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A few years ago, the automobile industry agreed to adopt standards for a new voltage for the production and use of electrical power. The perception was near universal that 14 Volts was at the limits of its capability, and that 42 Volts would be adopted in a rush. The universal perception was wrong. Since then, much of the auto industry has encountered hard financial times. In a totally separate development, parts suppliers introduced innovations at 14 Volts, some of which a few years ago were thought to require 42 Volts. Today, there are 42-Volt cars and trucks for sale, but only at numbers far lower than necessary to begin to achieve economies of scale. But the factor which caused the industry to develop the 42 Volt standard, the growth of electricity use on motor vehicles, continues with no sign of letup. Further, the true technical obstacles to adoption of 42 Volts have been discovered and at least provisionally solved.

This paper quantifies the potential of electric propulsion systems to reduce petroleum use and greenhouse gas (GHG) emissions in the 2030 U.S. light-duty vehicle fleet. The propulsion systems under consideration include gasoline hybrid-electric vehicles (HEVs), plug-in hybrid vehicles (PHEVs), fuel-cell hybrid vehicles (FCVs), and battery-electric vehicles (BEVs). The performance and cost of key enabling technologies were extrapolated over a 25-30 year time horizon. These results were integrated with software simulations to model vehicle performance and tank-to-wheel energy consumption. Well-to-wheel energy and GHG emissions of future vehicle technologies were estimated by integrating the vehicle technology evaluation with assessments of different fuel pathways. The results show that, if vehicle size and performance remain constant at present-day levels, these electric propulsion systems can reduce or eliminate the transport sector's reliance on petroleum.

An inexpensive driving simulation system with sufficient fidelity has been developed. The system produces motion cues of four degrees of freedom, visual and auditory cues, and control feel on the steering wheel. This paper describes the features of this newly developed system and gives examples that demonstrate its effectiveness. The motion cues provided in this system are yaw, heave, and lateral and fore/aft accelerations. The lateral and fore/aft accelerations are simulated by tilting the simulator compartment. A computer-processed road image is given through a CRT monitor. The restoring torque of the steering wheel is produced by an electrical servosystem via a coil spring. Cruising sound is given in order to improve speed perception. Since the system uses digital computers, the vehicle characteristics are altered easily by merely rewriting the software. This enables us to simulate special vehicle dynamics such as front & rear wheel steering.

The challenge of developing a robust, real-time driver gaze classification system is that it has to handle difficult edge cases that arise in real-world driving conditions: extreme lighting variations, eyeglass reflections, sunglasses and other occlusions. We propose a single-camera end-toend framework for classifying driver gaze into a discrete set of regions. This framework includes data collection, semi-automated annotation, offline classifier training, and an online real-time image processing pipeline that classifies the gaze region of the driver. We evaluate an implementation of each component on various subsets of a large onroad dataset. The key insight of our work is that robust driver gaze classification in real-world conditions is best approached by leveraging the power of supervised learning to generalize over the edge cases present in large annotated on-road datasets.

Advances in avionics and display technology are significantly changing the cockpit environment in current transport aircraft. The MIT Aeronautical Systems Lab (ASL) has developed a part-task flight simulator specifically to study the effects of these new technologies on flight crew situational awareness and performance. The simulator is based on a commercially-available graphics workstation, and can be rapidly reconfigured to meet the varying demands of experimental studies. The simulator has been successfully used to evaluate graphical microburst alerting displays, electronic instrument approach plates, terrain awareness and alerting displays, and ATC routing amendment delivery through digital datalinks.

The ability to make accurate decisions concerning early body-in-white architectures is critical to an automaker since these decisions often have long term cost and weight impacts. We address this need with a methodology which can be used to assist in body architecture decisions using process-based technical cost modeling (TCM) as a filter to evaluate alternate designs. Despite the data limitations of early design concepts, TCM can be used to identify key trends for cost-effectiveness between design variants. A compact body-in-white architecture will be used as a case study to illustrate this technique. The baseline steel structure will be compared to several alternate aluminum intensive structures in the context of production volume.

This paper introduces a new design for alternator systems that provides dramatic increases in peak and average power output from a conventional Lundell alternator, along with substantial improvements in efficiency. Experimental results demonstrate these capability improvements. Additional performance and functionality improvements of particular value for high-voltage (e.g., 42 V) alternators are also demonstrated. Tight load-dump transient suppression can be achieved using this new design and the alternator system can be used to implement jump charging (the charging of the high-voltage system battery from a low-voltage source). Dual-output extensions of the technique (e.g., 42/14 V) are also introduced. The new technology preserves the simplicity and low cost of conventional alternator designs, and can be implemented within the existing manufacturing infrastructure.

This paper presents a numerical model of the rotational and lateral dynamics of the piston (secondary motion) and piston slap in mixed lubrication. Piston dynamic behavior, frictional and impact forces are predicted as functions of crank angle. The model considers piston skirt surface waviness, roughness, skirt profile, thermal and mechanical deformations. The model considers partially-flooded skirt and calculates the pressure distributions and friction in the piston skirt region for both hydrodynamic and boundary lubrication. Model predictions are compared with measurements of piston position using gap sensors in a single-cylinder engine and the comparison between theory and measurement shows remarkable agreement.

Aircraft designers determine the optimum aircraft configuration to meet performance requirements. Aircraft secondary power systems are very important for aircraft operation, however, traditionally these systems have not been considered in detail while the aircraft configuration and specifications are preliminary studied. Therefore, we constructed an aircraft conceptual design tool considering the many aircraft systems. Furthermore, we applied this design tool to a simple design problem taking into account two different kinds of secondary power system architectures (i.e. the conventional bleed air system and the more electric system), and discussed how the introduction of new aircraft systems affects results. Although the present method is theoretical and conceptual with limited applicability, the effect of the aircraft's secondary power system upon the concerning aircraft specifications was made clear both for the bleed air system and the more electric system.

Low volume manufacturing has become increasingly important for the automotive industry. Globalization trends have led automakers and their suppliers to operate in developing regions where minimum efficient scales can not always be achieved. With proper maintenance, standard cast iron stamping tools can be used to produce millions of parts, but require large investments. Thus at high production volumes, the impact of the tooling investment on individual piece costs is minimized. However, at low volumes there is a substantial cost penalty. In light of the trends towards localized manufacturing and relatively low demands in some developing markets, low cost stamping tools are needed. Several alternate tooling technologies exist, each of which require significantly lower initial investments, but suffer from greatly reduced tool lives. However, the use of these technologies at intermediate to high volumes requires multiple tool sets thus eliminating their cost advantage.

Rare earths are a group of elements whose availability has been of concern due to monopolistic supply conditions and environmentally unsustainable mining practices. To evaluate the risks of rare earths availability to automakers, a first step is to determine raw material content and value in vehicles. This task is challenging because rare earth elements are used in small quantities, in a large number of components, and by suppliers far upstream in the supply chain. For this work, data on rare earth content reported by vehicle parts suppliers was assessed to estimate the rare earth usage of a typical conventional gasoline engine midsize sedan and a full hybrid sedan. Parts were selected from a large set of reported parts to build a hypothetical typical mid-size sedan. Estimates of rare earth content for vehicles with alternative powertrain and battery technologies were made based on the available parts' data.

To address the growing need for detailed chemistry in engine simulations, new software tools and validated data sets are being developed under an industry-funded consortium involving members from the automotive and fuels industry. The results described here include systematic comparison and validation of detailed chemistry models using a wide range of fundamental experimental data, and the development of software tools that support the use of detailed mechanisms in engineering simulations. Such tools include the automated reduction of reaction mechanisms for targeted simulation conditions. Selected results are presented and discussed.

A design framework based on the principles of lean manufacturing and axiomatic design was used as a guideline for designing an automotive component manufacturing system. A brief overview of this design decomposition is given to review its structure and usefulness. Examples are examined to demonstrate how this design framework was applied to the design of a gear manufacturing system. These examples demonstrate the impact that low-level design decisions can have on high-level system objectives and the need for a systems-thinking approach in manufacturing system design. Results are presented to show the estimated performance improvements resulting from the new system design.

Automated vehicles (AVs)—and the automated driving systems (ADSs) that enable them—are increasing in prevalence but remain far from ubiquitous. Progress has occurred in spurts, followed by lulls, while the motor transportation system learns to design, deploy, and regulate AVs. Automated Vehicles: A Human/Machine Co-learning Experience focuses on how engineers, regulators, and road users are all learning about a technology that has the potential to transform society. Those engaged in the design of ADSs and AVs may find it useful to consider that the spurts and lulls and stakeholder tussles are a normal part of technology transformations; however, this report will provide suggestions for effective stakeholder engagement. Click here to access the full SAE EDGETM Research Report portfolio.

Two critical milestones that must be achieved during concept design are 1) definition of a product architecture that meets performance, producibility, and strategic objectives, and 2) estimation of the integration risk in each candidate concept. This paper addresses these issues by describing the role played by the producibility members of an Integrated Product Team (IPT) during concept design. Our focus is on the execution of the what we call the “chain method”, which illustrates the structure of function delivery in a concept in a simple pictorial way and helps the IPT to understand the advantages or disadvantages of using a modular or an integral product architecture. The producibility members play a central role in capturing and evaluating the chains for different candidate concepts and decompositions.

In today's highly competitive automotive markets manufacturers must provide high quality products to survive. Manufacturers can achieve higher levels of quality by changing or improving their manufacturing process and/or by product inspection where many strategies with different cost implications are often available. Cost of Quality (CoQ) reconciles the competing objectives of quality maximization and cost minimization and serves as a useful framework for comparing available manufacturing process and inspection alternatives. In this paper, an analytic CoQ framework is discussed and some key findings are demonstrated using a set of basic inspection strategy scenarios. A case of a welded automotive assembly is chosen to explore the CoQ tradeoffs in inspection strategy selection and the value of welding process improvement. In the assembly process, many individual components are welded in series and each weld is inspected for quality.

This paper assesses the potential improvement of automotive powertrain technologies 25 years into the future. The powertrain types assessed include naturally-aspirated gasoline engines, turbocharged gasoline engines, diesel engines, gasoline-electric hybrids, and various advanced transmissions. Advancements in aerodynamics, vehicle weight reduction and tire rolling friction are also taken into account. The objective of the comparison is the potential of anticipated improvements in these powertrain technologies for reducing petroleum consumption and greenhouse gas emissions at the same level of performance as current vehicles in the U.S.A. The fuel consumption and performance of future vehicles was estimated using a combination of scaling laws and detailed vehicle simulations. The results indicate that there is significant potential for reduction of fuel consumption for all the powertrains examined.

Knowledge mapping is a first and mandatory step in creation of system architecture. This paper considers the conceptual modeling of automotive systems, and discusses the creation of a knowledge-based model with respect to the Object Process Methodology an approach used in designing intelligent systems by depicting them using object models and process models. With this knowledge, systems engineer should consider what a product is comprised of (its structure), how it operates (its dynamics), and how it interacts with the environment. As systems have become more complex, a prevalent problem in systems development has been the number of accruing errors. A clearly defined and consistent mapping of knowledge regarding structure, operation and interaction is necessary to construct an effective and useful system. An interactive, iterative and consistent method is needed to cope with this complex and circular problem.

Reliable means for on-board detection of particulate filter failures or malfunctions are needed to meet diagnostics (OBD) requirements. Detecting these failures, which result in tailpipe particulate matter (PM) emissions exceeding the OBD limit, over all operating conditions is challenging. Current approaches employ differential pressure sensors and downstream PM sensors, in combination with particulate filter and engine-out soot models. These conventional monitors typically operate over narrowly-defined time windows and do not provide a direct measure of the filter’s state of health. In contrast, radio frequency (RF) sensors, which transmit a wireless signal through the filter substrate provide a direct means for interrogating the condition of the filter itself.

Enhanced information management techniques made available through emerging Information Technology platforms hold a promise of providing significant improvements in both the effectiveness and efficiency of developing complex products. Determining actual management implementations that deliver on this promise has often proven elusive. Work in conjunction with the Lean Aircraft Initiative at MIT has revealed a straight forward use of Information Technology that portends significant cost reductions. By integrating previously separate types of data involved in the process of product development, engineers and designers can make decisions that will significantly reduce ultimate costs. Since the results presented are not specific to particular technologies or manufacturing processes, the conclusions are broadly applicable.