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Dimethyl ether (DME) is an alternative to diesel fuel for use in compression-ignition engines with modified fuel systems and offers potential advantages of efficiency improvements and emission reductions. DME can be produced from natural gas (NG) or from renewable feedstocks such as landfill gas (LFG) or renewable natural gas from manure waste streams (MANR) or any other biomass. This study investigates the well-to-wheels (WTW) energy use and emissions of five DME production pathways as compared with those of petroleum gasoline and diesel using the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET®) model developed at Argonne National Laboratory (ANL).

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.

Scalograms based on shift-invariant orthonormal wavelet transforms can be used to analyze impulsive and transient sounds in the presence of more stationary sound backgrounds, such as wind noise or drivetrain noise. The visual threshold of detection for impulsive features on the scalogram (signal energy content vs. time and frequency,) is shown to be similar to the audible threshold of detection of the human auditory system for the corresponding impulsive sounds. Two examples of impulsive sounds in a realistic automotive sound background are presented: automotive interior rattle in a vehicle passenger compartment, and spark knock recorded in an engine compartment.

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.

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.

A DMS (Driver Monitoring System) is one of the most important safety features that assist in the monitoring functions and alert drivers when distraction or drowsiness is detected. The system is based in a DSMC (Driver Status Monitoring Camera) mounted in the vehicle's dash, which has a predefined set of operational requirements that must be fulfilled to guarantee the correct operation of the system. These conditions represent a trade space analysis challenge for each vehicle since both the DSMC and the underlying vehicle’s requirements must be satisfied. Relying upon the camera’s manufacturer evaluation for every iteration of the vehicle’s design has proven to be time-consuming, resources-intensive, and ineffective from the decision-making standpoint.

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.

Knock in the Camshaft Torque Actuated (CTA) in the Variable Cam Timing (VCT) engine can be a NVH issue and a source of customer complaint. The knock noise usually occurs during hot idle when the VCT phaser is in the locked position and the locking pin is engaged. During a V8 engine development at Ford, the VCT knock noise was observed during hot idle run. In this paper investigation leading to the identification of the root cause through both test and the CAE simulation is presented. The key knock contributors involving torque and its rate of change in addition to the backlash level are discussed. A CAE metric to assess knock occurrence potential for this NVH failure mode is presented. Finally a new design feature in terms of locking pinhole positioning to mitigate or eliminate the knock is discussed.

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.

Realistic vehicle fuel economy studies require real-world vehicle driving behavior data along with various factors affecting the fuel consumption. Such studies require data with various vehicles usages for prolonged periods of time. A project dedicated to collecting such data is an enormous and costly undertaking. Alternatively, we propose to utilize two publicly available vehicle travel survey data sets. One is Puget Sound Travel Survey collected using GPS devices in 484 vehicles between 2004 and 2006. Over 750,000 trips were recorded with a 10-second time resolution. The data were obtained to study travel behavior changes in response to time-and-location-variable road tolling. The other is Atlanta Regional Commission Travel Survey conducted for a comprehensive study of the demographic and travel behavior characteristics of residents within the study area.

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.

Vehicle idle quality has become an increasing quality concern for automobile manufacturers because of its impact on customer satisfaction. There are two factors that critical to vehicle idle quality, the engine excitation force and vehicle sensitivity (transfer function). To better understand the contribution to the idle quality from these two factors and carry out well-planned improvement measures, a quick and easy way to measure vehicle sensitivity at idle conditions is desired. There are several different ways to get vehicle sensitivity at idle conditions. A typical way is to use CAE. One of the biggest advantages using CAE is that it can separate vehicle sensitivities to different forcing inputs. As always, the CAE results need to be validated before being fully utilized. Another way to get vehicle sensitivity is through impact test using impact hammer or shaker. However this method doesn't include the mount preload due to engine firing torque [3, 4, & 5].

Accounting for more than 90% of the molecules and more than 75% of the mass [1], hydrogen is the most abundant element in the universe. Due to the small molecule size and high buoyancy, it is not available in it’s free form on Earth. In recent years, hydrogen has gained the attention of the automotive industry [2–12] as an environmentally friendly alternative fuel. As a fuel, hydrogen is unique - it is odorless, colorless, tasteless, and burns invisibly in sunlight. Detection solutions such as the odorants used in natural gas are not yet feasible for automotive hydrogen because the available additives can poison the fuel cell catalyst. Additionally, the lower flammability limit of hydrogen is lower, and the flammability range wider, than fuels such as gasoline [13]. Hydrogen detection and its concentration measurement is usually done using hydrogen concentration sensors [13].