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In the developement process, the engineer is required to design, validate and deliver the components for manufacturing, in an as short as possible lead time. For that, the engineer may use some available tools to save not only time, but also cost. This work presents a zero prototype approach applyied to a plastic component, whose main accomplishment was the decreasing of lead time development due to the intensive use of virtual tools (CAD/CAE). As a result, the product was delivered in a short time, with no need of building physical prototypes, thus reducing development cost.

In the current Ford Pro-Trailer Backup Assist (TBA) system, trailer hitch angle is determined utilizing the reverse camera of the vehicle. In addition to being sensitive to environmental factors such as lighting conditions and occlusion, the vision-based approach is difficult to be applied to gooseneck or fifth wheel trailers. In this paper, a yaw rate based hitch angle observer is proposed as an alternative sensing solution for TBA. Based on the kinematic model of the vehicle-trailer, an instantaneous hitch angle is first derived by utilizing vehicle yaw rate, trailer yaw rate, vehicle velocity and vehicle/trailer parameters provided by the TBA system. Due to signal errors and parameter uncertainties, this instantaneous hitch angle may be noisy, especially at lower vehicle speed.

An L18 Taguchi-style Design of Experiments (DOE) with eight factors was used to optimize exterior mirrors for wind noise and drag. Eighteen mirror properties were constructed and tested on a full size greenhouse buck at the Lockheed low-speed wind tunnel in Marietta, GA. Buck interior sound data and drag measurements were taken at 80 MPH wind speed (0° yaw angle). Key wind noise parameters were the fore/aft length of mirror housing and the plan view angle of the mirror housing's inboard surface. Key drag parameters were the fore/aft length of the mirror housing, the cross-section shape of the mirror pedestal, and the angle of the pedestal (relative to the wind).

Weld lines occur when melt flow fronts meet during the injection molding of plastic parts. It is important to investigate the weld line because the weld line area can induce potential failure of structural application. In this paper, a weld line factor (W-L factor) was adopted to describe the strength reduction to the ultimate strength due to the appearance of weld line. There were two engineering thermoplastics involved in this study, including one neat PP and one of talc filled PP plastics. The experimental design was used to investigate four main injection molding parameters (melt temperature, mold temperature, injection speed and packing pressure). Both the tensile bar samples with/without weld lines were molded at each process settings. The sample strength was obtained by the tensile tests under two levels of testing speed (5mm/min and 200mm/min) and testing temperatures (room temperature and -30°C). The results showed that different materials had various values of W-L factor.

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.

Warpage is the distortion induced by inhomogeneous shrinkage during injection molding of plastic parts. Uncontrolled warpage will result in dimensional instability and bring a lot of challenges to the mold design and part assembly. Current commercial simulation software for injection molding cannot provide consistently accurate warpage prediction, especially for semi-crystalline thermoplastics. In this study, the root cause of inconsistency in warpage prediction has been investigated by using injection molded polypropylene plaques with a wide range of process conditions. The warpage of injection molded plaques are measured and compared to the numerical predictions from Moldex3D. The study shows that with considering cooling rate effect on crystallization kinetics and using of the improved material model for residual stress calculations, good agreements are obtained between experiment and simulation results.

This paper proposes a film dynamics model for liquid film resulting from fuel spray impinging on a wall surface. It is based on a thin film assumption and uses numerical particles to represent the film to be compatible with the particle spray models developed previously. The Lagrangian method is adopted to govern the transport of the film particles. A new, statistical treatment was introduced of the momentum exchange between the impinging spray and the wall film to account for the directional distribution of the impinging momentum. This model together with the previously published models for outgoing droplets constitutes a complete description of the spray wall impingement dynamics. For model validation, films resulting from impinging sprays on a flat surface with different impingement angles were calculated and the results were compared with the corresponding experimental measurements.

Under various real-world scenarios, vehicles can become disabled and require towing. OEMs allow a few options for vehicle wrecker towing that include wheel lift tow using a stinger or towing on a flatbed. These methods entail multiple loading events that need to be assessed for damage to the towed vehicle. OEMs have several testing and evaluation methods in place for those scenarios with majority requiring physical vehicle prototypes. Recent focus to reduce product development time and cost has replaced the need for prototype testing with analytical verification methods. In this paper, the CAE method involving multibody dynamic simulation (MBDS) as well as finite element analysis (FEA) of vehicle flatbed operation, winching onto a flatbed, and stinger-pull towing are discussed.

Virtual Prototyping (VP) is an important method to assess the sound performance of possible designs in earlier stages of development. The common noise simulation with simple level determination can now be combined with subjective assessments that can be particularly interesting for noise content judgment. This paper will revise the literature found in this field that is applicable to the Engine Air Induction System inlet orifice noise and presents an example to illustrate the main advantages and difficulties in the implementation of VP.

The requirements of the automotive industry move along due to product competitiveness and this contributes to increase complexity in the requirements for evaluation. Simulation tools play a key role thanks to their versatility and multiple physical phenomena that can be represented. The axis of analysis for this paper is the problem of the interaction of airflow and water flow in the cowl/plenum/leaf screen components. Airflow is represented by HVAC system operating and water flow by the vehicle in torrential rain. Initially, one simulation is evaluated at a time, in one side, the airflow entering the HVAC system in which the amount of air entering is monitored and pressure drop, on the other, the water simulation on the vehicle, both using a Lagrangian CFD model (using with tools such as STAR CCM+® or Ansys Fluent®) Due to this, a CFD methodology was developed to evaluate the interaction of air and water flow.

Metal cutting/machining is a widely used manufacturing process for producing high-precision parts at a low cost and with high throughput. In the automotive industry, engine components such as cylinder heads or engine blocks are all manufactured using such processes. Despite its cost benefits, manufacturers often face the problem of machining chips and cutting oil residue remaining on the finished surface or falling into the internal cavities after machining operations, and these wastes can be very difficult to clean. While part cleaning/washing equipment suppliers often claim that their washers have superior performance, determining the washing efficiency is challenging without means to visualize the water flow. In this paper, a virtual engineering methodology using particle-based CFD is developed to address the issue of metal chip cleanliness resulting from engine component machining operations. This methodology comprises two simulation methods.

The increasing use of aluminum in the design of Body In White (BIW) structures created the need to develop and verify repair methodologies specific to this substrate. Over the past century, steel has been used as the primary material in the production of automotive BIW systems. While repair methods and techniques in steel have been evolving for decades, aluminum structural repair requires special attention for such common practices as welding, mechanical fastening, and the use of adhesives. This paper outlines some of the advanced verification and testing methodologies used to develop collision repair procedures for the aluminum 2003 Jaguar XJ sedan. It includes the identification of potential failure modes found in production and customer applications, the formulation of testing methodologies, CAE verification testing and component subsystem prove-out. The objective of the testing was to develop repair methodologies that meet or exceed production system performance characteristics.

As the complexity of automotive chassis control systems increases with the introduction of technologies such as yaw and roll stability systems, processes for model-based development of chassis control systems becomes an essential part of ensuring overall vehicle safety, quality, and reliability. To facilitate such a model-based development process, a vehicle modeling framework intended for chassis control development has been created. This paper presents a design methodology centered on this modeling framework which has been applied to real world driving events and has demonstrated its capability to capture vehicle dynamic behavior for chassis control development applications.

Through the use of hybrid technology, Ford Motor Company continues to realize enhanced vehicle fuel economy while meeting customer performance and drivability targets. As is characteristic of all Ford Hybrid Electric Vehicles (HEVs), the basis for resolving these competing requirements resides with its Vehicle System Control (VSC) strategy. This strategy implements complex high-level executive controls to coordinate and optimize the desired operational state of the major HEV powertrain subsystems. To ensure that the VSC software meets its intended functionality, a software validation process developed at Research and Advanced Engineering has been integrated as part of the vehicle controls development process. In this paper, this VSC software validation process implemented for a next generation hybrid powertrain is presented. First, an overview of the hybrid powertrain application and the VSC software architecture is introduced.

A computational model of a mid-size sport utility vehicle was developed using MADYMO. The model includes a detailed description of the suspension system and tire characteristics that incorporated the Delft-Tyre magic formula description. The model was correlated by simulating a vehicle suspension kinematics and compliance test. The correlated model was then used to simulate a J-turn vehicle dynamics test maneuver, a roll and non-roll ditch test, corkscrew ramp and a lateral trip test, the results of which are presented in this paper. The results indicate that MADYMO is able to reasonably predict the vehicle and occupant responses in these types of applications and is potentially suited as a tool to help setup a suite of vehicle configurations and test conditions for rollover sensor testing. A suspension system sensitivity study is presented for the laterally tripped non-roll event.

An advanced powertrain cooling system with appropriate control strategy and active actuators allows greater flexibility in managing engine temperatures and operating near constraints. An organized controls development process is necessary to allow comparison of multiple configurations to select the best way forward. In this work, we formulate, calibrate and validate a Model Predictive Controller (MPC) for temperature regulation and constraint handling in an advanced cooling system. A model-based development process was followed; where the system model was used to develop and calibrate a gain scheduled linear MPC. The implementation of MPC for continuous systems and the modification related to implementing switching systems has been described. Multiple hardware configurations were compared with their corresponding control system in simulations. The system level requirements were translated into MPC calibration parameters for consistent comparison between multiple configurations.

A new methodology to predict vehicle interior wind noise using CFD results has been developed. The CFD simulation replaces wind tunnel testing for providing flow field information around vehicle greenhouse. A loadcase model based on the CFD results is used to excite an SEA vehicle model. This new approach has been demonstrated on a production vehicle with success for the frequency range of 250-10K Hz. The CAE prediction of interior wind noise agrees within 0.2 sones from wind tunnel testing. The model has been used to evaluate wind noise performance with different door glass design parameters. A glass thickness change from 3.8 mm to 4.8 mm results in 1.1 sones improvement, which agrees well to 1.4 sones improvement from testing. Laminated glass with about 3 times higher damping results in 2.5 sones improvement. This methodology using CFD results can be used in the early stage of product development to impact designs.

Among the development phases of an automotive vehicle one can point out the definition of the main characteristics of its suspensions like for example the suspension kinematics and compliances properties. Suspension definition phase can be understood as the following scenario: given a suspension type, which hard points (geometric) and what values of stiffness for the whole system will result in a desired dynamic behavior for the vehicle as well as production feasibility. This present work intends to show the influence of some suspension properties on the global dynamic behavior of the vehicle, having as a target an efficient suspension design. In terms of global dynamic behavior this work point out some control parameters, which describe the vehicle transient and steady-state properties. Those parameters are: Yaw phase lag, understeer gradient, Steady state acceleration gain and yaw overshoot during a maneuver like brake in a turn and power-off in a curve.

A new capability to simulate transient, non-linear handling maneuvers analytically, and dynamically display the vehicle's response with 3-dimensional animated graphics has been developed and is being utilized by Ford Motor Company. The implementation of this capability, which includes complete affects of steering and suspension kinematics, individual bushing compliances, non-linear shock absorber and jounce bumper characteristics, and transient tire force and moment data, represents a new frontier in the development of light truck and passenger car vehicles. Development of this model lends itself to analytical evaluations of numerous types of handling related maneuvers such as classical or linear behavior, transient and limit stability analysis, and special situations such as cross wind stability, torque steer, and vehicle drift characteristics.

Onboard, embedded cellular modems are enabling a range of new connectivity features in vehicles and rich, real-time data set transmissions from a vehicle’s internal network up to a cloud database are of particular interest. However, there is far too much information in a vehicle’s electrical state for every vehicle to upload all of its data in real-time. We are thus concerned with which data is uploaded and how that data is processed, structured, stored, and reported. Existing onboard data processing algorithms (e.g. for DTC detection) are hardcoded into critical vehicle firmware, limited in scope and cannot be reconfigured on the fly. Since many use cases for vehicle data analytics are still unknown, we require a system which is capable of efficiently processing and reporting vehicle deep data in real-time, such that data reporting can be switched on/off during normal vehicle operation, and that processing/reporting can be reconfigured remotely.