Rail pressure controller design of GDI basing on predictive functional control

Abstract Gasoline direct injection (GDI) is a pivotal technique for a highly efficient engine. However, how to maintain a stable rail pressure which offers good fuel economy and low emissions, is still a challengeable work. In this paper, a rail pressure controller is designed basing on predictive f...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Zhang, Zhiming [verfasserIn] Xie, Lei Su, Hongye

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Rail pressure control model based predictive control predictive functional control

Anmerkung:	© South China University of Technology, Academy of Mathematics and Systems Science, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Übergeordnetes Werk:	Enthalten in: Journal of control theory and applications - Guangzhou, 2003, 17(2019), 2 vom: 23. Apr., Seite 176-182
Übergeordnetes Werk:	volume:17 ; year:2019 ; number:2 ; day:23 ; month:04 ; pages:176-182

Links:	Volltext

DOI / URN:	10.1007/s11768-019-8243-1

Katalog-ID:	SPR022317422

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allfields	10.1007/s11768-019-8243-1 doi (DE-627)SPR022317422 (SPR)s11768-019-8243-1-e DE-627 ger DE-627 rakwb eng Zhang, Zhiming verfasserin aut Rail pressure controller design of GDI basing on predictive functional control 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © South China University of Technology, Academy of Mathematics and Systems Science, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2019 Abstract Gasoline direct injection (GDI) is a pivotal technique for a highly efficient engine. However, how to maintain a stable rail pressure which offers good fuel economy and low emissions, is still a challengeable work. In this paper, a rail pressure controller is designed basing on predictive functional control (PFC), a model predictive control (MPC) method, to surmount the nonlinearity and discontinuity brought by the common rail pressure system (CRPS). A control-oriented piecewise linear model is presented to simplify the CRPS. The simulation results on a benchmark show that rail pressure tracks the setpoint accurately even with some perturbations. Profiting from the conciseness of PFC algorithm, the controller can compute the online solution in a short time, which makes it possible to realize the strategy on a fast response system. Rail pressure control (dpeaa)DE-He213 model based predictive control (dpeaa)DE-He213 predictive functional control (dpeaa)DE-He213 Xie, Lei aut Su, Hongye aut Enthalten in Journal of control theory and applications Guangzhou, 2003 17(2019), 2 vom: 23. Apr., Seite 176-182 (DE-627)529093456 (DE-600)2299595-X 1993-0623 nnns volume:17 year:2019 number:2 day:23 month:04 pages:176-182 https://dx.doi.org/10.1007/s11768-019-8243-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 AR 17 2019 2 23 04 176-182
spelling	10.1007/s11768-019-8243-1 doi (DE-627)SPR022317422 (SPR)s11768-019-8243-1-e DE-627 ger DE-627 rakwb eng Zhang, Zhiming verfasserin aut Rail pressure controller design of GDI basing on predictive functional control 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © South China University of Technology, Academy of Mathematics and Systems Science, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2019 Abstract Gasoline direct injection (GDI) is a pivotal technique for a highly efficient engine. However, how to maintain a stable rail pressure which offers good fuel economy and low emissions, is still a challengeable work. In this paper, a rail pressure controller is designed basing on predictive functional control (PFC), a model predictive control (MPC) method, to surmount the nonlinearity and discontinuity brought by the common rail pressure system (CRPS). A control-oriented piecewise linear model is presented to simplify the CRPS. The simulation results on a benchmark show that rail pressure tracks the setpoint accurately even with some perturbations. Profiting from the conciseness of PFC algorithm, the controller can compute the online solution in a short time, which makes it possible to realize the strategy on a fast response system. Rail pressure control (dpeaa)DE-He213 model based predictive control (dpeaa)DE-He213 predictive functional control (dpeaa)DE-He213 Xie, Lei aut Su, Hongye aut Enthalten in Journal of control theory and applications Guangzhou, 2003 17(2019), 2 vom: 23. Apr., Seite 176-182 (DE-627)529093456 (DE-600)2299595-X 1993-0623 nnns volume:17 year:2019 number:2 day:23 month:04 pages:176-182 https://dx.doi.org/10.1007/s11768-019-8243-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 AR 17 2019 2 23 04 176-182
allfields_unstemmed	10.1007/s11768-019-8243-1 doi (DE-627)SPR022317422 (SPR)s11768-019-8243-1-e DE-627 ger DE-627 rakwb eng Zhang, Zhiming verfasserin aut Rail pressure controller design of GDI basing on predictive functional control 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © South China University of Technology, Academy of Mathematics and Systems Science, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2019 Abstract Gasoline direct injection (GDI) is a pivotal technique for a highly efficient engine. However, how to maintain a stable rail pressure which offers good fuel economy and low emissions, is still a challengeable work. In this paper, a rail pressure controller is designed basing on predictive functional control (PFC), a model predictive control (MPC) method, to surmount the nonlinearity and discontinuity brought by the common rail pressure system (CRPS). A control-oriented piecewise linear model is presented to simplify the CRPS. The simulation results on a benchmark show that rail pressure tracks the setpoint accurately even with some perturbations. Profiting from the conciseness of PFC algorithm, the controller can compute the online solution in a short time, which makes it possible to realize the strategy on a fast response system. Rail pressure control (dpeaa)DE-He213 model based predictive control (dpeaa)DE-He213 predictive functional control (dpeaa)DE-He213 Xie, Lei aut Su, Hongye aut Enthalten in Journal of control theory and applications Guangzhou, 2003 17(2019), 2 vom: 23. Apr., Seite 176-182 (DE-627)529093456 (DE-600)2299595-X 1993-0623 nnns volume:17 year:2019 number:2 day:23 month:04 pages:176-182 https://dx.doi.org/10.1007/s11768-019-8243-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 AR 17 2019 2 23 04 176-182
allfieldsGer	10.1007/s11768-019-8243-1 doi (DE-627)SPR022317422 (SPR)s11768-019-8243-1-e DE-627 ger DE-627 rakwb eng Zhang, Zhiming verfasserin aut Rail pressure controller design of GDI basing on predictive functional control 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © South China University of Technology, Academy of Mathematics and Systems Science, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2019 Abstract Gasoline direct injection (GDI) is a pivotal technique for a highly efficient engine. However, how to maintain a stable rail pressure which offers good fuel economy and low emissions, is still a challengeable work. In this paper, a rail pressure controller is designed basing on predictive functional control (PFC), a model predictive control (MPC) method, to surmount the nonlinearity and discontinuity brought by the common rail pressure system (CRPS). A control-oriented piecewise linear model is presented to simplify the CRPS. The simulation results on a benchmark show that rail pressure tracks the setpoint accurately even with some perturbations. Profiting from the conciseness of PFC algorithm, the controller can compute the online solution in a short time, which makes it possible to realize the strategy on a fast response system. Rail pressure control (dpeaa)DE-He213 model based predictive control (dpeaa)DE-He213 predictive functional control (dpeaa)DE-He213 Xie, Lei aut Su, Hongye aut Enthalten in Journal of control theory and applications Guangzhou, 2003 17(2019), 2 vom: 23. Apr., Seite 176-182 (DE-627)529093456 (DE-600)2299595-X 1993-0623 nnns volume:17 year:2019 number:2 day:23 month:04 pages:176-182 https://dx.doi.org/10.1007/s11768-019-8243-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 AR 17 2019 2 23 04 176-182
allfieldsSound	10.1007/s11768-019-8243-1 doi (DE-627)SPR022317422 (SPR)s11768-019-8243-1-e DE-627 ger DE-627 rakwb eng Zhang, Zhiming verfasserin aut Rail pressure controller design of GDI basing on predictive functional control 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © South China University of Technology, Academy of Mathematics and Systems Science, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2019 Abstract Gasoline direct injection (GDI) is a pivotal technique for a highly efficient engine. However, how to maintain a stable rail pressure which offers good fuel economy and low emissions, is still a challengeable work. In this paper, a rail pressure controller is designed basing on predictive functional control (PFC), a model predictive control (MPC) method, to surmount the nonlinearity and discontinuity brought by the common rail pressure system (CRPS). A control-oriented piecewise linear model is presented to simplify the CRPS. The simulation results on a benchmark show that rail pressure tracks the setpoint accurately even with some perturbations. Profiting from the conciseness of PFC algorithm, the controller can compute the online solution in a short time, which makes it possible to realize the strategy on a fast response system. Rail pressure control (dpeaa)DE-He213 model based predictive control (dpeaa)DE-He213 predictive functional control (dpeaa)DE-He213 Xie, Lei aut Su, Hongye aut Enthalten in Journal of control theory and applications Guangzhou, 2003 17(2019), 2 vom: 23. Apr., Seite 176-182 (DE-627)529093456 (DE-600)2299595-X 1993-0623 nnns volume:17 year:2019 number:2 day:23 month:04 pages:176-182 https://dx.doi.org/10.1007/s11768-019-8243-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 AR 17 2019 2 23 04 176-182
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spellingShingle	Zhang, Zhiming misc Rail pressure control misc model based predictive control misc predictive functional control Rail pressure controller design of GDI basing on predictive functional control
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topic_title	Rail pressure controller design of GDI basing on predictive functional control Rail pressure control (dpeaa)DE-He213 model based predictive control (dpeaa)DE-He213 predictive functional control (dpeaa)DE-He213
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title	Rail pressure controller design of GDI basing on predictive functional control
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title_full	Rail pressure controller design of GDI basing on predictive functional control
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title_sort	rail pressure controller design of gdi basing on predictive functional control
title_auth	Rail pressure controller design of GDI basing on predictive functional control
abstract	Abstract Gasoline direct injection (GDI) is a pivotal technique for a highly efficient engine. However, how to maintain a stable rail pressure which offers good fuel economy and low emissions, is still a challengeable work. In this paper, a rail pressure controller is designed basing on predictive functional control (PFC), a model predictive control (MPC) method, to surmount the nonlinearity and discontinuity brought by the common rail pressure system (CRPS). A control-oriented piecewise linear model is presented to simplify the CRPS. The simulation results on a benchmark show that rail pressure tracks the setpoint accurately even with some perturbations. Profiting from the conciseness of PFC algorithm, the controller can compute the online solution in a short time, which makes it possible to realize the strategy on a fast response system. © South China University of Technology, Academy of Mathematics and Systems Science, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2019
abstractGer	Abstract Gasoline direct injection (GDI) is a pivotal technique for a highly efficient engine. However, how to maintain a stable rail pressure which offers good fuel economy and low emissions, is still a challengeable work. In this paper, a rail pressure controller is designed basing on predictive functional control (PFC), a model predictive control (MPC) method, to surmount the nonlinearity and discontinuity brought by the common rail pressure system (CRPS). A control-oriented piecewise linear model is presented to simplify the CRPS. The simulation results on a benchmark show that rail pressure tracks the setpoint accurately even with some perturbations. Profiting from the conciseness of PFC algorithm, the controller can compute the online solution in a short time, which makes it possible to realize the strategy on a fast response system. © South China University of Technology, Academy of Mathematics and Systems Science, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2019
abstract_unstemmed	Abstract Gasoline direct injection (GDI) is a pivotal technique for a highly efficient engine. However, how to maintain a stable rail pressure which offers good fuel economy and low emissions, is still a challengeable work. In this paper, a rail pressure controller is designed basing on predictive functional control (PFC), a model predictive control (MPC) method, to surmount the nonlinearity and discontinuity brought by the common rail pressure system (CRPS). A control-oriented piecewise linear model is presented to simplify the CRPS. The simulation results on a benchmark show that rail pressure tracks the setpoint accurately even with some perturbations. Profiting from the conciseness of PFC algorithm, the controller can compute the online solution in a short time, which makes it possible to realize the strategy on a fast response system. © South China University of Technology, Academy of Mathematics and Systems Science, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2019
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title_short	Rail pressure controller design of GDI basing on predictive functional control
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Rail pressure controller design of GDI basing on predictive functional control

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