1998-02-23

Misfire Detection Using a Dynamic Neural Network with Output Feedback 980515

This paper presents a crankshaft speed fluctuation model based dynamic neural network misfire detection method to achieve high detection performance and compact network size. In this method, a dynamic neural network with output feedback is utilized to model an inverse system from the engine crankshaft speed signal to the firing event signal. The engine misfire detection is based on the output of the inverse system given the input of engine speed signal. Test results for a 4-cylinder engine show its promising capability of misfire detection even for the low sampling rate data under various engine operating conditions and misfire patterns.

SAE MOBILUS

Subscribers can view annotate, and download all of SAE's content. Learn More »

Access SAE MOBILUS »

Members save up to 43% off list price.
Login to see discount.
Special Offer: Purchase more aerospace standards and aerospace material specifications and save! AeroPaks off a customized subscription plan that lets you pay for just the documents that you need, when you need them.
X