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Ethanol fuel has received renewed attention in recent years because of its oxygenate content and its potential to reduce greenhouse gas emissions from spark ignition engines. The economic impact on farm industry has been one of the drivers for its use in engines in the U.S. Although ethanol, in various blends, has been used in automotive engines for almost a decade the fuel has seldom been utilized in off-highway engines where the fuel systems are not well controlled. This investigation was conducted to evaluate exhaust emissions and combustion characteristics of E85 fuel in an off-highway engine used in farm equipment. A single-cylinder, four-stroke, spark ignition engine equipped with a carburetor was used to investigate combustion and exhaust emissions produced by gasoline and blends of gasoline and ethanol fuels. The engine fuel system was modified to handle flow rates required by the engine. A variable size-metering orifice was used to control air-to-fuel ratios.

As greenhouse gas regulations continue to tighten, more opportunities to improve engine efficiency emerge, including exhaust gas heat recovery. Upon cold starts, engine exhaust gases downstream of the catalysts are redirected with a bypass valve into a heat exchanger, transferring its heat to the coolant to accelerate engine warm-up. This has several advantages, including reduced fuel consumption, as the engine’s efficiency improves with temperature. Furthermore, this accelerates readiness to defrost the windshield, improving both safety as well as comfort, with greater benefits in colder climates, particularly when combined with hybridization’s need for engine on-time solely for cabin heating. Such products have been in the market now for several years; however they are bulky, heavy and expensive, yielding opportunities for competitive alternatives.

The approaches of obtaining both fatigue strength distribution and fatigue life distribution for a given set of fatigue S-N data are reviewed in this paper. A new fatigue S-N curve transformation technique, which is based on the fundamental statistics definition and some reasonable assumptions, is specifically developed in this paper to transform a fatigue life distribution to a fatigue strength distribution. The procedures of applying the technique to multiple-stress level, two-stress level, and one-stress level fatigue S-N data are presented.

We present research in progress to develop and implement a transportable instrumentation package (TIP) to collect driver data in a vehicle. The overall objective of the project is to investigate the symbiotic relationship between humans and their vehicles. We first describe the state-of-art technologies to build the components of TIP that meet the criteria of ease of installation, minimal interference with driving, and sufficient signals to monitor driver state and condition. This method is a viable alternative to current practice which is to first develop a fully instrumented test vehicle, often at great expense, and use it to collect data from each participant as he/she drives a prescribed route. Another practice, as for example currently being used in the SHRP-2 naturalistic driving study, is to install the appropriate instrumentation for data collection in each individual's vehicle, often requiring several hours.

This paper describes a computerized value analysis tool (VAT) developed to aid automotive interior designers, engineers and planners to achieve the high levels of perceived quality of materials used in automotive door trim panels. The model requires a number of inputs related to types of materials, their manufacturing processes and customer perceived quality ratings, costs and importance of materials, features located in different areas of the door trim panel, etc. It allows the user to conduct iterative evaluation of total cost, total weighted customer perceived quality ratings, and estimates of perceived value (perceived quality divided by cost) for different door trim areas as well as the entire door trim panel. The VAT, thus, allows value and cost management related to materials and processing choices for automotive interiors.

Life testing or test-to-failure method and binomial testing method are the two most commonly used methods in product validation and reliability demonstration. The two-parameter Weibull distribution function is often used in the life testing and almost exclusively used in the extended time testing, which can be considered as an accelerated testing method by appropriately extending the testing time but with significantly reduced testing samples. However, the fatigue data from a wide variety of sources indicate that the three-parameter Weibull distribution function with a threshold parameter at the left tail is more appropriate for fatigue life data with large sample sizes. The uncertainties introduced from the assumptions about the underlying probabilistic distribution would significantly affect the interpretation of the test data and the assessment of the performance of the accelerated binomial testing methods, therefore, the selection of a probabilistic model is critically important.

Controller Area Network (CAN), the de facto standard for in-vehicle networks, has insufficient security features and thus is inherently vulnerable to various attacks. To protect CAN bus from attacks, intrusion detection systems (IDSs) based on advanced deep learning methods, such as Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN), have been proposed to detect intrusions. However, those models generally introduce high latency, require considerable memory space, and often result in high energy consumption. To accelerate intrusion detection and also reduce memory requests, we exploit the use of Binarized Neural Network (BNN) and hardware-based acceleration for intrusion detection in in-vehicle networks. As BNN uses binary values for activations and weights rather than full precision values, it usually results in faster computation, smaller memory cost, and lower energy consumption than full precision models.

A GT-suite commercial code was used to develop a fully integrated model of a light duty commercial vehicle with a V6 diesel engine, to study the use of a BorgWarner dual mode coolant pump (DMCP) in active thermal management of the vehicle. An Urban Dynamometer Driving Schedule (UDDS) was used to validate the simulation results with the experimental data. The conventional mechanical pump from the validated model was then replaced with the dual mode coolant pump. The control algorithm for the pump was based on controlling the coolant temperature with pump speed. Maximum electrical speed of the pump and the efficiency of the pump were used to determine whether the pump should run in mechanical or electrical mode. The model with the dual mode coolant pump was simulated for the UDDS cycle to demonstrate the effectiveness of control strategy.

This paper presents a comparison of aqueous corrosion rates in 5% NaCl solution for eight experimental creep-resistant magnesium alloys considered for automotive powertrain applications, as well as three reference alloys (pure magnesium, AM50B and AZ91D). The corrosion rates were measured using the techniques of titration, weight loss, hydrogen evolution, and DC polarization. The corrosion rates measured by these techniques are compared with each other as well as with those obtained with salt-spray testing using ASTM B117. The advantages and disadvantages of the various corrosion measurement techniques are discussed.

With introductions of stringent diesel engine emission regulations, the DOC and DPF systems have become the mainstream technology to eliminate soot particles through diesel combustion under various operation conditions. Urea-based SCR has been the mainstream technical direction to reduce NOx emissions. For both technologies, low-temperature conditions or cold start conditions pose challenges to activate DOC or SCR emission-reduction performance. To address this issue, mini or full flow burner systems may be used to increase exhaust temperature to reach DOC light-off or SCR initiation temperature by combustion of diesel fuel. In essence, the burner systems incorporate a fuel injector, spray atomization, proper fuel / air mixing mechanisms, and combustion control as independent heat sources.

Regulations on exhaust emissions from light- and heavy-duty diesel engines have generated interest in high-pressure fuel injection systems. It has been recognized that high-pressure injection systems produce fuel sprays that may be more conductive to reducing exhaust emissions in direct-injection diesel engines. However, for such a system to be effective it must be matched carefully with the engine design and its operating parameters. A common-rail type of fuel injection system was investigated in the present study. The injection system utilizes an intensifier to generate injection pressures as high as 160 MPa. The fuel spray characteristics were evaluated on a test bench in a chamber containing pressurized nitrogen gas. The injection system was then incorporated in a single-cylinder diesel engine. The injection system parameters were adjusted to match engine specifications and its operating parameters.

Gasoline-ethanol blends are being used or have been considered as a fuel for spark ignition engines. The motivation for using the blends varies in indifferent parts of the world and even in regions within a country. The increasing cost of gasoline, combined with regional tax incentives, is one of the reasons for increased interests in gasoline-ethanol blends in recent years in the U.S. Many vehicular engines are not designed to use a specific gasoline-ethanol blend. Rather, the engines have multi-blend capability, ranging from E0 to about E85. It is plausible that engine-out emissions will vary depending on the blend being used which may be further impacted by the level of EGR used with the blends. The present work was carried out to investigate engine out emissions when a vehicular spark-ignition engine was operated on E0 and E85 and different levels of EGR. A 4-cylinder, 2.5 liter, PFI engine was used in the experimental investigation.

External Exhaust Gas Recirculation (EGR) has been used on diesel engines for decades and has also been used on gasoline engines in the past. It is recently reintroduced on gasoline engines to improve fuel economy at mid and high engine load conditions, where EGR can reduce throttling losses and fuel enrichment. Fuel enrichment causes fuel penalty and high soot particulates, as well as hydrocarbon (HC) emissions, all of which are limited by emissions regulations. Under stoichiometric conditions, gasoline engines can be operated at high EGR rates (> 20%), but more than diesel engines, its intake gas including external EGR needs extreme cooling (down to ~50°C) to gain the maximum fuel economy improvement. However, external EGR and its problems at low temperatures (fouling, corrosion & condensation) are well known.

A study was conducted to investigate combustion variability and exhaust emissions from high-speed, natural gas fueled engines. Two types of fuel systems were used in the investigation: a mixer and a port fuel injection. The overall engine performances were not much different at stoichiometric fuel-air ratio. But as the equivalence ratio was reduced the engine with the mixer produced higher levels of hydrocarbons and larger coefficient of variations in imep. The same engine exhibited longer flame development angle and rapid burn duration in comparison to the fuel injected engine. The differences in burn durations increased as the equivalence ratio decreased and the mixer system produced larger variations in their values at these operating points. The investigation showed the performance of the engine was better with natural gas injection system than with the mixer, particularly at lean equivalence ratios.

Semi-trucks, specifically class-8 trucks, have recently become a platform of interest for autonomy systems. Platooning involves multiple trucks following each other in close proximity, with only the lead truck being manually driven and the rest being controlled autonomously. This approach to semi-truck autonomy is easily integrated on existing platforms, reduces delivery times, and reduces greenhouse gas emissions via fuel economy benefits. Level 1 SAE fuel studies were performed on class-8 trucks operating with the Auburn Cooperative Adaptive Cruise Control (CACC) system, and fuel savings up to 10-12% were seen. Enabling platooning autonomy required the use of radar, global positioning systems (GPS), and wireless vehicle-to-vehicle (V2V) communication. Poor measurements and state estimates can lead to incorrect or missing positioning data, which can lead to unnecessary dynamics and finally wasted fuel.

This paper presents results of a three-phase research project aimed at understanding how future automotive interior materials should be selected or designed to satisfy the needs of the customers. The first project phase involved development of 22 five-point semantic differential scales to measure visual, visual-tactile, and evaluative characteristics of the materials. Some examples of the adjective pairs used to create the semantic differential scales to measure the perceptual characteristics of the material are: a) Visual: Light vs. Dark, Flat vs. Shiny, etc., b) Visual-Tactile: Smooth vs. Rough, Slippery vs. Sticky, Compressive vs. Non-Compressive, Textured vs. Non-Textured, etc., c) Evaluative (overall perception): Dislike vs. Like, Fake vs. Genuine, Cheap vs. Expensive, etc. In the second phase, 12 younger and 12 older drivers were asked to evaluate a number of different automotive interior materials by using the 22 semantic differential scales.

Recent stringent government regulations on emission control and fuel economy drive the vehicles and their associated components and systems to the direction of lighter weight. However, the achieved lightweight must not be obtained by sacrificing other important performance requirements such as manufacturability, strength, durability, reliability, safety, noise, vibration and harshness (NVH). Additionally, cost is always a dominating factor in the lightweight design of automotive products. Therefore, a successful lightweight design can only be accomplished by better understanding the performance requirements, the potentials and limitations of the designed products, and by balancing many conflicting design parameters. The combined knowledge-based design optimization procedures and, inevitably, some trial-and-error design iterations are the practical approaches that should be adopted in the lightweight design for the automotive applications.

A probabilistic distribution function roughly consists of two parts: the middle part and the tails. The fatigue life distribution at a stress/load level is often described with two-parameter lognormal or Weibull distribution functions, which are more suitable for modeling the mean (middle) behaviors. The domains of the conventional probabilistic distribution functions are often unbounded, either infinite small (0 for the two-parameter Weibull) or infinite large or both. For most materials in low- and medium-cycle fatigue regimes, the domains of fatigue lives are usually bounded, and the inclusion of the bounds in a probabilistic model is often critical in some applications, such as product validation and life management. In this paper, four- and five-parameter Weibull distribution functions for the probabilistic distributions with bounds are developed. Finally, the applications of these new models in fatigue data analysis and damage assessment are provided and discussed.

This paper presents results of a research project conducted to develop a methodology and to refine the specifications of a small, low mass, low cost vehicle being developed at the University of Michigan-Dearborn. The challenge was to assure that the design would meet the needs and expectations of customers in three different countries, namely, China, India and the United States. U.S, Chinese and Indian students studying on the university campus represented customers from their respective countries for our surveys and provided us with the necessary data on: 1) Importance of various vehicle level attributes to the entry level small car customer, 2) Preferences to various features, and 3) Direction magnitude estimation on parameters to size the vehicle for each of the three markets.

This paper describes a research project currently in-progress to develop a parametric model of a vehicle for use in early design stages of a new vehicle program. The model requires key input parameters to define the kind of new vehicle to be designed — in terms of details such as its intended driver/user population, vehicle type (e.g. 2-box, 3-box designs), and some key exterior and interior dimensions related to its size and proportions. The model computes and graphically displays interior package, ergonomics zones for driver controls and displays, and field of views through window openings. It also allows importing or inputting and superimposing and manipulating exterior surfaces created by a designer to assess compatibility between the interior occupant package and the vehicle exterior.