Search Results

The fuel air ratio imbalance between individual cylinders can result in poor fuel economy and severe exhaust emissions. Individual cylinder fuel air ratio control is one of the important techniques used to improve fuel economy and reduce exhaust emission. California Air Resources Board (CARB) also has required automotive manufacturers to equip with on-board diagnosis system for cylinder fuel air ratio imbalance detection starting in 2011. However, one of the most challenging tasks for the individual cylinder fuel air ratio control and cylinder imbalance diagnosis is how to retrieve the cylinder fuel air ratio information effectively at low cost. This paper presents a novel and practical signal processing based fuel air ratio estimation method for individual cylinder fuel air ratio balance control and on-board fuel air ratio imbalance diagnosis.

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.