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Superior NVH performance is a key focus in the development of new powertrains. In recent years, computer simulations have gained an increasing role in the design, development, and optimization of powertrain NVH at component and system levels. This paper presents the results of a study carried out on a 4-cylinder in-line spark-ignition engine with focus on growl noise. Growl is a low frequency noise (300-700 Hz) which is primarily perceived at moderate engine speeds (2000-3000 rpm) and light to moderate throttle tip-ins. For this purpose, a coupled and fully flexible multi-body dynamics model of the powertrain was developed. Structural components were reduced using component mode synthesis and used to determine dynamics loads at various engine speeds and loading conditions. A comparative NVH assessment of various crankshaft designs, engine configurations, and in- cylinder gas pressures was carried out.

Improvements to 1D engine modeling accuracy and computational speed have led to greater reliance on this simulation technology during the engine development process. The benefits of modeling show up in many ways: increased simulation iterations for better optimization, reduction in prototype hardware iterations, reduction in program timing and overall cost. In this study a 1D GT-Power model of a turbocharged engine system was used to assist in the initial design phase and throughout the program. The model was developed using Chrysler Group LLC proprietary modeling features for predictive combustion and knock event prediction. In all stages of this project the model's accuracy was improved through regular correlation with dynamometer data. This paper mainly focuses on engine compression ratio selection, turbocharger selection, and cycle-to-cycle variation/cylinder-to-cylinder variation reduction through the combination of 1D GT-Power model optimization and dynamometer tests.

The Cardan joint of a steerable beam front axle is a complicated mechanical component. It is subjected to drive torque, speed fluctuations, and joint articulation due to powertrain inputs, steering, and suspension kinematics. This combination of high torque and speed fluctuations of the Cardan joint, due to high input drive torque and/or high steer angle maneuvers, can result in premature joint wear. Initially, some observations of premature wear were not well understood based on the existing laboratory and road test data. The present work summarizes a coordinated program of computer modeling, vehicle Rough Road data acquisition, and physical testing used to predict the joint dynamics and to develop advanced testing procedures. Results indicate analytical modeling can predict forces resulting from Cardan joint dynamics for high torque/high turn angle maneuvers, as represented by time history traces recorded in rough road data acquisition.

This paper describes a comprehensive methodology for the simulation of vehicle body panel buckling in an electrophoretic coat (electro-coat or e-coat) and/or paint oven environment. The simulation couples computational heat transfer analysis and structural analysis. Heat transfer analysis is used to predict temperature distribution throughout a vehicle body in curing ovens. The vehicle body temperature profile from the heat transfer analysis is applied as an input for a structural analysis to predict buckling. This study is focused on the radiant section of the curing ovens. The radiant section of the oven has the largest temperature gradients within the body structure. This methodology couples a fully transient thermal analysis to simulate the structure through the electro-coat and paint curing environments with a structural, buckling analysis.

Computational tools have been extensively applied to predict component temperatures before an actual vehicle is built for testing [1, 2, 3, 4, and 5]. This approach provides an estimate of component temperatures during a specific driving condition. The predicted component temperature is compared against acceptable temperature limits. If violations of the temperature limits are predicted, corrective actions will be applied. These corrective actions may include adding heat shields to the heat source or to the receiving components. Therefore, design changes are implemented based on the simulation results. Sensitivity analysis is the formal technique of determining most influential parameters in a system that affects its performance. Uncertainty analysis is the process of evaluating the deviation of the design from its intended design target.

Vehicle front end air flow management affects many aspects of vehicle aero/thermal performances. The HVAC system capacity is greatly driven by the airflow and the air temperature received at the condenser. In this paper, front end design practices are investigated using computer simulation and full vehicle test to evaluate their effects on AC system performance. A full vehicle 3D CFD model is developed and used to predict the airflow and temperature in underhood and around the vehicle body, and specifically the conditions entering the condenser. The condenser inlet airflow and temperature profiles from 3D CFD model are then used as inputs for the 1D AC system model. The 1D AC system model, which includes condenser, compressor, evaporator and TXV (Thermal eXpansion Valve), is developed to observe the critical AC performance indicators such as panel out air temperature and compressor head pressure.