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At the initial accessory drive system design stage, a model was created using commercial CAE software to predict the dynamic response of the pulleys, tensioner motion and pulley slip. In a typical 6 cylinder automotive accessory drive systems, the first system torsional mode is near the engine idle speed. The combination of these two events could generate numerous undesirable noise and vibration effects in the system. Data acquisition on a firing engine with a powertrain dynamometer confirmed the computer model's results. Correlations are then developed and established based on results between the firing engine to the CAE model to increase confidence in the generated model. Further system optimization through design modifications are used to tune the system to minimize the overall system dynamics.

The Controller Area Network (CAN) provides the user with several parameters to configure the bit timing, sampling point, and bit rate. With this flexibility comes some complexity in choosing the correct values for these parameters and properly configuring the bit rate. A given bit rate can be achieved by setting these parameter in more than one way. It is also possible to incorrectly configure these parameters and achieve a close enough bit rate that will allow the system to function but not perform in an optimized manner. This paper discusses how to calculate the bit rate and how to choose some of these parameters. A set of equations were developed and used in an example to configure the bit rate for a PIC18FXX8 CAN controller.

In this paper, loads acting on driveline components during an entire proving ground (PG) durability schedule are used to demonstrate the methodology of optimizing driveline performance reliability using both physical and computational methods. It is well known that there is an effect of driver variability on the driveline component loads. Yet, this effect has not been quantified in the past for lack of experimental data from multiple drivers and reliable data analysis methods. This paper presents the data reduction techniques that are used to identify the extreme driver performance and to extrapolate the short-term measurement to long-term data for driveline performance reliability. The driveline loading variability is made evident in the rotating moment histogram domain. This paper also introduces the concept for a simulation model to predict the driveline component loads based on a complete proving grounds schedule. A model-to-test correlation is also performed in this paper.

Improving catalyst light-off characteristics during cold start and reducing engine-out (more accurately converter-in) emissions prior to catalyst light-off have been regarded as the keys to meeting future stringent emissions regulations. Many technologies and control strategies have been proposed, and some of them have already been incorporated into production, to address these issues. Among these, secondary air injection received a lot of attention. This study was initiated to investigate the thermal and chemical processes associated with secondary air injection inside the exhaust system in order to maximize the simultaneous benefit of improving catalyst light-off performance and reducing converter-in emissions. The effects of several design and operating parameters such as secondary air injection location, exhaust manifold design, spark timing, engine enrichment level, and secondary air flow rate were carefully examined.