Constrained optimization of fuel efficiency for RCCI engines

Research output: Contribution to journalConference articleAcademicpeer-review

Abstract

Fuel efficiency optimization and emission reduction have become essential parts of engine research, due to the growing demand for environmental protection. In this paper, a computationally efficient optimization method has been applied to maximize the fuel efficiency under constraints of maximum pressure rise rate and various pollutant emissions using the combination of multiple regression analysis and particle swarm optimization. This optimization method has been applied to a Reactivity Controlled Compression Ignition (RCCI) engine. First, a data-driven model has been identied, which shows good agreement with experimental data for gIMEP as well as emissions. Using this RCCI model in the proposed optimization method, the optimal operating conditions for highest gross indicated thermal efficiency are determined under various conflicting emission and safety constraints.
Original languageEnglish
Pages (from-to)648-653
JournalIFAC-PapersOnLine
Volume52
Issue number5
DOIs
Publication statusPublished - 28 Jun 2019
Event9th IFAC International Symposium on Advances in Automotive Control (AAC2019) - Orléans, France
Duration: 24 Jun 201927 Jun 2019
https://aac19.sciencesconf.org/

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Constrained optimization
Ignition
Engines
Environmental protection
Regression analysis
Particle swarm optimization (PSO)

Keywords

  • engine efficiency optimization
  • multiple regression
  • particle swarm optimization
  • reactivity controlled compression ignition

Cite this

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title = "Constrained optimization of fuel efficiency for RCCI engines",
abstract = "Fuel efficiency optimization and emission reduction have become essential parts of engine research, due to the growing demand for environmental protection. In this paper, a computationally efficient optimization method has been applied to maximize the fuel efficiency under constraints of maximum pressure rise rate and various pollutant emissions using the combination of multiple regression analysis and particle swarm optimization. This optimization method has been applied to a Reactivity Controlled Compression Ignition (RCCI) engine. First, a data-driven model has been identied, which shows good agreement with experimental data for gIMEP as well as emissions. Using this RCCI model in the proposed optimization method, the optimal operating conditions for highest gross indicated thermal efficiency are determined under various conflicting emission and safety constraints.",
keywords = "engine efficiency optimization, multiple regression, particle swarm optimization, reactivity controlled compression ignition",
author = "Lu Xia and Robbert Willems and {de Jager}, Bram and Frank Willems",
year = "2019",
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day = "28",
doi = "10.1016/j.ifacol.2019.09.103",
language = "English",
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journal = "IFAC-PapersOnLine",
issn = "2405-8963",
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Constrained optimization of fuel efficiency for RCCI engines. / Xia, Lu; Willems, Robbert; de Jager, Bram; Willems, Frank.

In: IFAC-PapersOnLine, Vol. 52, No. 5, 28.06.2019, p. 648-653.

Research output: Contribution to journalConference articleAcademicpeer-review

TY - JOUR

T1 - Constrained optimization of fuel efficiency for RCCI engines

AU - Xia, Lu

AU - Willems, Robbert

AU - de Jager, Bram

AU - Willems, Frank

PY - 2019/6/28

Y1 - 2019/6/28

N2 - Fuel efficiency optimization and emission reduction have become essential parts of engine research, due to the growing demand for environmental protection. In this paper, a computationally efficient optimization method has been applied to maximize the fuel efficiency under constraints of maximum pressure rise rate and various pollutant emissions using the combination of multiple regression analysis and particle swarm optimization. This optimization method has been applied to a Reactivity Controlled Compression Ignition (RCCI) engine. First, a data-driven model has been identied, which shows good agreement with experimental data for gIMEP as well as emissions. Using this RCCI model in the proposed optimization method, the optimal operating conditions for highest gross indicated thermal efficiency are determined under various conflicting emission and safety constraints.

AB - Fuel efficiency optimization and emission reduction have become essential parts of engine research, due to the growing demand for environmental protection. In this paper, a computationally efficient optimization method has been applied to maximize the fuel efficiency under constraints of maximum pressure rise rate and various pollutant emissions using the combination of multiple regression analysis and particle swarm optimization. This optimization method has been applied to a Reactivity Controlled Compression Ignition (RCCI) engine. First, a data-driven model has been identied, which shows good agreement with experimental data for gIMEP as well as emissions. Using this RCCI model in the proposed optimization method, the optimal operating conditions for highest gross indicated thermal efficiency are determined under various conflicting emission and safety constraints.

KW - engine efficiency optimization

KW - multiple regression

KW - particle swarm optimization

KW - reactivity controlled compression ignition

U2 - 10.1016/j.ifacol.2019.09.103

DO - 10.1016/j.ifacol.2019.09.103

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JO - IFAC-PapersOnLine

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SN - 2405-8963

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