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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).

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.

This work describes a single camera based object distance estimation system. As technology on vehicles is constantly advancing on the road to autonomy, it is critical to know the locations of objects in 3D space for safe behavior of the vehicle. Though significant progress has been made on object detection in 2D sensor space from a single camera, this work additionally estimates the distance to said object without requiring stereo vision or absolute knowledge of vehicle motion. Specifically, our proposed system is comprised of three modules: vision based ego-motion estimation, object-detection, and distance estimation. In particular, we compensate for the vehicle ego-motion by using pin-hole camera model to increase the accuracy of the object distance estimation.

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.

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.

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.

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.

In structural design optimization, it is challenging to determine the optimal dimensions and material for each component simultaneously. Material selection of each part is always formulated as a categorical design variable in structural optimization problems. However, it is difficult to solve such mixed-variable problems using the metamodelbased strategy, because the prediction accuracy of metamodels deteriorates significantly when categorical variables exist. This paper investigates two different strategies of mixed-variable metamodeling: the “feature separating” strategy and the “all-in-one” strategy. A supervised learning-enhanced cokriging method is proposed, which fuses multi-fidelity information to predict new designs’ responses. The proposed method is compared with several existing mixed-variable metamodeling methods to understand their pros and cons. These methods include Neural Network (NN) regression, Classification and Regression Tree (CART) and Gaussian Process (GP).

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.

The paper describes a new tire cornering/traction trailer designed to measure the traction and steering performance of passenger car tires, outlines related test methods, and provides supporting test data. A general set of specifications is given for the entire test system. The major subsystems described are the trailer with its versatile suspension; the tow vehicle and its performance capabilities; the transducer system which measures the normal load, lateral force, fore-and-aft force, aligning torque, steer angle and speed; and the instrumentation. The calibration method is described. The test methods described include those for straight-line braking, maximum lateral traction, steady state and transient steering response, and combined braking and cornering traction. Supporting data and discussion are presented for each test method.

Thermally sprayed coatings have used in place of iron bore liners in recent aluminum engine blocks. The coatings are steel-based, and are sprayed on the bore wall in the liquid phase. The thermal response of the block structure determines how rapidly coatings can be applied and thus the investment and floor space required for the operation. It is critical not to overheat the block to prevent dimensional errors, metallurgical damage, and thermal stress cracks. This paper describes an innovative finite element procedure for estimating both the substrate temperature and residual stresses in the coating for the thermal spray process. Thin layers of metal at a specified temperature, corresponding to the layers deposited in successive thermal spray torch passes, are applied to the substrate model, generating a heat flux into the block. The thickness, temperature, and application speed of the layers can be varied to simulate different coating cycles.

Over the past five years, the US Automotive Materials Partnership (USAMP) has brought together representatives from DaimlerChrysler, General Motors, Ford Motor Company and over 40 other participant companies from the Mg casting industry to create and test a low-cost, Mg-alloy engine that would achieve a 15 - 20 % Mg component weight savings with no compromise in performance or durability. The block, oil pan, and front cover were redesigned to take advantage of the properties of both high-pressure die cast (HPDC) and sand cast Mg creep- resistant alloys. This paper describes the alloy selection process and the casting and testing of these new Mg-variant components. This paper will also examine the lessons learned and implications of this pre-competitive technology for future applications.

The concept of vehicle understeer and oversteer has been well studied and equations, test methods, and test results have been published for many decades. This concept has a specific definition in the steady-state driving range as opposed to quantification in highly transient limit handling events. There have been specific test procedures developed and employed by automotive engineers for decades on how to quantify understeer. These include the constant radius method, the constant steering wheel angle/variable speed method, the constant speed/ variable radius method, and the constant speed/variable steer method. These methods are very good for calculating the understeer gradient but care must be taken in interpreting the result at the limits of tire traction since lateral tire forces can be reduced on a drive axle when significant throttle is applied.

The Ford Spin Torsional NVH TEST Facility developed and completed in 1999 as a state-of-the-art powertrain NVH development facility(1). Since then, various designed capabilities have been verified with test vehicles for multiple applications to facilitate powertrain NVH development. This paper describes fundamental capabilities of the test facility, including input module to simulate engine torque signatures of arbitrary engines (“virtual engine” capability) and absorbing dynamometer systems, functioning as a precision 4WD/AWD chassis dynamometer. The correlation between road test/chassis dynamometer test and Spin-Torsional test is then illustrated, verifying high correlation of vehicle/sub-system responses between conventional vehicle testing and Spin-Torsional test results.

Physical tests and analysis of a typical automobile latch and outside handle release mechanism are performed to determine the effects of friction on the systems dynamic response. An automobile side door outside handle, outside handle rod linkage, and latch are mounted to a rigid fixture that is constrained by bearings to a “drop tower.” The fixture is released from controlled heights onto a compliant impact surface resulting in a constant duration acceleration transient of varying amplitude. An instrumented door latch striker is designed into the fixture to engage the latch. The pre-drop interface load between the latch and striker is adjusted allowing its effect on the dynamic behavior to be characterized. The latch position and the interface load between the latch and striker are monitored throughout the test. The results of the test show that friction forces internal to the latch significantly affect the quasistatic and dynamic behavior of the latching system.

This paper deals with the dynamic characterization of an automotive shock absorber, a continuation of an earlier work [1]. The objective of this on-going research is to develop a testing and analysis methodology for obtaining dynamic properties of automotive shock absorbers for use in CAE-NVH low-to-mid frequency chassis models. First, the effects of temperature and nominal length on the stiffness and damping of the shock absorber are studied and their importance in the development of a standard test method discussed. The effects of different types of input excitation on the dynamic properties of the shock absorber are then examined. Stepped sine sweep excitation is currently used in industry to obtain shock absorber parameters along with their frequency and amplitude dependence. Sine-on-sine testing, which involves excitation using two different sine waves has been done in this study to understand the effects of the presence of multiple sine waves on the estimated dynamic properties.

The process parameters to manufacture structural aluminum alloys are critical to their ductility. In particular, quench rate after solution heat treatment impacts the extent of grain boundary precipitation and the formation of precipitate free zone (PFZ) during later artificial aging. Cu-containing 6XXX alloys used for high strength automotive applications are quench sensitive as the Cu addition leads to Q-phase precipitation at grain boundaries, resulting in loss of ductility, which can negatively affect downstream manufacturing steps such as automotive joining and forming processes. Self-piercing rivet (SPR) joining, is a single step, spot joining process used to mechanically connect sheet materials together in automotive body structures. Ductility has been identified as an important metric of material rivet-ability or the ability to make a successful, crack-free SPR joint.