Finding optimum range for increasing the transport coefficients in a three-way catalytic converter in order to achieve minimum light-off time and maximum increase in efficiency using multiobjective genetic algorithm

Abstract

In this article, an optimum range for increasing transport coefficients with respect to the laminar flow condition in the channel of a three-way catalyst is introduced. A mathematical model of a three-way catalyst was first developed. The model is a one-dimensional plug flow model which involves mass and energy equations in gas and solid phases. To save numerical time, the three-way catalyst model was replaced with a neural network model used in optimization which was solved by using a multi-objective genetic algorithm method. The results of optimization introduce a range in which the desirable objectives will be satisfied. The objectives are to achieve minimum light-off time and maximum increase in catalyst efficiency during different operating conditions of engine. © 2014 American Institute of Chemical Engineers Environ Prog, 34: 368–379, 2015