An Artificial UEGO Sensor for Engine Cold Start -Methodology, Design, and Performance

摘要

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.