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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).

On the development process of truck vehicles, the dynamic behavior must be considered together with the costs involved in this development. Objective measurements, subjective evaluations and CAE simulations are used in order to support this development process. Ride comfort, acceleration and braking performance, handling and NVH are examples of attributes considered in the dynamic behavior evaluation of a tuck. Some characteristics of steering column vibration, noise and harshness are relevant to guarantee driver comfort level and vehicle safety. In this work, CAE models validated by experimental measurements were used to identify cab and vehicle modes of vibration which have significant influence on steering column response. Using this procedure, an alternative was proposed in order to decrease the amplitudes of cab and steering column vibration.

Vehicle chassis mounted cantilevered components should meet two critical design targets: 1) NVH criterion to avoid resonance with road noise and engine vibration and 2) satisfied durability performance to avoid any incident in structure failure and dysfunction. Generally, two types of testing are performed to validate chassis mounted cantilevered component in the design process: shaker table testing and vehicle proving ground testing. Shaker table testing is a powered vibration endurance test performed with load input summarized from real proving ground data and accurate enough to replicate the physical test. The proving ground test is typically performed at critical milestones with full vehicles. Most tests are simplified lab testing to save cost and effort. CAE procedures that virtually replicate these lab tests is even more helpful in the design verification stages.

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.

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.

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.

Recent trends show a growing demand for improved powertrain noise and vibration quality. In particular, there is little customer acceptance of vibration and noise (“boom”) at engine idle speeds. CAE analysis is being used increasingly as an aid for reducing overall vehicle level responses. Traditionally, analytical idle response is evaluated for only one particular engine order at a time. An efficient Excel based tool called VeCTRA (Vehicle Cascade & Target Response Analysis) was developed to accurately assess the effects of multiple powertrain orders on the vehicle level idle response. VeCTRA is capable of predicting the overall vehicle level response (tactile and acoustic) as well as determining the contribution from each engine order and the specific component excitations within an order. VeCTRA is capable of using analytical or experimentally measured sensitivity and/or excitation data.

Two finite element methodologies for simulating oil-canning tests on closure assemblies are presented. Reflecting the experimental conditions, the simulation methodologies assume load-controlled situations. One methodology uses an implicit finite-element code, namely ABAQUS®, and the other uses an explicit code, LS-DYNA®. It is shown that load-displacement behavior predicted by both the implicit and explicit codes agree well with experimental observations of oil-canning in a hood assembly. The small residual dent depth predictions are in line with experimental observations. The method using the implicit code, however, yields lower residual dent depth than that using the explicit code. Because the absolute values of the residual dent depths are small in the cases examined, more work is needed, using examples involving larger residual dent depth, to clearly distinguish between the two procedures.

Traditionally, Knee Air Bag (KAB) is constructed of a woven nylon or polyester fabric. Recently, Ford developed an injection molded air bag system for the passenger side called Active Glove Box (AGB). This system integrates a plastic bladder welded between the glove box outer and inner doors. This new system is smaller and lighter, thus improving the roominess and other creature comforts inside the passenger cabin while providing equivalent restraint performance as traditional knee airbag system. This patented technology allows positioning of airbags in new locations within the vehicle, thus giving more freedom to designers. The first application of this technology was standard equipment on the 2015 Ford Mustang. Given that this technology is first in the industry, it was a challenge to design, test and evaluate the performance of the system as there is no benchmark to compare this technology. A CAE driven design methodology was chosen to overcome this challenge.

The paradigm for utilizing computer-aided engineering (CAE) to analyze automotive steering and suspension designs is rapidly changing. CAE's role has expanded beyond mere analysis to designing and improving product reliability and robustness. This paper presents an approach for avoiding the steering wheel nibble failure mode by improving robustness and therefore reliability through the use of CAE. For this paper, reliability is the ability of the system to avoid failure modes. A failure mode is any customer perceived deviation from ideal and avoiding failure modes naturally improves reliability. [1]

For many years, the use of in-mold fasteners has been avoided for various reasons including: not fully understanding the load cases in the part, the fear of quality issues occurring, the need for servicing, or the lack of understanding the complexity of all failure modes. The most common solution has been the use of secondary operations to provide attachments, such as, screws, metal clips, heat staking, sonic welding or other methods which are ultimately a waste in the process and an increase in manufacturing costs. The purpose of this paper is to take the reader through the design process followed to design an in-molded attachment clip on plastic parts. The paper explores the design process for in-molded attachment clips beginning with a design concept idea, followed by basic concept testing using a desktop 3D printer, optimizing the design with physical tests and CAE analysis, and finally producing high resolution 3D prototypes for validation and tuning.

This paper reports a study of the dynamic characteristics of body mounts in body on frame vehicles and their effects on structural and occupant CAE results. The body mount stiffness and damping are computed from spring-damper models and component test results. The model parameters are converted to those used in the full vehicle structural model to simulate the vehicle crash performance. An effective body mount in a CAE crash model requires a set of coordinated damping and stiffness to transfer the frame pulse to the body. The ability of the pulse transfer, defined as transient transmissibility[1]1, is crucial in the early part of the crash pulse prediction using a structural model such as Radioss[2]. Traditionally, CAE users input into the model the force-deflection data of the body mount obtained from the component and/or full vehicle tests. In this practice, the body mount in the CAE model is essentially represented by a spring with the prescribed force-deflection data.

Squeak and rattle is one of the major concerns in vehicle design for customer satisfaction. Traditionally squeak and rattle problems are found and fixed at a very late design stage due to lack of up-front CAE prevention and prediction tools. A research work at Ford reveals a correlation between the squeak and rattle performance and diagonal distortions at body closure openings and fastener accelerations in an instrument panel. These findings make it possible to assess squeak and rattle performance implications between different body designs using body-in-prime (B-I-P) and vehicle low frequency noise, vibration and harshness (NVH) CAE models at a very early design stage. This paper is concerned with applications of this squeak and rattle assessment method for up-front body designs prior to a prototype stage.

This paper presents a method of using CAE to determine the pre-load and torque applied to a U-Bolt rear Spring Seat. In this paper it is review two U-bolt design and the stresses generated by the pre-load torque applied, based in this study a process to determine the minimal preload and the torque is discussed. By this process it is possible to determine the minimum Torque and the correct pre-load in the U-Bolt element and assuring the correct fastening of the components avoiding over stress in the Bar elements.

Virtual Verification (VV) of engineering designs is a critical enabler in the Product Development (PD) process to reduce the time-to-market in a cost efficient manner. Reliance on cost effective VV methods have significantly increased with increased pressure to meet customer expectations for new products at reduced PD budgets. Computer Aided Engineering (CAE) is one such VV method that affords an engineer to make decisions about the ability of the designs to meet the design criteria even before a prototype is built. The first step of the CAE process is meshing which is a time consuming, manual and laborious process. Also mesh development time and accuracy significantly varies with the (1) component (trim body, engine, suspension, brakes, etc.), (2) features predominantly occurring in the component (welds, ribs, fillets, etc.), meshing guidelines based on which the model needs to be developed (durability, safety, NVH, etc.), and the expertise of the meshing engineer involved.

Weight is a major factor during the development of Automotive Powertrains due to stringent fuel economy requirements. Light weighting constitutes a challenge to the engineering community when trying to deliver quieter powertrains. For this reason, the NVH (Noise Vibration Harshness) CAE engineers are adopting advanced vibro-acoustic simulation methods combined with topology optimization methods to drive the design of the under hood components for Noise Vibration and Harshness. Vibro-acoustic computational methods can be complex and require significant computation effort. Computation of Equivalent Radiated Power (referred to as ERP) is a simplified method to assess maximum dynamic radiation of components for specific excitations in frequency response analysis which in turn affects radiated sound. Topology Optimization is a mathematical technique used to find the best material distribution for structural systems in order to deliver a specific objective under clearly defined constraints.

Recently, in the automotive industry the usage of CAE models in the development of a product has grown significantly. Virtual models allow the auto makers to speed up the programs and also to predict desired characteristics of the product. However in order to build up a reliable model, capable to reproduce in a detailed manner maneuvers done subjectively, a solid procedure to validate the model as well as a robust tire modeling are required. Once with a model validated, detailed enough at suspension, steering and other sub-systems level, all others sources of variation must come from the tire model. And at this moment, properties of the kind of tire modeling can be pointed out. This work shows one approach to have a good validation of a CAE model at sub-systems level and mainly, discuss the properties and limitations of different tire modeling for different maneuvers, including Pacjeka 94, B-Spline and Delft.