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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.

Almost all published results of wake measurements for ground vehicles or similar shapes have included very limited information on streamwise development of wake structures. This is typically a result of the fact that the wake measurements have been conducted as parts of particular vehicle development efforts. So the focus has been on the incremental changes in the wakes associated with alternative geometries or buildup of various parts. The objectives are typically reached by limiting the surveys to a single streamwise plane. The present study, by contrast, is a study of wake development for a series of relatively simple rectangular shapes with radiused edges with a systematic variation in the ratio of height to width or “Aspect Ratio”.

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.

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.

A wind noise model of a vehicle has been developed using Statistical Energy Analysis (SEA) with measured turbulent pressure data as the source input. Empirical formulas are used to scale the input data for changes in flow and design parameters. Wind tunnel tests have been conducted on a standard and modified vehicle to validate the SEA model and the input scaling. The results show good correlation with both the exterior turbulent pressure levels and the interior sound pressure levels across the audio frequency range.

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.

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.

The air-hybrid engine absorbs the vehicle kinetic energy during braking, puts it into storage in the form of compressed air, and reuses it to assist in subsequent vehicle acceleration. In contrast to electric hybrid, the air hybrid does not require a second propulsion system. This approach provides a significant improvement in fuel economy without the electric hybrid complexity. The paper explores the fuel economy potential of an air hybrid engine by presenting the modeling results of a 2.5L V6 spark-ignition engine equipped with an electrohydraulic camless valvetrain and used in a 1531 kg passenger car. It describes the engine modifications, thermodynamics of various operating modes and vehicle driving cycle simulation. The air hybrid modeling projected a 64% and 12% of fuel economy improvement over the baseline vehicle in city and highway driving respectively.

To support its recycling efforts, Ford Motor Company is using a Raman based instrument, the RP-1, co-developed with SpectraCode Inc. to identify unknown polymeric parts. Our recycling initiative involves detailed dismantling of our vehicles into individual parts, calculating the percentage recyclability and making recommendations for the future use of recycled polymers. While Ford has voluntarily adopted the SAE J1344 marking protocol for identifying part material composition, a large number of unmarked parts still exist and require identification. This identification is being done with the help of RP-1. To facilitate this identification, we have generated an accurate reference library of Raman spectra for comparison to those of unknown materials. This paper will describe the techniques that were used to develop and refine the RP-1 reference library to identify automotive polymers, especially black/dark plastics.

The Corrosion Task Force of the Automotive/Steel Partnership has developed the SAE J2334 cyclic laboratory test for evaluating the cosmetic corrosion resistance of auto body steel sheet. [Ref. 1] Since the publishing of this test in 1997, further work has improved the precision of J2334. In this paper, the results of this work along with the revisions to the J2334 test will be discussed.

This paper presents an uncertainty analysis of aerodynamic force and moment coefficients for production vehicles in an automotive wind tunnel. The analysis uses a Monte Carlo numerical simulation technique. Emphasis is placed on defining the elemental random and systematic uncertainties from the tunnel’s instrumentation, understanding how they propagate through the data reduction equations and under what conditions specific elemental error sources are or are not important, and how the approach to data reduction influences the overall uncertainties in the coefficients. The results of the analysis are used to address the issue of averaging time in the context of maintaining a maximum allowable uncertainty level. Also, a maximum error requirement in the vehicle’s installation is suggested to allow the use of rapid but approximate vehicle alignment methods without incurring errors that exceed the data uncertainty. Observed reproducibility results are presented spanning a 16 month period.

This paper compares the results from three human factors studies conducted in a motion-based simulator in 2008, 2014 and 2023, to highlight the trends in driver's response to Forward Collision Warning (FCW). The studies were motivated by the goal to develop an effective HMI (Human-Machine Interface) strategy that enables the required driver's response to FCW while minimizing the level of annoyance of the feature. All three studies evaluated driver response to a baseline-FCW and no-FCW conditions. Additionally, the 2023 study included two modified FCW chime variants: a softer FCW chime and a fading FCW chime. Sixteen (16) participants, balanced for gender and age, were tested for each group in all iterations of the studies. The participants drove in a high-fidelity simulator with a visual distraction task (number reading). After driving 15 minutes in a nighttime rural highway environment, a surprise forward collision threat arose during the distraction task.

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.

The 2nd Automotive CFD Prediction workshop (AutoCFD2) was organized to improve the state-of-the-art in automotive aerodynamic prediction. It is the mission of the workshop organizing committee to drive the development and validation of enhanced CFD methods by establishing publicly available standard test cases for which high quality on- and off-body wind tunnel test data is available. This paper reports on the AutoCFD2 workshop for the Ford DrivAer test case. Since its introduction, the DrivAer quickly became the quasi-standard for CFD method development and correlation. The Ford DrivAer has been chosen due to the proven, high-quality experimental data available, which includes integral aerodynamic forces, 209 surface pressures, 11 velocity profiles and 4 flow field planes. For the workshop, the notchback version of the DrivAer in a closed cooling, static floor test condition has been selected.

Automobile customers are looking for higher performance and quieter comfortable rides. The driveline of a vehicle can be a substantial source of NVH issues. This paper provides an understanding of a driveline noise issue which can affect any variant of driveline architecture (FWD, AWD, RWD and 4X4). This metallic noise is mostly present during the take-off and appropriately termed as ting noise. This noise was not prevalent in the past. For higher fuel economy, OEMs started integrating several components for lighter subsystems. This in effect made the system more sensitive to the excitation. At present the issue is addressed by adding a ting washer in the interface of the wheel hub bearings and the halfshafts. This paper explains the physics behind the excitation and defines the parameters that influence the excitation. The halfshaft and the wheel hub are assembled with a specified hub nut torque.

The three-dimensional non-reacting flow field inside a typical dual-monolith automotive catalytic converter was simulated using finite difference analysis. The monolithic brick resistance was formulated from the pressure gradient of fully developed laminar duct-flow and corrected for the entrance effect. This correlation was found to agree with experimental pressure drop data, and was introduced as an additional source term into the non-dimensional momentum governing equation within the brick. Flow distribution within the monolith was found to depend strongly on the diffuser performance, which is a complex function of flow Reynolds number, brick resistance, and inlet pipe length and bending angles. A distribution index was formulated to quantify the degree of non-uniformity at selected test cases covering ranges of flow conditions, brick types, and inlet conditions.

The Ford Motor Company Rolling Road Wind Tunnel (RRWT) is a state-of-the-art aerodynamic wind tunnel test facility in Allen Park, Michigan. The RRWT has operated since January 2022 and is designed for passenger and motorsport vehicle development. The test facility includes an office area, three secure customer vehicle preparation bays, a garage area, a vehicle frontal area measurement system, and a full-scale ¾ open jet wind tunnel. The wind tunnel features an interchangeable single belt and 5-belt Moving Ground Plane (MGP) system with an integrated 6-component balance, a two-position nozzle, boundary layer removal systems, and two independent flow traverse systems. Each flow traverse has a large horizontal box beam and vertical Z-strut that can position the flow traverse accurately within the test volume.

Industry trends towards lighter, more aerodynamically efficient road vehicles have the potential to degrade a vehicle’s response to crosswinds. In this paper, a methodology is outlined that indirectly couples a computational fluid dynamics (CFD) simulation of the vehicle’s aerodynamic characteristics with a multi-body dynamics simulation (MBD) to determine yaw, roll and pitch response characteristics during a severe crosswind event. This one-way coupling approach mimics physical test conditions outlined in open loop test procedure ISO 12021:2010 that forms part of the vehicle sign-off criterion at Ford Motor Company. The methodology uses an overset mesh CFD method to drive the vehicle through a prescribed crosswind event, providing unfiltered predictions of vehicle force and moment responses that are used as applied forces in the MBD model. The method does not account for changes in vehicle attitude due to applied aerodynamic forces and moments.