Research on train braking model by improved Polach model considering wheel‐rail adhesion characteristics

Abstract To study the braking process of the train under different adhesion conditions, this paper takes the braking system of a single rail vehicle as the research object. The author establishes a corresponding co‐simulation platform based on MATLAB/Simulink and AMESim, including the sub‐models of...
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Autor*in:	Peiwen Chen [verfasserIn] Wenliang Zhu [verfasserIn] Chaogang Yu [verfasserIn] Ningyuan Sun [verfasserIn] Wenshen Xue [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	brakes braking railway rolling stock simulation vehicle dynamics and control

Übergeordnetes Werk:	In: IET Intelligent Transport Systems - Wiley, 2021, 17(2023), 12, Seite 2432-2443
Übergeordnetes Werk:	volume:17 ; year:2023 ; number:12 ; pages:2432-2443

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.1049/itr2.12422

Katalog-ID:	DOAJ099400197

Internformat


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520			\|a Abstract To study the braking process of the train under different adhesion conditions, this paper takes the braking system of a single rail vehicle as the research object. The author establishes a corresponding co‐simulation platform based on MATLAB/Simulink and AMESim, including the sub‐models of braking control, vehicle brake longitudinal dynamics and air brake unit. Considering the cleaning effect caused by large sliding, the author builds a suitable adhesion model for different adhesion conditions based on the improved Polach model, which is the input of the vehicle braking longitudinal dynamics sub‐model. Based on the finite state machine, the anti‐skid control algorithm of the train is constructed as the core of the brake control sub‐model, which can judge the motion state of the wheelset, and control the stage release and hold of the brake cylinder pressure. According to the International Standard EN15595 and the actual operating parameters of a certain type of train, the braking process of the train under dry and wet rail conditions is simulated on the platform. The validity of the model is verified, which provides a reliable method for future research on the braking process.
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allfields	10.1049/itr2.12422 doi (DE-627)DOAJ099400197 (DE-599)DOAJ57d30d43eca44dd78f5975604b5f724d DE-627 ger DE-627 rakwb eng TA1001-1280 QA75.5-76.95 Peiwen Chen verfasserin aut Research on train braking model by improved Polach model considering wheel‐rail adhesion characteristics 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract To study the braking process of the train under different adhesion conditions, this paper takes the braking system of a single rail vehicle as the research object. The author establishes a corresponding co‐simulation platform based on MATLAB/Simulink and AMESim, including the sub‐models of braking control, vehicle brake longitudinal dynamics and air brake unit. Considering the cleaning effect caused by large sliding, the author builds a suitable adhesion model for different adhesion conditions based on the improved Polach model, which is the input of the vehicle braking longitudinal dynamics sub‐model. Based on the finite state machine, the anti‐skid control algorithm of the train is constructed as the core of the brake control sub‐model, which can judge the motion state of the wheelset, and control the stage release and hold of the brake cylinder pressure. According to the International Standard EN15595 and the actual operating parameters of a certain type of train, the braking process of the train under dry and wet rail conditions is simulated on the platform. The validity of the model is verified, which provides a reliable method for future research on the braking process. brakes braking railway rolling stock simulation vehicle dynamics and control Transportation engineering Electronic computers. Computer science Wenliang Zhu verfasserin aut Chaogang Yu verfasserin aut Ningyuan Sun verfasserin aut Wenshen Xue verfasserin aut In IET Intelligent Transport Systems Wiley, 2021 17(2023), 12, Seite 2432-2443 (DE-627)521693659 (DE-600)2264527-5 17519578 nnns volume:17 year:2023 number:12 pages:2432-2443 https://doi.org/10.1049/itr2.12422 kostenfrei https://doaj.org/article/57d30d43eca44dd78f5975604b5f724d kostenfrei https://doi.org/10.1049/itr2.12422 kostenfrei https://doaj.org/toc/1751-956X Journal toc kostenfrei https://doaj.org/toc/1751-9578 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 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_2034 GBV_ILN_2037 GBV_ILN_2038 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_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 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_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 17 2023 12 2432-2443
spelling	10.1049/itr2.12422 doi (DE-627)DOAJ099400197 (DE-599)DOAJ57d30d43eca44dd78f5975604b5f724d DE-627 ger DE-627 rakwb eng TA1001-1280 QA75.5-76.95 Peiwen Chen verfasserin aut Research on train braking model by improved Polach model considering wheel‐rail adhesion characteristics 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract To study the braking process of the train under different adhesion conditions, this paper takes the braking system of a single rail vehicle as the research object. The author establishes a corresponding co‐simulation platform based on MATLAB/Simulink and AMESim, including the sub‐models of braking control, vehicle brake longitudinal dynamics and air brake unit. Considering the cleaning effect caused by large sliding, the author builds a suitable adhesion model for different adhesion conditions based on the improved Polach model, which is the input of the vehicle braking longitudinal dynamics sub‐model. Based on the finite state machine, the anti‐skid control algorithm of the train is constructed as the core of the brake control sub‐model, which can judge the motion state of the wheelset, and control the stage release and hold of the brake cylinder pressure. According to the International Standard EN15595 and the actual operating parameters of a certain type of train, the braking process of the train under dry and wet rail conditions is simulated on the platform. The validity of the model is verified, which provides a reliable method for future research on the braking process. brakes braking railway rolling stock simulation vehicle dynamics and control Transportation engineering Electronic computers. Computer science Wenliang Zhu verfasserin aut Chaogang Yu verfasserin aut Ningyuan Sun verfasserin aut Wenshen Xue verfasserin aut In IET Intelligent Transport Systems Wiley, 2021 17(2023), 12, Seite 2432-2443 (DE-627)521693659 (DE-600)2264527-5 17519578 nnns volume:17 year:2023 number:12 pages:2432-2443 https://doi.org/10.1049/itr2.12422 kostenfrei https://doaj.org/article/57d30d43eca44dd78f5975604b5f724d kostenfrei https://doi.org/10.1049/itr2.12422 kostenfrei https://doaj.org/toc/1751-956X Journal toc kostenfrei https://doaj.org/toc/1751-9578 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 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_2034 GBV_ILN_2037 GBV_ILN_2038 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_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 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_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 17 2023 12 2432-2443
allfields_unstemmed	10.1049/itr2.12422 doi (DE-627)DOAJ099400197 (DE-599)DOAJ57d30d43eca44dd78f5975604b5f724d DE-627 ger DE-627 rakwb eng TA1001-1280 QA75.5-76.95 Peiwen Chen verfasserin aut Research on train braking model by improved Polach model considering wheel‐rail adhesion characteristics 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract To study the braking process of the train under different adhesion conditions, this paper takes the braking system of a single rail vehicle as the research object. The author establishes a corresponding co‐simulation platform based on MATLAB/Simulink and AMESim, including the sub‐models of braking control, vehicle brake longitudinal dynamics and air brake unit. Considering the cleaning effect caused by large sliding, the author builds a suitable adhesion model for different adhesion conditions based on the improved Polach model, which is the input of the vehicle braking longitudinal dynamics sub‐model. Based on the finite state machine, the anti‐skid control algorithm of the train is constructed as the core of the brake control sub‐model, which can judge the motion state of the wheelset, and control the stage release and hold of the brake cylinder pressure. According to the International Standard EN15595 and the actual operating parameters of a certain type of train, the braking process of the train under dry and wet rail conditions is simulated on the platform. The validity of the model is verified, which provides a reliable method for future research on the braking process. brakes braking railway rolling stock simulation vehicle dynamics and control Transportation engineering Electronic computers. Computer science Wenliang Zhu verfasserin aut Chaogang Yu verfasserin aut Ningyuan Sun verfasserin aut Wenshen Xue verfasserin aut In IET Intelligent Transport Systems Wiley, 2021 17(2023), 12, Seite 2432-2443 (DE-627)521693659 (DE-600)2264527-5 17519578 nnns volume:17 year:2023 number:12 pages:2432-2443 https://doi.org/10.1049/itr2.12422 kostenfrei https://doaj.org/article/57d30d43eca44dd78f5975604b5f724d kostenfrei https://doi.org/10.1049/itr2.12422 kostenfrei https://doaj.org/toc/1751-956X Journal toc kostenfrei https://doaj.org/toc/1751-9578 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 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_2034 GBV_ILN_2037 GBV_ILN_2038 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_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 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_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 17 2023 12 2432-2443
allfieldsGer	10.1049/itr2.12422 doi (DE-627)DOAJ099400197 (DE-599)DOAJ57d30d43eca44dd78f5975604b5f724d DE-627 ger DE-627 rakwb eng TA1001-1280 QA75.5-76.95 Peiwen Chen verfasserin aut Research on train braking model by improved Polach model considering wheel‐rail adhesion characteristics 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract To study the braking process of the train under different adhesion conditions, this paper takes the braking system of a single rail vehicle as the research object. The author establishes a corresponding co‐simulation platform based on MATLAB/Simulink and AMESim, including the sub‐models of braking control, vehicle brake longitudinal dynamics and air brake unit. Considering the cleaning effect caused by large sliding, the author builds a suitable adhesion model for different adhesion conditions based on the improved Polach model, which is the input of the vehicle braking longitudinal dynamics sub‐model. Based on the finite state machine, the anti‐skid control algorithm of the train is constructed as the core of the brake control sub‐model, which can judge the motion state of the wheelset, and control the stage release and hold of the brake cylinder pressure. According to the International Standard EN15595 and the actual operating parameters of a certain type of train, the braking process of the train under dry and wet rail conditions is simulated on the platform. The validity of the model is verified, which provides a reliable method for future research on the braking process. brakes braking railway rolling stock simulation vehicle dynamics and control Transportation engineering Electronic computers. Computer science Wenliang Zhu verfasserin aut Chaogang Yu verfasserin aut Ningyuan Sun verfasserin aut Wenshen Xue verfasserin aut In IET Intelligent Transport Systems Wiley, 2021 17(2023), 12, Seite 2432-2443 (DE-627)521693659 (DE-600)2264527-5 17519578 nnns volume:17 year:2023 number:12 pages:2432-2443 https://doi.org/10.1049/itr2.12422 kostenfrei https://doaj.org/article/57d30d43eca44dd78f5975604b5f724d kostenfrei https://doi.org/10.1049/itr2.12422 kostenfrei https://doaj.org/toc/1751-956X Journal toc kostenfrei https://doaj.org/toc/1751-9578 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 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_2034 GBV_ILN_2037 GBV_ILN_2038 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_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 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_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 17 2023 12 2432-2443
allfieldsSound	10.1049/itr2.12422 doi (DE-627)DOAJ099400197 (DE-599)DOAJ57d30d43eca44dd78f5975604b5f724d DE-627 ger DE-627 rakwb eng TA1001-1280 QA75.5-76.95 Peiwen Chen verfasserin aut Research on train braking model by improved Polach model considering wheel‐rail adhesion characteristics 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract To study the braking process of the train under different adhesion conditions, this paper takes the braking system of a single rail vehicle as the research object. The author establishes a corresponding co‐simulation platform based on MATLAB/Simulink and AMESim, including the sub‐models of braking control, vehicle brake longitudinal dynamics and air brake unit. Considering the cleaning effect caused by large sliding, the author builds a suitable adhesion model for different adhesion conditions based on the improved Polach model, which is the input of the vehicle braking longitudinal dynamics sub‐model. Based on the finite state machine, the anti‐skid control algorithm of the train is constructed as the core of the brake control sub‐model, which can judge the motion state of the wheelset, and control the stage release and hold of the brake cylinder pressure. According to the International Standard EN15595 and the actual operating parameters of a certain type of train, the braking process of the train under dry and wet rail conditions is simulated on the platform. The validity of the model is verified, which provides a reliable method for future research on the braking process. brakes braking railway rolling stock simulation vehicle dynamics and control Transportation engineering Electronic computers. Computer science Wenliang Zhu verfasserin aut Chaogang Yu verfasserin aut Ningyuan Sun verfasserin aut Wenshen Xue verfasserin aut In IET Intelligent Transport Systems Wiley, 2021 17(2023), 12, Seite 2432-2443 (DE-627)521693659 (DE-600)2264527-5 17519578 nnns volume:17 year:2023 number:12 pages:2432-2443 https://doi.org/10.1049/itr2.12422 kostenfrei https://doaj.org/article/57d30d43eca44dd78f5975604b5f724d kostenfrei https://doi.org/10.1049/itr2.12422 kostenfrei https://doaj.org/toc/1751-956X Journal toc kostenfrei https://doaj.org/toc/1751-9578 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 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_2034 GBV_ILN_2037 GBV_ILN_2038 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_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 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_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 17 2023 12 2432-2443
language	English
source	In IET Intelligent Transport Systems 17(2023), 12, Seite 2432-2443 volume:17 year:2023 number:12 pages:2432-2443
sourceStr	In IET Intelligent Transport Systems 17(2023), 12, Seite 2432-2443 volume:17 year:2023 number:12 pages:2432-2443
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	brakes braking railway rolling stock simulation vehicle dynamics and control Transportation engineering Electronic computers. Computer science
isfreeaccess_bool	true
container_title	IET Intelligent Transport Systems
authorswithroles_txt_mv	Peiwen Chen @@aut@@ Wenliang Zhu @@aut@@ Chaogang Yu @@aut@@ Ningyuan Sun @@aut@@ Wenshen Xue @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	521693659
id	DOAJ099400197
language_de	englisch
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callnumber-first	T - Technology
author	Peiwen Chen
spellingShingle	Peiwen Chen misc TA1001-1280 misc QA75.5-76.95 misc brakes misc braking misc railway rolling stock misc simulation misc vehicle dynamics and control misc Transportation engineering misc Electronic computers. Computer science Research on train braking model by improved Polach model considering wheel‐rail adhesion characteristics
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topic_title	TA1001-1280 QA75.5-76.95 Research on train braking model by improved Polach model considering wheel‐rail adhesion characteristics brakes braking railway rolling stock simulation vehicle dynamics and control
topic	misc TA1001-1280 misc QA75.5-76.95 misc brakes misc braking misc railway rolling stock misc simulation misc vehicle dynamics and control misc Transportation engineering misc Electronic computers. Computer science
topic_unstemmed	misc TA1001-1280 misc QA75.5-76.95 misc brakes misc braking misc railway rolling stock misc simulation misc vehicle dynamics and control misc Transportation engineering misc Electronic computers. Computer science
topic_browse	misc TA1001-1280 misc QA75.5-76.95 misc brakes misc braking misc railway rolling stock misc simulation misc vehicle dynamics and control misc Transportation engineering misc Electronic computers. Computer science
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title	Research on train braking model by improved Polach model considering wheel‐rail adhesion characteristics
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title_full	Research on train braking model by improved Polach model considering wheel‐rail adhesion characteristics
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author_browse	Peiwen Chen Wenliang Zhu Chaogang Yu Ningyuan Sun Wenshen Xue
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title_sort	research on train braking model by improved polach model considering wheel‐rail adhesion characteristics
callnumber	TA1001-1280
title_auth	Research on train braking model by improved Polach model considering wheel‐rail adhesion characteristics
abstract	Abstract To study the braking process of the train under different adhesion conditions, this paper takes the braking system of a single rail vehicle as the research object. The author establishes a corresponding co‐simulation platform based on MATLAB/Simulink and AMESim, including the sub‐models of braking control, vehicle brake longitudinal dynamics and air brake unit. Considering the cleaning effect caused by large sliding, the author builds a suitable adhesion model for different adhesion conditions based on the improved Polach model, which is the input of the vehicle braking longitudinal dynamics sub‐model. Based on the finite state machine, the anti‐skid control algorithm of the train is constructed as the core of the brake control sub‐model, which can judge the motion state of the wheelset, and control the stage release and hold of the brake cylinder pressure. According to the International Standard EN15595 and the actual operating parameters of a certain type of train, the braking process of the train under dry and wet rail conditions is simulated on the platform. The validity of the model is verified, which provides a reliable method for future research on the braking process.
abstractGer	Abstract To study the braking process of the train under different adhesion conditions, this paper takes the braking system of a single rail vehicle as the research object. The author establishes a corresponding co‐simulation platform based on MATLAB/Simulink and AMESim, including the sub‐models of braking control, vehicle brake longitudinal dynamics and air brake unit. Considering the cleaning effect caused by large sliding, the author builds a suitable adhesion model for different adhesion conditions based on the improved Polach model, which is the input of the vehicle braking longitudinal dynamics sub‐model. Based on the finite state machine, the anti‐skid control algorithm of the train is constructed as the core of the brake control sub‐model, which can judge the motion state of the wheelset, and control the stage release and hold of the brake cylinder pressure. According to the International Standard EN15595 and the actual operating parameters of a certain type of train, the braking process of the train under dry and wet rail conditions is simulated on the platform. The validity of the model is verified, which provides a reliable method for future research on the braking process.
abstract_unstemmed	Abstract To study the braking process of the train under different adhesion conditions, this paper takes the braking system of a single rail vehicle as the research object. The author establishes a corresponding co‐simulation platform based on MATLAB/Simulink and AMESim, including the sub‐models of braking control, vehicle brake longitudinal dynamics and air brake unit. Considering the cleaning effect caused by large sliding, the author builds a suitable adhesion model for different adhesion conditions based on the improved Polach model, which is the input of the vehicle braking longitudinal dynamics sub‐model. Based on the finite state machine, the anti‐skid control algorithm of the train is constructed as the core of the brake control sub‐model, which can judge the motion state of the wheelset, and control the stage release and hold of the brake cylinder pressure. According to the International Standard EN15595 and the actual operating parameters of a certain type of train, the braking process of the train under dry and wet rail conditions is simulated on the platform. The validity of the model is verified, which provides a reliable method for future research on the braking process.
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title_short	Research on train braking model by improved Polach model considering wheel‐rail adhesion characteristics
url	https://doi.org/10.1049/itr2.12422 https://doaj.org/article/57d30d43eca44dd78f5975604b5f724d https://doaj.org/toc/1751-956X https://doaj.org/toc/1751-9578
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doi_str	10.1049/itr2.12422
callnumber-a	TA1001-1280
up_date	2024-07-03T22:35:57.854Z
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The author establishes a corresponding co‐simulation platform based on MATLAB/Simulink and AMESim, including the sub‐models of braking control, vehicle brake longitudinal dynamics and air brake unit. Considering the cleaning effect caused by large sliding, the author builds a suitable adhesion model for different adhesion conditions based on the improved Polach model, which is the input of the vehicle braking longitudinal dynamics sub‐model. Based on the finite state machine, the anti‐skid control algorithm of the train is constructed as the core of the brake control sub‐model, which can judge the motion state of the wheelset, and control the stage release and hold of the brake cylinder pressure. According to the International Standard EN15595 and the actual operating parameters of a certain type of train, the braking process of the train under dry and wet rail conditions is simulated on the platform. 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