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When vehicles share certain information wirelessly via Dedicated Short Range Communications (DSRC), they enable a new layer of electronic vehicle safety that, when needed, can generate warnings to drivers and even initiate automatic preventive actions. Vehicle location and velocity provided by Global Navigation Systems (GNSS), including GPS, are key in allowing vehicle path estimation. GNSS is effective in accurately determining a vehicle's location coordinates in most driving environments, but its performance suffers from obstructions in dense urban environments. To combat this, augmentations to GNSS are being contemplated and tested. This testing has been typically done using a reference GNSS system complimented by expensive military-grade inertial sensors, which can still fail to provide adequate reference performance in certain environments.

Impact of driving patterns on fuel economy is significant in hybrid electric vehicles (HEVs). Driving patterns affect propulsion and braking power requirement of vehicles, and they play an essential role in HEV design and control optimization. Driving pattern conscious adaptive strategy can lead to further fuel economy improvement under real-world driving. This paper proposes a real-time driving pattern recognition algorithm for supervisory control under real-world conditions. The proposed algorithm uses reference real-world driving patterns parameterized from a set of representative driving cycles. The reference cycle set consists of five synthetic representative cycles following the real-world driving distance distribution in the US Midwestern region. Then, statistical approaches are used to develop pattern recognition algorithm. Driving patterns are characterized with four parameters evaluated from the driving cycle velocity profiles.

Currently, two consolidated aftertreatment technologies are available for the reduction of NOx emissions from diesel engines: Urea SCR (Selective Catalytic Reduction) systems and LNT (Lean NOx Trap) systems. Urea SCR technology, which has been widely used for many years at stationary sources, is becoming nowadays an attractive alternative also for light-duty diesel applications. However, SCR systems are much more effective in NOx reduction efficiency at high load operating conditions than light load condition, characterized by lower exhaust gas temperatures.

Optimization of the engine cold start is critical for gasoline direct injection (GDI) engines to meet increasingly stringent emission regulations, since the emissions during the first 20 seconds of the cold start constitute more than 80% of the hydrocarbon (HC) emissions for the entire EPA FTP75 drive cycle. However, Direct Injection Spark Ignition (DISI) engine cold start optimization is very challenging due to the rapidly changing engine speed, cold thermal environment and low cranking fuel pressure. One approach to reduce HC emissions for DISI engines is to adopt retarded spark so that engines generate high heat fluxes for faster catalyst light-off during the cold idle. This approach typically degrades the engine combustion stability and presents additional challenges to the engine cold start. This paper describes a CFD modeling based approach to address these challenges for the Ford 3.5L V6 EcoBoost engine cold start.

In order to detect degradation of engine oil lubricant, bench testing along with a number of diesel-powered Ford trucks were instruments and tested. The purpose of the bench testing was primarily to determine performance aspects such as repeatability, hysteresis effects and so on. Vehicle testing was conducted by designing and installing a separate oil reservoir along with a circulation system which was mounted in the vicinity of the oil pan. An innovative oil sensor was directly installed on the reservoir which can measure five (5) independent oil parameters (viscosity, density, permittivity, conductance, temperature). In addition, the concept is capable of detecting the oil level continuously during normal engine operation. The sensing system consists of an ultrasonic transducer for the oil level detection as well as a Tuning Fork mechanical resonator for the oil condition measurement.

The challenges of flex-fuel vehicle (FFV) emissions measurements have recently come to the forefront for the emissions testing community. The proliferation of ethanol blended gasoline in fractions as high as 85% has placed a new challenge in the path of accurate measures of NMHC and NMOG emissions. Test methods need modification to cope with excess amounts of water in the exhaust, assure transfer and capture of oxygenated compounds to integrated measurement systems (impinger and cartridge measurements) and provide modal emission rates of oxygenated species. Current test methods fall short of addressing these challenges. This presentation will discuss the challenges to FFV testing, modifications made to Ford Motor Company’s Vehicle Emissions Research Laboratory test cells, and demonstrate the improvements in recovery of oxygenated species from the vehicle exhaust system for both regulatory measurements and development measurements.

Selective Catalytic Reduction (SCR) catalysts have been designed to reduce NOx with the assistance of an ammonia-based reductant. Diesel Particulate Filters (DPF) have been designed to trap and eventually oxidize particulate matter (PM). Combining the SCR function within the wall of a high porosity particulate filter substrate has the potential to reduce the overall complexity of the aftertreatment system while maintaining the required NOx and PM performance. The concept, termed Selective Catalytic Reduction Filter (SCRF) was studied using a synthetic gas bench to determine the NOx conversion robustness from soot, coke, and hydrocarbon deposition. Soot deposition, coke derived from propylene exposure, and coke derived from diesel fuel exposure negatively affected the NOx conversion. The type of soot and/or coke responsible for the inhibited NOx conversion did not contribute to the SCRF backpressure.

A dual piston Variable Compression Ratio (VCR) engine has been newly developed. This compact VCR system uses the inertia force and hydraulic pressure accompanying the reciprocating motion of the piston to raise and lower the outer piston and switches the compression ratio in two stages. For the torque characteristic enhancement and the knocking prevention when the compression ratio is being switched, it is necessary to carry out engine controls based on accurate compression ratio judgment. In order to accurately judge compression ratio switching timing, a control system employing the Hidden Markov Model (HMM) was used to analyze vibration generated during the compression ratio switching. Also, in order to realize smooth torque characteristics, an ignition timing control system that separately controls each cylinder and simultaneously performs knocking control was constructed.

A systematic methodology has been employed to develop the Duratec 3.5L EcoBoost combustion system, with focus on the optimization of the combustion system including injector spray pattern, intake port design, piston geometry, cylinder head geometry. The development methodology was led by CFD (Computational Fluid Dynamics) modeling together with a testing program that uses optical, single-cylinder, and multi-cylinder engines. The current study shows the effect of several spray patterns on air-fuel mixing, in-cylinder flow development, surface wetting, and turbulence intensity. A few sets of injector spray patterns are studied; some that have a wide total cone angle, some that have a narrow cone angle and a couple of optimized injector spray patterns. The effect of the spray pattern at part load, full load and cold start operation was investigated and the methodology for choosing an optimized injector is presented.

EGR coolers are effective to reduce NOx emissions from diesel engines due to lower intake charge temperature. EGR cooler fouling reduces heat transfer capacity of the cooler significantly and increases pressure drop across the cooler. Engine coolant provided at 40–90 C is used to cool EGR coolers. The presence of a cold surface in the cooler causes particulate soot deposition and hydrocarbon condensation. The experimental data also indicates that the fouling is mainly caused by soot and hydrocarbons. In this study, a 1-D model is extended to simulate particulate soot and hydrocarbon deposition on a concentric tube EGR cooler with a constant wall temperature. The soot deposition caused by thermophoresis phenomena is taken into account the model. Condensation of a wide range of hydrocarbon molecules are also modeled but the results show condensation of only heavy molecules at coolant temperature.

The relationship between gasoline properties and vehicle particulate matter emissions was investigated, for the purpose of constructing a predictive model. Various chemical species were individually blended with an indolene base fuel, and the solid particulate number (PN) emissions from each blend were measured over the New European Driving Cycle (NEDC). The results indicated that aromatics with a high boiling point and a high double bond equivalent (DBE) value tended to produce more PN emissions. However, high boiling point components with low DBE values, such as paraffins, displayed only a minor effect on PN. Upon further analysis of the test results, it was also confirmed that low vapor pressure components correlated with high PN emissions, as might be expected based on their combustion behavior. A predictive model, termed the “PM Index,” was constructed based on the weight fraction, vapor pressure, and DBE value of each component in the fuel.

Today's automotive and electronics technologies are evolving so rapidly that educators and industry are both challenged to re-educate the technological workforce in the new area before they are replaced with yet another generation. In early November 2009 Ford's Product Development senior management formally approved a proposal by the University of Detroit Mercy to transform 125 of Ford's “IC Engine Automotive Engineers” into “Advanced Electric Vehicle Automotive Engineers.” Two months later, the first course of the Advanced Electric Vehicle Program began in Dearborn. UDM's response to Ford's needs (and those of other OEM's and suppliers) was not only at the rate of “academic light speed,” but it involved direct collaboration of Ford's electric vehicle leaders and subject matter experts and the UDM AEV Program faculty.

The use of model-based software development in automotive applications has increased in recent years. Current vehicles contain millions of lines of code, and millions of dollars are spent each year fixing software issues. Most new features are software controlled and many times include distributed functionality, resulting in increased vehicle software content and accelerated complexity. To handle rapid change, OEMs and suppliers must work together to accelerate software development and testing. As development processes adapt to meet this challenge, model-based design can provide a solution. Model-based design is a broad development approach that is applied to a variety of applications in various industries. This paper reviews a project using the MATLAB/Simulink/Stateflow environment to complete a functional model of a low cost radio.

Prediction of drowsiness based on an objective measure is demanded in machine and vehicle operations, in which human error may cause fatal accidents. Recently, we focused on the pupil which is controlled by the autonomic nervous system, easily and non-invasively observable from the outside of the body. Prior to the large low frequency pupil-diameter fluctuation, which is known to associate with drowsiness, a Gradual Miosis was observed in most subjects. During this miosis period, the subjects were not yet aware of their drowsiness. We have developed a software system which automatically detects the Gradual Miosis in real time.

In the automobile industries, weight reduction has been investigated to improve fuel efficiency together with reduction of CO2 emission. In such circumstance, it becomes necessity to make an electric power steering (EPS) more compact and lightweight. In this study, we aimed to have a smaller and lighter EPS gear size by focusing on an impact load caused at steering end. In order to increase the shock absorption energy without increase of stopper bush size, we propose new theory of impact energy absorption by not only spring function but also friction, and a new stopper bush was designed on the basis of the theory. The profile of the new stopper bush is cylinder form with wedge-shaped grooves, and when the new stopper bush is compressed by the end of rack and the gear housing at steering end, it enables to expand the external diameter and produce friction. In this study, we considered the durability in the proposed profile.

In order to reduce automobile body weight and improve crashworthiness, the use of high-strength steels has increased greatly in recent years. An optimal combination of both crash safety performance and lightweight structure has been a major challenge in automobile body engineering. In this study, the Cockcroft-Latham fracture criterion was applied to predict the fracture of high-strength steels. Marciniak-type biaxial stretching tests for high-strength steels were performed to measure the material constant of the Cockcroft-Latham fracture criterion. Furthermore, in order to improve the simulation accuracy, local anisotropic parameters based on the plastic strain (strain dependent model of anisotropy) were measured using the digital image grid method and were incorporated into Hill's anisotropic yield condition by the authors. In order to confirm the validity of the Cockcroft-Latham fracture criterion, uniaxial tensile tests were performed.

When a vehicle is in motion, noise is generated in the cabin that is composed of noise in multiple narrow-frequency bands and caused by input from the road surface. This type of noise is termed low-frequency-band road noise, and its reduction is sought in order to increase occupant comfort. The research discussed in this paper used feedback control technology as the basis for the development of an active noise control technology able to simultaneously reduce noise in multiple narrow-frequency bands. Methods of connecting multiple single-frequency adaptive notch filters, a type of adaptive filter, were investigated. Based on the results, a method of connecting multiple filters that would mitigate mutual interference caused by different controller transmission characteristics was proposed.

The technology to estimate engine load using the amplitude of crankshaft angular velocity variation during a cycle, which is referred to as “Δω (delta omega)”, in a four-stroke single-cylinder gasoline engine has been established in our former studies. This study was aimed to apply this technology to the spark advance control system for small motorcycles. The cyclic variation of the Δω signal, which affects engine load detection accuracy, was a crucial issue when developing the system. To solve this issue, filtering functions that can cope with various running conditions were incorporated into the computation process that estimates engine loads from Δω signals. In addition, the system made it possible to classify engine load into two levels without a throttle sensor currently used. We have thus successfully developed the new spark advance system that is controlled in accordance with the engine speed and load.

The suitability of FM radio receivers for automotive applications has conventionally been evaluated by evaluating the reception characteristics of broadcast waves while conducting repeated driving tests in a special test environment. Because the evaluation of sound quality while driving relies upon the auditory judgment of a limited range of test subjects, these tests present issues in terms of the reproducibility and objectivity of the evaluations. In order to resolve these issues, a method of evaluating the suitability of FM receivers for automotive applications through the creation of a virtual radio wave environment on a PC was developed (this has been termed the “Two-Stage method”). In the research described in this paper, the Two-Stage method was used to analyze the effect of multipath distortion on FM receivers when driving through arbitrary radio wave propagation environments.

Traditionally, the suitability of radio receivers and similar devices for automotive use has been evaluated by evaluating their reception characteristics in relation to transmitted waves via repeated driving tests. This method of evaluation presents issues in terms of reproducibility and objectivity. A method of evaluating the suitability of FM receivers for vehicle fitting using a virtual propagation environment created on a PC (termed the Two-Stage method) has been developed in order to address these issues. The major challenge in the Two-Stage method is the creation of an actual propagation environment on a PC. A test-based incoming wave estimation technology able to accurately estimate the characteristics of actual propagation environments is therefore essential. The estimation of incoming FM waves necessitates large array antennas. In addition, the incoming waves become coherent multipath waves.