Estimating ignition timing from engine cylinder pressure with neural networks

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Abstract
A study was conducted to determine the ability of neural networks to extract high level control information from cylinder pressure data. Various experiments were performed using neural networks for pattern recognition on a series of data files consisting of cylinder pressure versus crank angle. The goal of these experiments was to estimate spark timing based on the cylinder pressure signature-all other engine parameters were held constant during the data collection process. Test results indicate that an approximate spark time value can be obtained using cylinder pressure data as the inputs to a neural network and spark timing as the output.

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