Title :
Online identification and adaptation of LNT models for improved emission control in lean burn automotive engines
Author :
Le Yi Wang ; Kolmanovsky, Ilya ; Sun, Jing
Author_Institution :
Wayne State Univ., Detroit, MI, USA
Abstract :
In the absence of online emission measurements, the control of lean burn engine after treatment system is often done in a feedforward fashion based on models of feed gas emissions and the after-treatment subsystems. When the ambient conditions (such as humidity) change or the engine components age, these models are no longer accurate, and the performance of the control system that relies on these models may deteriorate. In this paper, we show how the parameters of a lean NOx trap (LNT) model can be identified online using a conventional switching exhaust gas oxygen sensor to improve robustness of the after treatment control system
Keywords :
air pollution control; automobiles; gas sensors; identification; internal combustion engines; real-time systems; NO; automotive engines; emission control; exhaust gas; lean NOx trap model; lean burn engines; online identification; oxygen sensor; Adaptation model; Carbon dioxide; Control system synthesis; Engines; Fuel economy; Gas detectors; Nitrogen; Petroleum; Switches; Vehicle safety;
Conference_Titel :
American Control Conference, 2000. Proceedings of the 2000
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-5519-9
DOI :
10.1109/ACC.2000.876652
