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MACHINE LEARNING FOR MISFIRE DETECTION IN A DYNAMIC FIRING LEVEL MODULATION CONTROLLED ENGINE OF A VEHICLE
MACHINE LEARNING FOR MISFIRE DETECTION IN A DYNAMIC FIRING LEVEL MODULATION CONTROLLED ENGINE OF A VEHICLE
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机译:车辆动态射击水平调制控制引擎中的机器学习
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摘要
Using machine learning for cylinder misfire detection in a dynamic firing level modulation controlled internal combustion engine is described. In a classification embodiment, cylinder misfires are differentiated from intentional skips based on a measured exhaust manifold pressure. In a regressive model embodiment, the measured exhaust manifold pressure is compared to a predicted exhaust manifold pressure generated by neural network in response to one or more inputs indicative of the operation of the vehicle. Based on the comparison, a prediction is made if a misfire has occurred or not. In yet other alternative embodiment, angular crank acceleration is used as well for misfire detection.
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