Multi-objective optimization of water injection in spark-ignition engines using the stochastic reactor model with tabulated chemistry
Journal article, 2019

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.

detailed chemistry

spark-ignition engine

Water injection

genetic optimization

stochastic reactor model

Author

T. Franken

Brandenburg University of Technology

C. Netzer

Brandenburg University of Technology

F. Mauss

Brandenburg University of Technology

M. Pasternak

LOGE

L. Seidel

LOGE

A. Borg

LOGE AB

Harry Lehtiniemi

LOGE AB

Andrea Matrisciano

Chalmers, Mechanics and Maritime Sciences (M2), Combustion and Propulsion Systems

Andre Casal Kulzer

Porsche AG

International Journal of Engine Research

1468-0874 (ISSN) 2041-3149 (eISSN)

Vol. 20 10 1089-1100

Subject Categories

Aerospace Engineering

Energy Engineering

Computational Mathematics

DOI

10.1177/1468087419857602

More information

Latest update

10/15/2019