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EcoBoost engines constitute one of the strategies used by Ford Motor Company to deliver engines with improved fuel economy and performance. However, turbochargers exhibit many inherent NVH challenges that need to be addressed in order to deliver refined engines that meet customer’s expectation. One of these challenges is the turbocharger 1st order synchronous noise due to the interaction between the manufacturing tolerances of the rotating components and the dynamic behavior of the rotor. This paper discusses an MBD/FEA/BEM based method to predict the nonlinear dynamic behavior of the rotor semi floating bearing, its impact on the bearing loads and the resulting powerplant noise due to the interaction with the turbocharger imbalance level.

The increasing demands to reduce cost is forcing North American Automotive designers towards finding ways to use the thermoplastic material for the under hood components. The use of this material has often been avoided in this type of applications due to concerns around its long-term strength and temperature performance. In particular, the materials of choice for the engine cam cover are Aluminum, Magnesium and Vinyl Ester (Thermoset) although thermoplastic is widely used in Europe and Asia. This paper examines the potential of a thermoplastic cam cover designed to replace the thermoset cam cover in a 4.0L SOHC V6 engine. Experimental data, presented in this paper, demonstrate that a well-designed thermoplastic cam cover can achieve key functional requirements, such as NVH and sealing, while providing substantial cost saving.

Exhaust systems can be a source of vibrations that transmit inside the vehicle through the exhaust hangers. These vibrations are caused by engine excitations under acceleration. During the upfront development stage, it is important to predict accurately the forces of the exhaust hangers in order to drive a robust exhaust system design and prevent objectionable noise and vibrations inside the vehicle. This paper describes an FEA-based simulation method to predict the exhaust hanger forces. It demonstrates the effect of temperature on the exhaust dynamic behavior and its importance for an accurate prediction of the exhaust hanger forces.

Combustion stability is a key contributor to engine shake at idle speed and can impact the overall perception of vehicle quality. The sub-firing harmonics of the combustion torque are used as a metric to assess idle shake and are, typically, measured at different levels of engine break mean effective pressure (BMEP). Due to the nature of the combustion phenomena at idle, it is clear that predicting the cycle-to-cycle and cylinder-to-cylinder combustion pressure variations, required to assess the combustion uniformity, cannot be achieved with the state of the art simulation technology. Inspired by the advancement in the field of machine learning and artificial intelligence and by the availability of a large amount of measured combustion test data, this paper explores the performance of various machine learning algorithms in predicting the idle combustion uniformity.

Variable Displacement Oil Pump (VDOP) is becoming the design of choice for engine friction reduction and fuel economy improvement. Unfortunately, this pump creates excessive pressure ripples, at the outlet port during oil pump shaft rotation, causing oscillating forces within the lubrication system and leading to the generation of objectionable tonal noises and vibrations. In order to minimize the level of noise, different vanes spacing and porting geometries are used. Moreover, an oil pressure relief groove can be added, at the onset of the high pressure port, to achieve this goal. This paper presents an optimization method to identify the best geometry of the oil pressure relief groove. This method integrates adaptive meshing, 3D CFD simulation, Matlab routine and Genetic Algorithm based optimization. The genetic algorithm is used to create the required design space in order to perform a multi-objective optimization using a large number of parameterized groove geometries.