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Multi-objective optimization of water injection in spark-ignition engines using the stochastic reactor model with tabulated chemistry

Franken, T. (författare)
Brandenburgische Technische Universität Cottbus-Senftenberg,Brandenburg University of Technology Cottbus-Senftenberg
Netzer, C. (författare)
Brandenburgische Technische Universität Cottbus-Senftenberg,Brandenburg University of Technology Cottbus-Senftenberg
Mauss, F. (författare)
Brandenburgische Technische Universität Cottbus-Senftenberg,Brandenburg University of Technology Cottbus-Senftenberg
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Pasternak, M. (författare)
Seidel, L. (författare)
Borg, A. (författare)
Lehtiniemi, Harry (författare)
Matrisciano, Andrea, 1986 (författare)
Chalmers tekniska högskola,Chalmers University of Technology
Kulzer, Andre Casal (författare)
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 (creator_code:org_t)
2019-06-19
2019
Engelska.
Ingår i: International Journal of Engine Research. - : SAGE Publications. - 1468-0874 .- 2041-3149. ; 20:10, s. 1089-1100
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • Water injection is investigated for turbocharged spark-ignition engines to reduce knock probability and enable higher engine efficiency. The novel approach of this work is the development of a simulation-based optimization process combining the advantages of detailed chemistry, the stochastic reactor model and genetic optimization to assess water injection. The fast running quasi-dimensional stochastic reactor model with tabulated chemistry accounts for water effects on laminar flame speed and combustion chemistry. The stochastic reactor model is coupled with the Non-dominated Sorting Genetic Algorithm to find an optimum set of operating conditions for high engine efficiency. Subsequently, the feasibility of the simulation-based optimization process is tested for a three-dimensional computational fluid dynamic numerical test case. The newly proposed optimization method predicts a trade-off between fuel efficiency and low knock probability, which highlights the present target conflict for spark-ignition engine development. Overall, the optimization shows that water injection is beneficial to decrease fuel consumption and knock probability at the same time. The application of the fast running quasi-dimensional stochastic reactor model allows to run large optimization problems with low computational costs. The incorporation with the Non-dominated Sorting Genetic Algorithm shows a well-performing multi-objective optimization and an optimized set of engine operating parameters with water injection and high compression ratio is found.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Rymd- och flygteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Aerospace Engineering (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Energiteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Energy Engineering (hsv//eng)
NATURVETENSKAP  -- Matematik -- Beräkningsmatematik (hsv//swe)
NATURAL SCIENCES  -- Mathematics -- Computational Mathematics (hsv//eng)

Nyckelord

detailed chemistry
spark-ignition engine
Water injection
genetic optimization
stochastic reactor model

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