator bed. The motor characterization is performed in ANSYS electromagnetic simulation tool, to determine the applied forces, coupling inductance, and strength of the magnetic field of the proposed LSRM for the traction propulsion system. The finite element analysis (FEA) is utilized here to analyze the modeled configuration, for verification of the design and performance prediction of the proposed LSRM. | ||
| 650 | 4 | |a Linear switched reluctance motor |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Finite element analysis |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Transit system |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Rotating switched reluctance motor |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Active stator passive translator |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Jain, Shailendra |4 aut | |
| 700 | 1 | |a Ojha, Amit |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Neural computing & applications |d London : Springer, 1993 |g 34(2022), 23 vom: 11. Aug., Seite 21175-21189 |w (DE-627)271595574 |w (DE-600)1480526-1 |x 1433-3058 |7 nnns |
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10.1007/s00521-022-07598-3 doi (DE-627)SPR048551805 (SPR)s00521-022-07598-3-e DE-627 ger DE-627 rakwb eng Murty, V. Shirish verfasserin aut Analyzing modeled configuration using finite element analysis for performance prediction of LSRM 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Due to high precision, high speed, and high fault tolerance capability, the linear switched reluctance motor (LSRM) is applied in digital control technologies as well as electronic switching devices. The LSRM is considered as a good substitute for conventional linear drive systems for long-way transportation. In this paper, a single-stator and double-stator longitudinal flux-type LSRM for high-speed transit system is proposed. Since the flux in the longitudinal arrangement is in the same alignment as the motion of the translator, the proposed system is easier to construct, mechanically stable with minimum eddy current loss. It also produces the magnetic flux along the direction of motion, which makes it highly suitable for high-speed linear transit application. The proposed conceptual LSRM differs from the conventional LSRM, in such a way that the active stator holds the excitation windings, while at the same time it acts as a translational body that moves over the stationary translator bed. The motor characterization is performed in ANSYS electromagnetic simulation tool, to determine the applied forces, coupling inductance, and strength of the magnetic field of the proposed LSRM for the traction propulsion system. The finite element analysis (FEA) is utilized here to analyze the modeled configuration, for verification of the design and performance prediction of the proposed LSRM. Linear switched reluctance motor (dpeaa)DE-He213 Finite element analysis (dpeaa)DE-He213 Transit system (dpeaa)DE-He213 Rotating switched reluctance motor (dpeaa)DE-He213 Active stator passive translator (dpeaa)DE-He213 Jain, Shailendra aut Ojha, Amit aut Enthalten in Neural computing & applications London : Springer, 1993 34(2022), 23 vom: 11. Aug., Seite 21175-21189 (DE-627)271595574 (DE-600)1480526-1 1433-3058 nnns volume:34 year:2022 number:23 day:11 month:08 pages:21175-21189 https://dx.doi.org/10.1007/s00521-022-07598-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 34 2022 23 11 08 21175-21189 |
| spelling |
10.1007/s00521-022-07598-3 doi (DE-627)SPR048551805 (SPR)s00521-022-07598-3-e DE-627 ger DE-627 rakwb eng Murty, V. Shirish verfasserin aut Analyzing modeled configuration using finite element analysis for performance prediction of LSRM 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Due to high precision, high speed, and high fault tolerance capability, the linear switched reluctance motor (LSRM) is applied in digital control technologies as well as electronic switching devices. The LSRM is considered as a good substitute for conventional linear drive systems for long-way transportation. In this paper, a single-stator and double-stator longitudinal flux-type LSRM for high-speed transit system is proposed. Since the flux in the longitudinal arrangement is in the same alignment as the motion of the translator, the proposed system is easier to construct, mechanically stable with minimum eddy current loss. It also produces the magnetic flux along the direction of motion, which makes it highly suitable for high-speed linear transit application. The proposed conceptual LSRM differs from the conventional LSRM, in such a way that the active stator holds the excitation windings, while at the same time it acts as a translational body that moves over the stationary translator bed. The motor characterization is performed in ANSYS electromagnetic simulation tool, to determine the applied forces, coupling inductance, and strength of the magnetic field of the proposed LSRM for the traction propulsion system. The finite element analysis (FEA) is utilized here to analyze the modeled configuration, for verification of the design and performance prediction of the proposed LSRM. Linear switched reluctance motor (dpeaa)DE-He213 Finite element analysis (dpeaa)DE-He213 Transit system (dpeaa)DE-He213 Rotating switched reluctance motor (dpeaa)DE-He213 Active stator passive translator (dpeaa)DE-He213 Jain, Shailendra aut Ojha, Amit aut Enthalten in Neural computing & applications London : Springer, 1993 34(2022), 23 vom: 11. Aug., Seite 21175-21189 (DE-627)271595574 (DE-600)1480526-1 1433-3058 nnns volume:34 year:2022 number:23 day:11 month:08 pages:21175-21189 https://dx.doi.org/10.1007/s00521-022-07598-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 34 2022 23 11 08 21175-21189 |
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10.1007/s00521-022-07598-3 doi (DE-627)SPR048551805 (SPR)s00521-022-07598-3-e DE-627 ger DE-627 rakwb eng Murty, V. Shirish verfasserin aut Analyzing modeled configuration using finite element analysis for performance prediction of LSRM 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Due to high precision, high speed, and high fault tolerance capability, the linear switched reluctance motor (LSRM) is applied in digital control technologies as well as electronic switching devices. The LSRM is considered as a good substitute for conventional linear drive systems for long-way transportation. In this paper, a single-stator and double-stator longitudinal flux-type LSRM for high-speed transit system is proposed. Since the flux in the longitudinal arrangement is in the same alignment as the motion of the translator, the proposed system is easier to construct, mechanically stable with minimum eddy current loss. It also produces the magnetic flux along the direction of motion, which makes it highly suitable for high-speed linear transit application. The proposed conceptual LSRM differs from the conventional LSRM, in such a way that the active stator holds the excitation windings, while at the same time it acts as a translational body that moves over the stationary translator bed. The motor characterization is performed in ANSYS electromagnetic simulation tool, to determine the applied forces, coupling inductance, and strength of the magnetic field of the proposed LSRM for the traction propulsion system. The finite element analysis (FEA) is utilized here to analyze the modeled configuration, for verification of the design and performance prediction of the proposed LSRM. Linear switched reluctance motor (dpeaa)DE-He213 Finite element analysis (dpeaa)DE-He213 Transit system (dpeaa)DE-He213 Rotating switched reluctance motor (dpeaa)DE-He213 Active stator passive translator (dpeaa)DE-He213 Jain, Shailendra aut Ojha, Amit aut Enthalten in Neural computing & applications London : Springer, 1993 34(2022), 23 vom: 11. Aug., Seite 21175-21189 (DE-627)271595574 (DE-600)1480526-1 1433-3058 nnns volume:34 year:2022 number:23 day:11 month:08 pages:21175-21189 https://dx.doi.org/10.1007/s00521-022-07598-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 34 2022 23 11 08 21175-21189 |
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10.1007/s00521-022-07598-3 doi (DE-627)SPR048551805 (SPR)s00521-022-07598-3-e DE-627 ger DE-627 rakwb eng Murty, V. Shirish verfasserin aut Analyzing modeled configuration using finite element analysis for performance prediction of LSRM 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Due to high precision, high speed, and high fault tolerance capability, the linear switched reluctance motor (LSRM) is applied in digital control technologies as well as electronic switching devices. The LSRM is considered as a good substitute for conventional linear drive systems for long-way transportation. In this paper, a single-stator and double-stator longitudinal flux-type LSRM for high-speed transit system is proposed. Since the flux in the longitudinal arrangement is in the same alignment as the motion of the translator, the proposed system is easier to construct, mechanically stable with minimum eddy current loss. It also produces the magnetic flux along the direction of motion, which makes it highly suitable for high-speed linear transit application. The proposed conceptual LSRM differs from the conventional LSRM, in such a way that the active stator holds the excitation windings, while at the same time it acts as a translational body that moves over the stationary translator bed. The motor characterization is performed in ANSYS electromagnetic simulation tool, to determine the applied forces, coupling inductance, and strength of the magnetic field of the proposed LSRM for the traction propulsion system. The finite element analysis (FEA) is utilized here to analyze the modeled configuration, for verification of the design and performance prediction of the proposed LSRM. Linear switched reluctance motor (dpeaa)DE-He213 Finite element analysis (dpeaa)DE-He213 Transit system (dpeaa)DE-He213 Rotating switched reluctance motor (dpeaa)DE-He213 Active stator passive translator (dpeaa)DE-He213 Jain, Shailendra aut Ojha, Amit aut Enthalten in Neural computing & applications London : Springer, 1993 34(2022), 23 vom: 11. Aug., Seite 21175-21189 (DE-627)271595574 (DE-600)1480526-1 1433-3058 nnns volume:34 year:2022 number:23 day:11 month:08 pages:21175-21189 https://dx.doi.org/10.1007/s00521-022-07598-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 34 2022 23 11 08 21175-21189 |
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10.1007/s00521-022-07598-3 doi (DE-627)SPR048551805 (SPR)s00521-022-07598-3-e DE-627 ger DE-627 rakwb eng Murty, V. Shirish verfasserin aut Analyzing modeled configuration using finite element analysis for performance prediction of LSRM 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Due to high precision, high speed, and high fault tolerance capability, the linear switched reluctance motor (LSRM) is applied in digital control technologies as well as electronic switching devices. The LSRM is considered as a good substitute for conventional linear drive systems for long-way transportation. In this paper, a single-stator and double-stator longitudinal flux-type LSRM for high-speed transit system is proposed. Since the flux in the longitudinal arrangement is in the same alignment as the motion of the translator, the proposed system is easier to construct, mechanically stable with minimum eddy current loss. It also produces the magnetic flux along the direction of motion, which makes it highly suitable for high-speed linear transit application. The proposed conceptual LSRM differs from the conventional LSRM, in such a way that the active stator holds the excitation windings, while at the same time it acts as a translational body that moves over the stationary translator bed. The motor characterization is performed in ANSYS electromagnetic simulation tool, to determine the applied forces, coupling inductance, and strength of the magnetic field of the proposed LSRM for the traction propulsion system. The finite element analysis (FEA) is utilized here to analyze the modeled configuration, for verification of the design and performance prediction of the proposed LSRM. Linear switched reluctance motor (dpeaa)DE-He213 Finite element analysis (dpeaa)DE-He213 Transit system (dpeaa)DE-He213 Rotating switched reluctance motor (dpeaa)DE-He213 Active stator passive translator (dpeaa)DE-He213 Jain, Shailendra aut Ojha, Amit aut Enthalten in Neural computing & applications London : Springer, 1993 34(2022), 23 vom: 11. Aug., Seite 21175-21189 (DE-627)271595574 (DE-600)1480526-1 1433-3058 nnns volume:34 year:2022 number:23 day:11 month:08 pages:21175-21189 https://dx.doi.org/10.1007/s00521-022-07598-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 34 2022 23 11 08 21175-21189 |
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Shirish</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Analyzing modeled configuration using finite element analysis for performance prediction of LSRM</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Due to high precision, high speed, and high fault tolerance capability, the linear switched reluctance motor (LSRM) is applied in digital control technologies as well as electronic switching devices. The LSRM is considered as a good substitute for conventional linear drive systems for long-way transportation. In this paper, a single-stator and double-stator longitudinal flux-type LSRM for high-speed transit system is proposed. Since the flux in the longitudinal arrangement is in the same alignment as the motion of the translator, the proposed system is easier to construct, mechanically stable with minimum eddy current loss. It also produces the magnetic flux along the direction of motion, which makes it highly suitable for high-speed linear transit application. The proposed conceptual LSRM differs from the conventional LSRM, in such a way that the active stator holds the excitation windings, while at the same time it acts as a translational body that moves over the stationary translator bed. The motor characterization is performed in ANSYS electromagnetic simulation tool, to determine the applied forces, coupling inductance, and strength of the magnetic field of the proposed LSRM for the traction propulsion system. 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Murty, V. Shirish |
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Murty, V. Shirish misc Linear switched reluctance motor misc Finite element analysis misc Transit system misc Rotating switched reluctance motor misc Active stator passive translator Analyzing modeled configuration using finite element analysis for performance prediction of LSRM |
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Analyzing modeled configuration using finite element analysis for performance prediction of LSRM Linear switched reluctance motor (dpeaa)DE-He213 Finite element analysis (dpeaa)DE-He213 Transit system (dpeaa)DE-He213 Rotating switched reluctance motor (dpeaa)DE-He213 Active stator passive translator (dpeaa)DE-He213 |
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analyzing modeled configuration using finite element analysis for performance prediction of lsrm |
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Analyzing modeled configuration using finite element analysis for performance prediction of LSRM |
| abstract |
Abstract Due to high precision, high speed, and high fault tolerance capability, the linear switched reluctance motor (LSRM) is applied in digital control technologies as well as electronic switching devices. The LSRM is considered as a good substitute for conventional linear drive systems for long-way transportation. In this paper, a single-stator and double-stator longitudinal flux-type LSRM for high-speed transit system is proposed. Since the flux in the longitudinal arrangement is in the same alignment as the motion of the translator, the proposed system is easier to construct, mechanically stable with minimum eddy current loss. It also produces the magnetic flux along the direction of motion, which makes it highly suitable for high-speed linear transit application. The proposed conceptual LSRM differs from the conventional LSRM, in such a way that the active stator holds the excitation windings, while at the same time it acts as a translational body that moves over the stationary translator bed. The motor characterization is performed in ANSYS electromagnetic simulation tool, to determine the applied forces, coupling inductance, and strength of the magnetic field of the proposed LSRM for the traction propulsion system. The finite element analysis (FEA) is utilized here to analyze the modeled configuration, for verification of the design and performance prediction of the proposed LSRM. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstractGer |
Abstract Due to high precision, high speed, and high fault tolerance capability, the linear switched reluctance motor (LSRM) is applied in digital control technologies as well as electronic switching devices. The LSRM is considered as a good substitute for conventional linear drive systems for long-way transportation. In this paper, a single-stator and double-stator longitudinal flux-type LSRM for high-speed transit system is proposed. Since the flux in the longitudinal arrangement is in the same alignment as the motion of the translator, the proposed system is easier to construct, mechanically stable with minimum eddy current loss. It also produces the magnetic flux along the direction of motion, which makes it highly suitable for high-speed linear transit application. The proposed conceptual LSRM differs from the conventional LSRM, in such a way that the active stator holds the excitation windings, while at the same time it acts as a translational body that moves over the stationary translator bed. The motor characterization is performed in ANSYS electromagnetic simulation tool, to determine the applied forces, coupling inductance, and strength of the magnetic field of the proposed LSRM for the traction propulsion system. The finite element analysis (FEA) is utilized here to analyze the modeled configuration, for verification of the design and performance prediction of the proposed LSRM. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstract_unstemmed |
Abstract Due to high precision, high speed, and high fault tolerance capability, the linear switched reluctance motor (LSRM) is applied in digital control technologies as well as electronic switching devices. The LSRM is considered as a good substitute for conventional linear drive systems for long-way transportation. In this paper, a single-stator and double-stator longitudinal flux-type LSRM for high-speed transit system is proposed. Since the flux in the longitudinal arrangement is in the same alignment as the motion of the translator, the proposed system is easier to construct, mechanically stable with minimum eddy current loss. It also produces the magnetic flux along the direction of motion, which makes it highly suitable for high-speed linear transit application. The proposed conceptual LSRM differs from the conventional LSRM, in such a way that the active stator holds the excitation windings, while at the same time it acts as a translational body that moves over the stationary translator bed. The motor characterization is performed in ANSYS electromagnetic simulation tool, to determine the applied forces, coupling inductance, and strength of the magnetic field of the proposed LSRM for the traction propulsion system. The finite element analysis (FEA) is utilized here to analyze the modeled configuration, for verification of the design and performance prediction of the proposed LSRM. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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Analyzing modeled configuration using finite element analysis for performance prediction of LSRM |
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https://dx.doi.org/10.1007/s00521-022-07598-3 |
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Jain, Shailendra Ojha, Amit |
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10.1007/s00521-022-07598-3 |
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| score |
7.4016886 |