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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.

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).

North American drivers particularly dislike wheel dust (brake dust on their wheels). For some vehicle lines, customer surveys indicate that wheel dust is a significant concern. For this reason, Ford and its suppliers are investigating the root causes of brake dust and developing test procedures to detect wheel dust issues up-front. Intuitively, it would appear that more brake wear would lead to more wheel dust. To test this hypothesis, a gage was needed to quantitatively measure the wheel dust. Gages such as colorimeters were evaluated to measure the brightness (L*) of the wheel, which ranged from roughly 70-80% (clean) to 10-20% (very dirty). Gage R&R's and subjective ratings by a panel of 30 people were used to validate the wheel dust gages. A city traffic vehicle test and an urban dynamometer procedure were run to compare the level of wheel dust for 10 different lining types on the same vehicle.

Recent applied mathematics research on the properties of the invertible shift-invariant discrete wavelet transform has produced new ways to visualize, separate, and synthesize impulsive sounds, such as thuds, slaps, taps, knocks, and rattles. These new methods can be used to examine the joint time-frequency characteristics of a sound, to select individual components based on their time-frequency localization, to quantify the components, and to synthesize new sounds from the selected components. The new tools will be presented in a non-mathematical way illustrated by two real-life sound quality problems, extracting the impulsive components of a windshield wiper sound, and analyzing a door closing-induced rattle.

High gas prices combined with demand for improved fuel economy have prompted increased interest in diesel engine applications for both light-duty and heavy-duty vehicles. The development of aftertreatment systems for these vehicles requires significant investments of capital and time. A reliable and robust qualification testing procedure will allow for more rapid development with lower associated costs. Qualification testing for DPFs has its basis in methods similar to DOCs but also incorporates a PM loading method and regeneration testing of loaded samples. This paper examines the effects of accelerated loading using a PM generator and compares PM generator loaded DPFs to engine dynamometer loaded samples. DPFs were evaluated based on pressure drop and regeneration performance for samples loaded slowly and for samples loaded under accelerated conditions. A regeneration reactor was designed and built to help evaluate the DPFs loaded using the PM generator and an engine dynamometer.

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.

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.

The USDOT and the Crash Avoidance Metrics Partnership-Vehicle Safety Communications 2 (CAMP-VSC2) Consortium (Ford, GM, Honda, Mercedes, and Toyota) initiated, in December 2006, a three-year collaborative effort in the area of wireless-based safety applications under the Vehicle Safety Communications-Applications (VSC-A) Project. The VSC-A Project developed and tested communications-based vehicle safety systems to determine if Dedicated Short Range Communications (DSRC) at 5.9 GHz, in combination with vehicle positioning, would improve upon autonomous vehicle-based safety systems and/or enable new communications-based safety applications.

The United States Department of Transportation (USDOT) and the Crash Avoidance Metrics Partnership-Vehicle Safety Communications 2 (CAMP-VSC2) Consortium (Ford, General Motors, Honda, Mercedes-Benz, and Toyota) initiated, in December 2006, a three-year collaborative effort in the area of wireless-based safety applications under the Vehicle Safety Communications-Applications (VSC-A) Project. The VSC-A Project developed and tested Vehicle-to-Vehicle (V2V) communications-based safety systems to determine if Dedicated Short Range Communications (DSRC) at 5.9 GHz, in combination with vehicle positioning, would improve upon autonomous vehicle-based safety systems and/or enable new communications-based safety applications.

The increasing trend toward electric and hybrid-electric vehicles (HEVs) has created unique challenges for NVH development and refinement. Traditionally, characterization of in-vehicle powertrain noise and vibration has been assessed through standard operating conditions such as fixed gear engine speed sweeps at varied loads. Given the multiple modes of operation which typically exist for HEVs, characterization and source-path analysis of these vehicles can be more complicated than conventional vehicles. In-vehicle NVH assessment of an HEV powertrain requires testing under multiple operating conditions for identification and characterization of the various issues which may be experienced by the driver. Generally, it is necessary to assess issues related to IC engine operation and electric motor operation (running simultaneously with and independent of the IC engine), under both motoring and regeneration conditions.

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.

To manage the function of a vehicle's engine, transmission, and related subsystems, almost all modern vehicles make use of one or more electronic controllers running embedded software, henceforth referred to as a Powertrain Controller System or PCS. Fully validating this PCS is a necessary step of vehicle development, and the validation process requires extensive amounts of testing. Traditionally, this validation testing is done with open-loop signal generators, powertrain dynamometers, and real vehicles. Such testing methods either cannot simulate complex control system interactions, or are expensive and subject to variability. To address these concerns while decreasing development time and improving vehicle quality, Ford Motor Company is placing increasing focus on validating a PCS through simulation. One such testing method is a Hardware-in-the-Loop (HIL) simulation, which mates the physical elements of a PCS to a real-time computer simulation of a powertrain.

Ford Motor Company’s assembly plants build vehicles in a certain sequence. The planned sequence for the plant’s trim and final assembly area is developed centrally and is sent to the plant several days in advance. In this work we present the study of two cases where the plant changes the planned sequence to cope with production constraints. In one case, a plant pulls ahead two-tone orders that require two passes through the paint shop. This is further complicated by presence in the body shop area of a unidirectional rotating tool that allows efficient build of a sequence “A-B-C” but heavily penalizes a sequence “C-B-A”. The plant changes the original planned sequence in the body shop area to the one that satisfies both pull-ahead and rotating tool requirements. In the other case, a plant runs on lean inventories. Material consumption is tightly controlled down to the hour to match with planned material deliveries.

Traditional automotive seat development has relied on a series of physical prototypes that are evaluated and refined in an iterative fashion. Costs are managed by sharing prototypes across multiple attributes. To further manage costs, many OEMs and Tier 1s have, over the past decade, started to investigate various levels of virtual prototyping. The change, which represents a dramatic paradigm shift, has been slow to materialize since virtual prototyping has not significantly reduced the required number of physical prototypes. This is related to the fact virtual seat prototyping efforts have been focused on only selected seat attributes - safety / occupant positioning and mechanical comfort are two examples. This requires that physical prototypes still be built for seat attributes like craftsmanship, durability, and thermal comfort.

A key ingredient in designing products that are more robust is a thorough knowledge of the physics of the ideal function of those products and the physics of the failure modes of those products. We refer to the mathematical functions describing this physics as the transfer functions for that product. Dimensional analysis (DA) is a well known, but often overlooked, tool for reducing the number of experiments needed to characterize a physical system. In this paper, we demonstrate how the application of DA can be used to reduce the size of a DOE needed to estimate transfer functions experimentally. Furthermore, the transfer function generated using DOEs with DA tend to be more general than those generated using larger DOEs directly on the design parameters. With ever-increasing competitive pressure and reduced product development time, a tool such as DA, which can dramatically reduce experimental cost, is an incredibly valuable addition to an engineers toolbox.

The ability to extract and evaluate the time history of structural deformations or crush during vehicle crashes represents a significant challenge to automotive safety researchers. Current methods are limited by the use of electro-mechanical devices such as string pots and/or linear variable displacement transducers (LVDT). Typically, one end of the transducer must be mounted to a point on the structure that will remain un-deformed during the event; the other end is then attached to the point on the structure where the deformation is to be measured. This approach measures the change in distance between these two points and is unable to resolve any movement into its respective X, Y, or Z directions. Also, the accuracy of electro-mechanical transducers is limited by their dynamic response to crash conditions. The photogrammetry technique has been used successfully in a wide variety of applications including aerial surveying, civil engineering and documentation of traffic accidents.

In Fall of 2001, a new emissions test cell was installed at Ford Motor Company that was specifically designed for precise low-level measurements (as described in Reference 6). The primary design focus for this cell was to ensure that optimal measurement capability was available to test vehicles that meet the stringent Partial Zero Emission Vehicle (PZEV) tailpipe requirements (NMOG = 10 mg/mile, NOx = 20 mg/mile). Over the past four years, there have been numerous improvements to the operational and Quality Assurance (QA) practices used in the PZEV Test Cell. Several investigations have also been performed to demonstrate the quality of its emissions measurements. Finally, a number of “lessons learned” have been documented from our experiences with PZEV measurements and with testing hybrid-electric vehicles. This paper summarizes these findings as a reference for others interested in low-level emissions measurements.

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.

A methodology is developed that incorporates high resolution CFD flowfield information and a particle trajectory simulation, aimed at addressing Paint Transfer Efficiency (PTE) for bell sprayers. Given a solid model for the bell sprayer, the CFD simulation, through automeshing, determines a high resolution Cartesian volume mesh (14-20 million cells). With specified values of the initial shaping air, transient and steady-state flow field information is obtained. A particle trajectory visualization tool called SpraySIM uses this complicated flowfield information to determine the particle trajectories of the paint particles under the influence of drag, gravity and electrostatic potential. The sensitivity of PTE on shaping air velocity, charge-to-mass ratio, potential, and particle diameter are examined.

People and their communities are looking for transportation solutions that reduce travel time, improve well-being and accessibility, and reduce emissions and traffic congestion. Although new mobility services like ride-hailing advertise improvements in these areas, closer inspection has revealed a discrepancy between industry claims and reality. Key decision-makers, including citizens, cities and enterprise, and mobility service providers have the opportunity to leverage connected vehicle and connected device data through cloud-based APIs. We propose a GHG data analytics framework that functions on top of a cloud platform to provide unique system-level perspectives on operating transportation services, from procuring the most environmentally and people friendly vehicles to scheduling and designing the services based on data insights.