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A detailed Design of Experiments (DOE) study is presented to understand the aerodynamic effects of exterior design features and shape parameters of a pick-up truck using Computational Fluid Dynamics (CFD). The goal of the study is to characterize several key design parameters and the interactions between them as related to overall drag of the vehicle. Using this data, the exterior shape is optimized to minimize drag within specified design constraints. An adaptive sampling methodology is also presented that progressively reduces errors in the design response surfaces generated. This combined with a Latin Hypercube based initial design space characterization yields computational efficiency. A trend-predictive meta-model is presented that can be used for early design development. Results from the meta-model are also correlated with experimental data from the wind tunnel.

Upper frame deflection of automobile doors is a key design attribute that influences structural integrity and door seal performance as related to NVH. This is a critical customer quality perception attribute and is a key enabler to ensure wind noise performance is acceptable. This paper provides an overview of two simulation methodologies to predict door upper frame deflection. A simplified simulation approach using point loads is presented along with its limitations and is compared to a new method that uses CFD tools to estimate aerodynamic loads on body panels at various vehicle speeds and wind directions. The approach consisted of performing external aerodynamic CFD simulation and using the aerodynamic loads as inputs to a CAE simulation. The details of the methodology are presented along with results and correlation to experimental data from the wind tunnel.

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.

Automotive vehicle body electrophoretic (e-coat) and paint application has a high degree of complexity and expense in vehicle assembly. These steps involve coating and painting the vehicle body. Each step has multiple coatings and a curing process of the body in an oven. Two types of heating methods, radiation and convection, are used in the ovens to cure coatings and paints during the process. During heating stage in the oven, the vehicle body has large thermal stresses due to thermal expansion. These stresses may cause permanent deformation and weld/joint failure. Body panel deformation and joint failure can be predicted by using structural analysis with component surface temperature distribution. The prediction will avoid late and costly changes to the vehicle design. The temperature profiles on the vehicle components are the key boundary conditions used to perform structure analysis.

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.

Pickup trucks are designed with a taller ride height and a larger tire envelope compared to other vehicle types given the duty cycle and environment they operate in. These differences play an important role in the flow field around spinning wheels and tires and their interactions with the vehicle body. From an aerodynamics perspective, understanding and managing this flow field are critical for drag reduction, wheel design, and brake cooling. Furthermore, the validation of numerical simulation methodology is essential for a systematic approach to aerodynamically efficient wheel design as a standard practice of vehicle design. This paper presents a correlation the near-wheel flow field for both front and rear spinning wheels with two different wheel designs for a Ram Quad Cab pick-up truck with moving ground. Twelve-hole probe experimental data obtained in a wind tunnel with a full width belt system are compared to the predictions of numerical simulations.