Estimating In-Cylinder Precombustion Mixture Temperatures Using Acoustic Resonances

Abstract

The air-fuel ratio of automotive engines during the warm-up period is difficult to control and contributes a substantial portion of the emissions on the EPA test cycle. High bandwidth estimation of the in-cylinder charge temperature provides opportunities for improvement in spark ignition (SI) engine control algorithms. Pressure sensor based algorithms for estimating air-fuel ratio (AFR) have been shown to be improved by bulk temperature information. This paper explores the suitability of using acoustic resonances to estimate charge temperature in the presence of an unknown AFR and without the ‘sharp’ excitation of diesel or knocking SI combustion. A technique that allows for the estimation of the precombustion average bulk charge temperature during a 1-2 ms interval based on acoustic resonance data gathered from a pressure transducer is described. A parameter estimation algorithm suitable for extracting the required frequency information from short data sets is identified. The variation in temperature estimates as a function of AFR has been explored using a computer simulation that accounts for the change in the ratio of specific heats with changing mixture strength. The performance of the acoustic resonance based temperature estimates has been evaluated by comparing them to predictions based on a polytropic compression.