Abstract

Abstract European standards on pollutants have resulted in the systematic integration of a three-way catalytic converter (3WCC) on gasoline engines. The conversion efficiency of the 3WCC is strongly dependent on the temperature of the 3WCC itself. Knowing this temperature is a key element in predicting and minimizing the real quantities of pollutants that the gasoline engine rejects. Due to cost issues, it is really difficult to obtain this information through a direct measurement. This article presents a complete methodology for estimating exhaust gas and catalyst temperature in real time. The first step of this methodology consists of building a 1-dimensional physical model (1D model) of the 3WCC’s temperature. All of the parameters of this model are identified using some experimental data and a particle swarm optimization algorithm. The second step of the proposed methodology consists of using an extended Kalman filter algorithm to estimate all temperatures in real time from a linearized model based on the previous 1D physical model and a measurement downstream of the 3WCC. Every step of this methodology is validated using experimental data.

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