International Journal of Computational
Intelligence Research (IJCIR)
Volume 2, Number 2 (2006)
Evolutionary algorithm as a tool for advanced designing of Diesel engines
Donateo Teresa, Laforgia Domenico
Research Center for Energy and Environment – University of Lecce via per Monteroni - Lecce, Italy
Aloisio Giovanni, Mocavero Silvia
CACT/ISUFI & NNL/INFM&CNR – University of Lecce, via per Arnesano - Lecce, Italy
An evolutionary algorithm has been developed for the design of a diesel engine combustion chamber in order to fulfill present day and future regulations about pollutant emissions and greenhouse gases. The competitive goals to be achieved in engine optimization are the reduction of emission levels (soot, NOx and HC) and the improvement of specific fuel consumption. They have been taken into account by using a multi-objective approach implemented in an optimization tool called HiPerGEO, which is characterized by a very small population and a mechanism of reinizialization, combined with an external memory to store non-dominated solutions.
The method was applied to the design of the combustion chamber profile and numerical simulations were performed with a modified version of the KIVA3V code to evaluate the fitness values of the solutions. The chamber profile was defined according to five geometrical parameters used as inputs to the optimization method. The output of the simulations in terms of emissions and IMEP were used to define four different objective functions. The search for the optimum was performed by applying the Pareto optimality criterion so that it is not bounded to arbitrary weights assigned to each objective. At the end of the simulation, the user can choose from the final Pareto set the best compromise solution for different applications.
The method allows the optimization with respect to different engine operating conditions, i.e. load and speed values. In the present investigation, four operating modes were considered and weights were assigned to them according to their importance in the reduction of emissions and fuel consumption. The use of a 3D simulation code to simulate the behavior of the engine with respect to four operating modes is a very time expensive approach. To reduce the required computational time, which is prohibitive on a sequential machine, grid technologies were implemented in a grid portal named DESGrid.
Grid technologies, industrial problem, micro genetic algorithm, multi-objective optimization, Diesel engines, clustering.