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Vehicle certification data are used to study the effectiveness of the major powertrain technologies used by car manufacturers to reduce fuel consumption. Methods for differentiating vehicles effectively were developed by leveraging theoretical models of engine and vehicle fuel consumption. One approach normalizes by displacement per unit distance, which puts both fuel used and vehicle work in mean effective pressure units, and is useful when comparing engine technologies. The other normalizes by engine rated power, a customer-relevant output metric. The normalized work/power is proportional to weight/power, the most fundamental performance metric. Certification data for 2016 and 2017 U.S. vehicles with different powertrain technologies are compared to baseline vehicles with port fuel injection (PFI) naturally aspirated engines and six-speed automatic transmissions.

Acoustic standing waves are excited in internal combustion chambers by both normal combustion and autoignition. The energy in these acoustic modes can be transmitted through the engine block and radiated as high-frequency engine noise. Using finite-element models of two different (four-valve and two-valve) production engine combustion chambers, the mode shapes and relative frequencies of the in-cylinder volume acoustic modes are calculated as a function of crank angle. The model is validated by comparison to spectrograms of experimental time-sampled waveforms (from flush-mounted cylinder pressure sensors and accelerometers) from these two typical production spark-ignited engines.

In this paper a new knock control algorithm is developed based on a stochastic interpretation of the knock signal and on a control objective specified as a certain percentage of knocking cycles. Unlike previous ‘stochastic’ knock controllers, the new algorithm does not average or low pass filter the knock intensity signal and the transient response of the controller is consequently much faster. The performance of the new controller is compared in detail with the response of a traditional deterministic controller using a simple but effective knock simulation tool. The results show that the new controller is able to operate at a more advanced mean spark angle and that there is much less cyclic variance about this mean. The transient response to excess knocking events is as fast, or faster, than the conventional controller, though the rate of recovery from overly retarded conditions is slower.

The frequency of the pressure oscillations caused by spark knock depends on the temperature-dependent speed of sound in the combustion gases. Engine dynamometer tests showed a 6.5% (390 Hz) reduction in the knock fundamental frequency as the air/fuel ratio was swept from 13:1 to 20:1. Engine cycle simulation model predictions of maximum burned gas temperatures correlate well with the data. A robust knock detection system must be insensitive to the range of burned gas temperature (frequency of pressure oscillations) that will be encountered with a particular engine control system operating under the expected range of fuels and environmental conditions.

Spark knock pressure oscillations can be detected by a cylinder pressure transducer or by an accelerometer mounted on the engine block. Accelerometer-based detection is lower cost but is affected by extraneous mechanical vibrations and the frequency response of the engine block and accelerometer. The knock oscillation frequency changes during the expansion stroke because the chamber geometry is changing due to the piston motion and the burned gases are cooling. Spectrogram analysis shows the time-dependent frequency content of the pressure and acceleration signals, revealing characteristic signatures of knock and mechanical vibrations. Illustrative spectrograms are presented which yield physical insight into accelerometer-based knock detection.

A wavelet-based technique for reducing the impulsive character of sound recordings is presented. The amount of impulsive content removed may be adjusted by varying a statistical threshold. The technique is validated for a diesel idle sound-quality application. The wavelet-based modification produces a substantial decrease in impulsive character as verified by an objective sound-quality metric for engine “ticking”. Informal subjective assessment of the modified results found them to be realistic and free from artifacts. The procedure is expected to be useful for sound-quality simulation and target-setting for diesel powertrain noise and other automotive sounds containing both impulsive and non-impulsive content.

One important design goal for spark-ignited engines is to minimize cyclic variability. A small amount of cyclic variability (slow burns) can produce undesirable engine vibrations. A larger amount of cyclic variability (incomplete burns) leads to increased hydrocarbon consumption/emissions. Recent studies have reported deterministic patterns in cyclic variability under extremely lean (misfiring) operating conditions. The present work is directed toward more realistic non-misfiring conditions. Production engine test results suggest that deterministic patterns in cyclic variability are the consequence of incomplete combustion, hence control algorithms based on the occurrence of these patterns are not expected to be of significant practical value.