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An onboard diagnosis method for misfire detection that utilizes a superposed output of combustion pressure sensors (CPS's) is proposed and examined. We consider a model case where piezo-electric type CPS's are installed for each cylinder of a four-stroke-four-cylinder gasoline engine. The outputs of the CPS's are linearly combined to obtain the superposed signal. We show that the superposed signal exhibits a characteristic change when a misfire occurs. A waveform analysis of the signal leads to a clear detection of misfires. A combination setup with a non-intrusive type of fiber-optic CPS that is installed into the cylinder head gasket is also discussed as a future option for the sensing system.

In this study, a system to perform a parameter search of heavy-duty diesel engines is proposed. Recently, it has become essential to use design methodologies including computer simulations for diesel engines that have small amounts of NOx and SOOT while maintaining reasonable fuel economy. For this purpose, multi-objective optimization techniques should be used. Multi-objective optimization problems have several types of objectives and they should be minimized or maximized at the same time. There is often a trade-off relationship between objects and derivation of the Pareto optimum solutions that express the relationship between the objects is one of the goals in this case. The proposed system consists of a multi-objective genetic algorithm (MOGA) and phenomenological model. MOGA has strong search capability for Pareto optimum solutions. However, MOGA requires a large number of iterations.