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An Artificial UEGO Sensor for Engine Cold Start - Methodology, Design, and Performance
Technical Paper
2000-01-0541
ISSN: 0148-7191, e-ISSN: 2688-3627
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Sector:
Event:
SAE 2000 World Congress
Language:
English
Abstract
The AFR control accuracy in the cold start is crucial to lowering emissions from IC-engine vehicles. An artificial UEGO “sensor” for estimating the real-time AFR during the engine cold start has been developed on the basis of a fuel-perturbation algorithm at Ford Scientific Research Labs. The AFR values calculated by the artificial UEGO sensor have been used in the closed-loop fuel control. Considering that the engine cold start AFR is an uncertain, non-linear problem, some other techniques for optimizing the input stimulation signal and the output-filtering model are integrated together with the fuel perturbation. This artificial sensor was realized and its performance was tested on a Ford vehicle for EPA75 cold 505 test. The assessment of the artificial sensor was quite different in comparison with that of a real UEGO sensor. The concept of this artificial UEGO sensor may also be applied to lean-combustion control, FMM (failure mode management) emissions control, reduction in vehicle calibration time, and misfire diagnosis.
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Authors
Topic
Citation
Tang, X., "An Artificial UEGO Sensor for Engine Cold Start - Methodology, Design, and Performance," SAE Technical Paper 2000-01-0541, 2000, https://doi.org/10.4271/2000-01-0541.Also In
Electronic Engine Controls 2000: Modeling, Neural Networks, Obd, and Sensors
Number: SP-1501; Published: 2000-03-06
Number: SP-1501; Published: 2000-03-06
References
- Asik J.R. Peter J.M. Meyer G.M. Tang X. “Transient A/F Estimation and Control Using a Neural Network” SAE Paper No. 970619
- Tang X. Asik J.R. Meyer G.M. Samson R.G. “Optimal A/F Estimation Model (Synthetic UEGO) for SI Engine Cold Transient AFR Feedback Control” SAE Paper No. 980798