شماره ركورد كنفرانس :
3222
عنوان مقاله :
Online Torque Estimation of Internal Combustion Engines Using Neural Networks
پديدآورندگان :
Naserimojarad Mohammad Mehdi School of Electrical and Computer Engineering - Shiraz University , Safavi Ali Akbar School of Electrical and Computer Engineering - Shiraz University , Tadayoninejad Ali School of Electrical and Computer Engineering - Shiraz University , Bahmani Koukhdan Ali School of Electrical and Computer Engineering - Shiraz University
كليدواژه :
Online Torque Estimation , Internal Combustion Engines , Neural Networks
عنوان كنفرانس :
دومين كنفرانس بين المللي كنترل، ابزار دقيق و اتوماسيون
چكيده لاتين :
An internal combustion engine torque estimation method based on artificial neural networks has been proposed in this paper. Besides, an investigation has been done to show neural networks ability to detect faults like misfire, O2 sensor problem, MAP sensor problem and fuel injector problem. Unlike most other methods there is no need to auxiliary add-on systems to collect data and all of the estimation procedure takes place via available data on the on-board diagnostic data line. This method has been tested on a real experimental XU7; Peugeot engine connected to a dynamometer. Estimated torque values and determined faults have been compared with the real experimental data
