Misfire Detection Including Confidence Indicators Using a Hardware Neural Network

Chris Kirkham; Roberta Cambio

doi:10.4271/2006-01-1349

2006-04-03

Misfire Detection Including Confidence Indicators Using a Hardware Neural Network 2006-01-1349

The complexity of automotive power train and control systems is necessitating the implementation of advanced techniques, in turn placing an increasing computational load on the ECU systems.

Misfire detection is a pattern classification problem involving the complex, non-linear interactions of good combustion/misfire event distributions for multiple input signals.

Building on previously reported developments in these areas, this paper describes practical advances in misfire detection techniques that, through the use of hardware neural network technology, provide measures of “confidence” in the decision, and a single diagnostic metric for arbitration and calibration of the solution for a current series production engine.

SAE MOBILUS

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

Access SAE MOBILUS »

Digital $37.00 Print $37.00

Preview Document

We also recommend:

Standards

SAE Mobilus®

Publications

News

Events

Professional Development

A World in Motion (PreK-12)

Participate with SAE

SAE Membership

Donate

Misfire Detection Including Confidence Indicators Using a Hardware Neural Network 2006-01-1349

SAE MOBILUS