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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).

Wheel Fight is the undesirable rotational response of a vehicle's steering wheel due to road input at any or all of the road/wheel tire patches. The type of road input that will cause wheel fight comes in two forms: continuous rough road surfaces such as broken concrete or transient inputs such as pot-holes and tar strips. An objective method to quantify a vehicle's wheel fight sensitivity would be of great value to the vehicle development engineer. To that end, a study was conducted on Ford's Vehicle Vibration Simulator (VVS) to gather subjective responses and use those as a basis for correlation to an objective metric. One road surface known to induce wheel fight consists of using a rubber strip and driving over it while impacting only one side of the vehicle. Under this condition, steering wheel data was acquired on five different light trucks from which paired comparison studies were conducted.

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.

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.

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.

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.

Ford Motor Company has investigated a series hybrid electric vehicle (SHEV) configuration to move further toward powertrain electrification. This paper first provides a brief overview of the Vehicle System Controls (VSC) architecture and its development process. The paper then presents the energy management strategies that select operating modes and desired powertrain operating points to improve fuel efficiency. The focus will be on the controls design and optimization in a Model-in-the-Loop environment and in the vehicle. Various methods to improve powertrain operation efficiency will also be presented, followed by simulation results and vehicle test data. Finally, opportunities for further improvements are summarized.

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.

Improving passenger safety inside vehicle cabins requires continuously monitoring vehicle seat occupancy statuses. Monitoring a vehicle seat’s occupancy status includes detecting if the seat is occupied and classifying the seat’s occupancy type. This paper introduces an innovative non-intrusive technique that employs capacitive sensing and an occupancy classifier to monitor a vehicle seat’s occupancy status. Capacitive sensing is facilitated by a meticulously constructed capacitance-sensing mat that easily integrates with any vehicle seat. When a passenger or an inanimate object occupies a vehicle seat equipped with the mat, they will induce variations in the mat’s internal capacitances. The variations are, in turn, represented pictorially as grayscale capacitance-sensing images (CSI), which yield the feature vectors the classifier requires to classify the seat’s occupancy type.

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.

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.

Vehicle thermal loads in sunny climates are strongly influenced by the absorption of solar thermal energy. Reduction of the absorptivity in the near infrared (IR) spectrum would decrease vehicle soak temperatures, reduce air conditioning power consumption and not affect the vehicle visible spectrum radiation properties (color). The literature [1] indicates that paint formulations with carbon-black pigment removed or reduced can be made to be reflective to near infrared frequencies. Experiments indicated that the reflectivity can be improved with existing basecoats and primers. Experiments and numerical simulations indicate that vehicle soak temperatures can be reduced by over 2 °C with existing basecoats and primers.

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.

Locations of key body segments of Hybrid III dummies used in FMVSS 208 compliance tests and NCAP tests were measured and subjected to statistical analysis. Mean clearance dimensions and their standard deviations for selected body segments of driver and passenger occupants with respect to selected vehicle surfaces were determined for several classes of vehicles. These occupant locations were then investigated for correlation with impact responses measured in crash tests and by using a three dimensional human-dummy mathematical model in comparable settings. Based on these data, the importance of some of the clearance dimensions between the dummy and the vehicle surfaces was determined. The study also compares observed Hybrid III dummy positions within selected vehicles with real world occupant positions reported in published literature.

This paper summarizes the validation of prototype vehicle-to-infrastructure (V2I) safety applications based on Dedicated Short Range Communications (DSRC) in the United States under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). After consideration of a number of V2I safety applications, Red Light Violation Warning (RLVW), Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure Warning (RSZW/LC) were developed, validated and demonstrated using seven different vehicles (six passenger vehicles and one Class 8 truck) leveraging DSRC-based messages from a Road Side Unit (RSU). The developed V2I safety applications were validated for more than 20 distinct scenarios and over 100 test runs using both light- and heavy-duty vehicles over a period of seven months. Subsequently, additional on-road testing of CSW on public roads and RSZW/LC in live work zones were conducted in Southeast Michigan.

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.

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.

Electric vehicles are highly sensitive to variations in environmental factors (like temperature, drive style, grade, etc.). The distribution of real-world range of electric vehicles due to these environmental factors is an important consideration in target setting. This distribution can be obtained by running several simulations of an electric vehicle for a number of high-frequency velocity, grade, and temperature real-world trip profiles. However, in order to speed up simulation time, a unique set of drive profiles that represent the entire real-world data set needs to be developed. In this study, we consider 40,000 unique velocity and grade profiles from various real-world applications in EU. We generate metadata that describes these profiles using trip descriptor variables. Due to the large number of descriptor variables when considering second order effects, we normalize each descriptor and use principal component analysis to reduce the dimensions of our dataset to six components.

An intervention of vehicle stability control systems is more likely on slippery surfaces, e.g. when the road is covered with snow or ice. Contrary to testing on dry asphalt, testing on such surfaces is restricted by weather and proving grounds. Another drawback in testing is the reproducibility of measurements, since the surface condition changes during the tests, and the vehicle reaction is more sensitive on slippery surface. For that, simulation enables a good pre-assessment of the control systems independent from testing conditions. Essential for this is a good knowledge about the contact between vehicle and road, meaning a good tyre model and a reasonable set of tyre model parameters. However, the low friction surface has a high variation in the friction coefficient. For instance, the available lateral acceleration on scraped ice could vary between 0.2 and 0.4 g within a day. These facts lead to the idea of using generic tyre parameters that vary in a certain range.