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Technical Paper

Motion Analysis Enhances Visualization of Underbody Flow

Velocity profiles for air flowing under a vehicle body are determined by analyzing videotapes of neutrally buoyant soap bubbles using motion analysis software and equipment. What had heretofore been primarily a qualitative flow visualization technique has been extended to provide quantitative data. The light sources, cameras, and bubble generator, mounted on the vehicle, are powered by the vehicle's electrical system, making it possible to compare underbody velocities measured in a wind tunnel with those over the road. Results are presented for a heavy-duty 4×4 pickup truck at speeds up to 25m/s (55 mph). The velocity profiles in the tunnel and on the road were quite similar.
Technical Paper

Overall Results: Phase I Ad Hoc Diesel Fuel Test Program

The future of diesel-engine-powered passenger cars and light-duty vehicles in the United States depends on their ability to meet Federal Tier 2 and California LEV2 tailpipe emission standards. The experimental purpose of this work was to examine the potential role of fuels; specifically, to determine the sensitivity of engine-out NOx and particulate matter (PM) to gross changes in fuel formulation. The fuels studied were a market-average California baseline fuel and three advanced low sulfur fuels (<2 ppm). The advanced fuels were a low-sulfur-highly-hydrocracked diesel (LSHC), a neat (100%) Fischer-Tropsch (FT100) and 15% DMM (dimethoxy methane) blended into LSHC (DMM15). The fuels were tested on modern, turbocharged, common-rail, direct-injection diesel engines at DaimlerChrysler, Ford and General Motors. The engines were tested at five speed/load conditions with injection timing set to minimize fuel consumption.
Technical Paper

A New Experimental Methodology to Estimate Chassis Force Transmissibility and Applications to Road NVH Improvement

The performance of structure-borne road NVH can be cascaded down to three major systems: 1) vehicle body structure, 2) chassis/suspension, 3) tire/wheel. The forces at the body attachment points are controlled by the isolation efficiency of the chassis/suspension system and the excitation at the spindle/knuckle due to the tire/road interaction. The chassis force transmissibility is a metric to quantify the isolation efficiency. This paper presents a new experimental methodology to estimate the chassis force transmissibility from a fully assembled vehicle. For the calculation of the transmissibility, the spindle force/moment estimation and the conventional Noise Path Analysis (NPA) methodologies are utilized. A merit of the methodology provides not only spindle force to body force transmissibility but also spindle moment to body force transmissibility. Hence it enables us to understand the effectiveness of the spindle moments on the body forces.
Technical Paper

Application of Fuzzy Classification Methods for Diagnosis of Reject Root Causes in Manufacturing Environment

This paper presents an approach of using neural network and fuzzy logic methods for the diagnosis of fault root causes in a manufacturing environment. As the first step in this approach, data from all the valid test points were collected and studied based on their statistical characteristics. An information-gain-based procedure was then followed to quantitatively evaluate the relevance of each test point to the diagnosis process. Accordingly, an objective rank of all relevant test points was generated for a particular reject. The root cause of rejects was then identified by a procedure based on an information-gain-weighted radial basis function neural network and a fuzzy multiple voting classification algorithm. This method has been tested with the top five rejects of the transmission main control component at Ford and promising results have been obtained.
Technical Paper

Fast Charging Lithium-Ion Batteries

We try to understand the fast recharge capability of automotive lithium-ion batteries and its effect of fast charge on capacity degradation. We find out that 5 Ah prismatic Li-ion cells can be fully recharged in 3 minutes under a constant rate of 20C, or in 2 min (25.5C) from 0% to 85% state of charge (SOC) without undue stresses. We cycle the battery at 16C charge rate from 0 to 100%SOC and do not see any unexpected battery capacity loss in 50 cycles, where half of the cycles are charged at1C-rate as a reference capacity check. We realize that the batteries under the fast charge tests do not experience any negative impacts related to mass transport in either solid electrodes or the electrolyte system. In the paper, we propose a new procedure to measure the ac and dc resistances of the battery under continuous operation. Electrochemical impedance analyses on the whole battery and the individual electrodes are also conducted.
Technical Paper

An Indirect Occupancy Detection and Occupant Counting System Using Motion Sensors

This paper proposes a low-cost but indirect method for occupancy detection and occupant counting purpose in current and future automotive systems. It can serve as either a way to determine the number of occupants riding inside a car or a way to complement the other devices in determining the occupancy. The proposed method is useful for various mobility applications including car rental, fleet management, taxi, car sharing, occupancy in autonomous vehicles, etc. It utilizes existing on-board motion sensor measurements, such as those used in the vehicle stability control function, together with door open and closed status. The vehicle’s motion signature in response to an occupant’s boarding and alighting is first extracted from the motion sensors that measure the responses of the vehicle body. Then the weights of the occupants are estimated by fitting the vehicle responses with a transient vehicle dynamics model.
Technical Paper

Secure and Privacy-Preserving Data Collection Mechanisms for Connected Vehicles

Nowadays, the automotive industry is experiencing the advent of unprecedented applications with connected devices, such as identifying safe users for insurance companies or assessing vehicle health. To enable such applications, driving behavior data are collected from vehicles and provided to third parties (e.g., insurance firms, car sharing businesses, healthcare providers). In the new wave of IoT (Internet of Things), driving statistics and users’ data generated from wearable devices can be exploited to better assess driving behaviors and construct driver models. We propose a framework for securely collecting data from multiple sources (e.g., vehicles and brought-in devices) and integrating them in the cloud to enable next-generation services with guaranteed user privacy protection.
Technical Paper


This paper describes the design and build of an experimental super transport truck for high-speed, long distance freight hauling on the interstate highway system of the 1970's. The tractor, powered by a 600-hp gas turbine engine, pulls two 40-foot tandem axle trailers at a G.C.W. of 170,000 lbs. Details of the turbine engine development are covered in SAE paper, No. 991B. One of the features of the super transport truck is the cab, which is designed for long-distance, non-stop, two-man operation. It is provided with sleeping accommodations, washroom conveniences, food facilities, and a complete heating and air-conditioning system. The 13-foot high cab roof is flush with the top of the trailers, providing a substantial aerodynamic advantage. Other features and components of the truck are described, and observations made during the 5500-mile national tour are discussed.
Technical Paper

A Statistical Evaluation of Brake Performance

Utilization of statistical methods can improve vehicle stopping-distance projections and reduce the complexity of brake deceleration models. These techniques can be very useful in the course of ascertaining whether an untested vehicle conforms to the applicable Federal Motor Vehicle Safety Standard (FMVSS), but they have much broader uses in the design of brake systems.
Technical Paper

Effect of Road Excitations on Driveline Output Torque Measurements

This paper presents the characterization of the random noise in driveline output shaft torque measurements that is commonly induced by road disturbances. To investigate the interaction between the shaft torque and road side excitation, torque signals are measured using a magnetoelastic torque sensor, as well as a conventional strain gauge sensor, under various types of road surfaces and conditions such as unevenness. A generalized de-trending method for producing a stationary random signal is first conducted. Statistical methods, in particular the probability density function and transform technique, are utilized to provide an evident signature for identifying the road excitation effect on the vehicle output shaft torque. Analysis results show how the road surface can act as a disturbance input to the vehicle shaft torque.
Technical Paper

A Statistical Approach to Assess the Impact of Road Events on PHEV Performance using Real World Data

Plug in hybrid electric vehicles (PHEVs) have gained interest over last decade due to their increased fuel economy and ability to displace some petroleum fuel with electricity from power grid. Given the complexity of this vehicle powertrain, the energy management plays a key role in providing higher fuel economy. The energy management algorithm on PHEVs performs the same task as a hybrid vehicle energy management but it has more freedom in utilizing the battery energy due to the larger battery capacity and ability to be recharged from the power grid. The state of charge (SOC) profile of the battery during the entire driving trip determines the electric energy usage, thus determining overall fuel consumption.
Technical Paper

Trail-Braking Driver Input Parameterization for General Corner Geometry

Trail-Braking (TB) is a common cornering technique used in rally racing to negotiate tight corners at (moderately) high speeds. In a previous paper by the authors it has been shown that TB can be generated as the solution to the minimum-time cornering problem, subject to fixed final positioning of the vehicle after the corner. A TB maneuver can then be computed by solving a non-linear programming (NLP). In this work we formulate an optimization problem by relaxing the final positioning of the vehicle with respect to the width of the road in order to study the optimality of late-apex trajectories typically followed by rally drivers. We test the results on a variety of corners. The optimal control inputs are approximated by simple piecewise linear input profiles defined by a small number of parameters. It is shown that the proposed input parameterization can generate close to optimal TB along the various corner geometries.
Technical Paper

A Matrix Array Technique for Evaluation of Adhesively Bonded Joints

Adhesive bonding technology is playing an increasingly important role in automotive industry. Ultrasonic evaluation of adhesive joints of metal sheets is a challenging problem in Non-Destructive Testing due to the large acoustic impedance mismatch between metal and adhesive, variability in the thickness of metal and adhesive layers, as well as variability in joint geometry. In this paper, we present the results from a matrix array of small flat ultrasonic transducers for evaluation of adhesively bonded joints in both laboratory and production environments. The reverberating waveforms recorded by the array elements are processed to obtain an informative parameter, whose two-dimensional distribution can be presented as a C-scan. Energy of the reflected waveform, normalized with respect to the energy obtained from an area with no adhesive, is a robust parameter for discriminating "adhesive/no-adhesive" regions.
Technical Paper

The Use of Discrete Wavelet Transform in Road Loads Signals Compression

Wavelets are a powerful mathematical tool used to multi-resolution time-frequency decomposition of signals, in order to analyze them in different scales and obtain different aspects of the information. Despite being a relatively new tool, wavelets have being applied in several areas of human knowledge, especially in signal processing, with emphasis in encoding and compression of image, video and audio. Based on a previous successful applications (FRAZIER, 1999) together a commitment to quality results, this paper evaluates the use of the Discrete Wavelet Transform (DWT) as an compression algorithm to reduce the amount of data collected in road load signals (load history) which are used by the durability engineering teams in the automotive industry.
Technical Paper

Mexico City Traffic and Los Angeles City Traffic Testing: An Approach to Test Route Development for Results Homologation

Vehicle testing on public roads is used by the automotive community in different locations to evaluate the noise characteristics of brake systems under typical customer usage conditions. These tests are generally carried out on different locations and show results with questionable compatibility as has been concluded on several investigations over the last years [1]. Global projects on the other hand mandate to have tests that can represent vehicle usage in several types of environments in order to have reliable indicators of performance on different conditions. This paper suggests a method to characterize roads on different sites and modify the route to match a specific target.
Technical Paper

Generation and Usage of Virtual Data for the Development of Perception Algorithms Using Vision

Camera data generated in a 3D virtual environment has been used to train object detection and identification algorithms. 40 common US road traffic signs were used as the objects of interest during the investigation of these methods. Traffic signs were placed randomly alongside the road in front of a camera in a virtual driving environment, after the camera itself was randomly placed along the road at an appropriate height for a camera located on a vehicle’s rear view mirror. In order to best represent the real world, effects such as shadows, occlusions, washout/fade, skew, rotations, reflections, fog, rain, snow and varied illumination were randomly included in the generated data. Images were generated at a rate of approximately one thousand per minute, and the image data was automatically annotated with the true location of each sign within each image, to facilitate supervised learning as well as testing of the trained algorithms.
Technical Paper

Statistical Analysis of the Drivability Impacts with Ethanol

This paper presents a study performed in 10 vehicles available in Brazilian market where the drivability with ethanol and gasoline, also referred as gasohol were compared. The motivation for this work came from the constant competition of the automotive industry, where engineers are searching for ways to improve the quality of the products aiming the “best in class” drivability with the best cost efficiency. For the Brazilian market, a further complexity is added to the development and verification process, which is the need to design and verify the controls and calibration considering the two fuels available in the market, the ethanol and the gasoline. In order to determine how the drivability is impacted by the ethanol, the paper presents a study where the drivability data were generated using the objective drivability measurement system AVL-DRIVE™.
Technical Paper

Effective Evaluation of Automated Driving Systems

In the last years various advanced driver assistance systems (ADAS) have been introduced on the market. More highly advanced functions up to automated driving functions are currently under research. By means of these functions partly automated driving in specific situations is already or will be realized soon, e.g. traffic jam assist. Besides the technical challenges to develop such automated driving functions for complex situations, e.g. construction or intersection areas, new approaches for the evaluation of these functions under different driving conditions are necessary, in order to assess the benefits and identify potential weaknesses. Classical approaches for evaluation and market sign off will require an extensive testing, which results in high costs and time demands. Therefore the classical approaches are hardly feasible taking into account higher levels of support and automation. Today the final sign-off requires a high amount of real world tests.
Technical Paper

Region Proposal Technique for Traffic Light Detection Supplemented by Deep Learning and Virtual Data

In this work, we outline a process for traffic light detection in the context of autonomous vehicles and driver assistance technology features. For our approach, we leverage the automatic annotations from virtually generated data of road scenes. Using the automatically generated bounding boxes around the illuminated traffic lights themselves, we trained an 8-layer deep neural network, without pre-training, for classification of traffic light signals (green, amber, red). After training on virtual data, we tested the network on real world data collected from a forward facing camera on a vehicle. Our new region proposal technique uses color space conversion and contour extraction to identify candidate regions to feed to the deep neural network classifier. Depending on time of day, we convert our RGB images in order to more accurately extract the appropriate regions of interest and filter them based on color, shape and size. These candidate regions are fed to a deep neural network.