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Engine cylinder pressure is traditionally measured with a piezo-electric pressure transducer, and as such, must be referenced or pegged to a known value. Frequently, the cylinder pressure is pegged to the pressure in the intake manifold plenum whereby the manifold absolute pressure (MAP) at the end of the intake stroke is measured and the cylinder pressure trace for the entire cycle is adjusted such that the cylinder pressure is set equal to the manifold pressure at the end of the intake stroke. However, any error in pegging induces an error in the cylinder pressure trace, which has an adverse effect on the entire combustion analysis. This research is focused on assessing the pegging error for several pegging methods across a wide range of engine operating conditions, and ultimately determining best practices to minimize error in pegging and the calculated combustion metrics. The study was conducted through 1D simulations using the commercially available GT-Power.

The proliferation of small silicon micro-chips has led to a large assortment of low-cost transducers for data acquisition. Production vehicles on average exploit more than 60 on board sensors, and that number is projected to increase beyond 200 per vehicle by 2020. Such a large increase in sensors is leading the fourth industrial revolution of connectivity and autonomy. One major downfall to installing many sensors is compromises in their accuracy and processing power due to cost limitations for high volume production. The same common errors in data acquisition such as sampling, quantization, and multiplexing on the CAN bus must be accounted for when utilizing an entire array of vehicle sensors. A huge advantage of onboard sensors is the ability to calculate vehicle parameters during a daily drive cycle to update ECU calibration factors in real time. One such parameter is driveline damping, which changes with gear state and drive mode. A damping value is desired for every gear state.