Concept investigation for misfire detection in spark-ignited gas engines

Detta är en Master-uppsats från KTH/Skolan för industriell teknik och management (ITM)

Författare: Stefan Hamberg; [2019]

Nyckelord: ;

Sammanfattning: As a supplier of sustainable transport solutions, Scania manufactures gas engines. Fueled with biogas, they offer a significant decrease in carbon dioxide emissions compared to standard diesel. The gas engines are fitted with a three-way catalytic converter, which converts hydrocarbons, carbon monoxide and nitrogen oxides from the combustion process to substances with less adverse effects. A misfire is an undesired lack of combustion. They are typically caused by faults in the ignition system, fuel system or by an unsuitable air/fuel ratio. If a misfire occurs, fuel may enter the catalytic converter where it combusts. This increases the temperature in the catalyst to above its design limit, permanently damaging it. The excess fuel also causes increased hydrocarbon emissions. Emission legislation mandates that malfunctions causing excess emissions must be continuously monitored by the vehicle. The misfire detection on engines sold in the North American market must comply with the stringent CARB legislation. It may also be assumed that upcoming European legislation will be stricter. Furthermore, current production engines use dedicated hardware to detect misfires. A misfire detection method that uses signals from sensors already fitted to the engine could result in cost savings. A literature study was performed, after which suitable methods to proceed with were chosen. Data was collected in an engine test cell, and was analyzed offline. Misfire detection methods based on exhaust pressure sensors and knock sensors were evaluated. A detection algorithm developed for Scania’s diesel engines was evaluated. With some modifications, it appears suitable for gas engines. Simplified variants of this method were developed with promising results. A method based on Fourier transform of a low-order frequency showed excellent results, perhaps at the expense of processor load. A knock sensor based method also showed some promise in detecting misfires. However, the position of the knock sensors appears critical, and further investigation is required. Classified parts of this thesis are replaced by the symbol □. Some plot axes are erased for the same reason.

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