A new algorithm to detect cylinder misfire in automotive gasoline engines is presented in this paper. It is based on processing the variations in crankshaft speed of the engine. In the algorithm, the crankshaft speed data is preprocessed and then modeled as a Mixture of Gaussian components. The appropriate number of components in the data is determined using a goodness-of-fit measure. When misfire is taking place, two or more Gaussian components will appear in the mixture model. Based on the estimated parameters (mean, variance) of the components and a specified probability of false alarms, a Generalized Likelihood decision rule is designed to classify every data point as a misfire or no-misfire behavior. The algorithm was tested on real engine data and the results were encouraging.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.