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ECOtality North America, in partnership with the Idaho National Laboratory (INL), Nissan North America, General Motors, and over 40 government, electric utility, and private organizations, has launched a large-scale demonstration of electric vehicle charging infrastructure. This demonstration, called The EV Project, will deploy more than 15,000 level 2 and DC fast chargers in private residence, commercial, and public locations in seven market areas in Arizona, California, Oregon, Tennessee, Texas, Washington state, and Washington, D.C. The EV Project will also include a total of 5,700 Nissan Leaf battery electric vehicles and 2,600 Chevrolet Volt extended range electric vehicles, operated by consumers and fleets in each of the market areas. This demonstration, which is funded by the U.S. Department of Energy�s (DOE) Vehicle Technologies Program, represents the largest ever deployment of electric vehicles and charging infrastructure.

There are many macro drivers that are creating opportunities for transportation electrification. They include the environment, dependence on foreign oil, national security, battery technology and government incentives to name a few. In light of this growing momentum consumers will have choices to where they can charge ? at home, workplace or publicly. Electrical vehicle supply equipment will drive value throughout the supply chain ? installer, building owner, automaker, suppliers, utilities and consumers. Market acceptance will occur when consumer?s needs and wants are met. To meet these needs access to products through multiple channels will be required. Presenter Manoj Karwa, Leviton Manufacturing Co. Inc.

Career development is no longer something you focus on in your twenties and are set for life, it is ongoing and constant. New technologies, globalization and the world-wide competition for jobs demand that we continue to grow our skills and knowledge throughout our life. This session will provide you with tools to help you meet this demand as an engineering professional. Participants will create a personal mission statement and set career goals, identify the best way to research new opportunities and build their network while also crafting a personal brand with consistent messaging. Organizer Martha Schanno, SAE International Panelist Caryn Mateer, Transformational Leaders Intl. Kathleen Riley, Transformational Leaders Intl.

Edgewater Computer Systems Inc. product RTEdge Platform 1.2 is a software toolset supporting proof based engineering, implementation and deployment of software components, built using the RTEdge AADL Microkernel modeling subset. This is a small subset of the AADL component model and execution semantics, covering threads and thread-groups communicating solely through asynchronous event ports and through explicitly shared data ports. Threads behavior is expressed as state machines and dispatch run time semantics is encoded in a Run-time Executive, enforcing pre-emptive priority dispatch based on statically assigned event priorities, with ceiling priority protocol access to shared data. This simple AADL microkernel semantic core can support all dispatch policies, communication and synchronization mechanisms of a fully fledged AADL run time environment, permitting the systematic use of the RTEdge static analysis tools for AADL compliant software components.

: Fiber Placement equipment has historically been very large and very expensive. Therefore, the AFP process has been mostly exclusive to the larger aerospace companies of the world. In order to achieve more widespread use of the AFP process, a wider variety of machine configurations must be offered and cost of the equipment must be decreased. Commercially available, articulated robotic arms have been identified as an attractive, low cost option for AFP machine platforms. However, incorporating AFP material delivery technology with robotic arms has many challenges. These challenges relate to both hardware and software issues. This presentation will address the technical challenges of using robots as a machine platform for the AFP process and review the current status of this composites lamination equipment technology. Presenter Frederic Challois, Coriolis Composites

Understanding in-use fleet operating behavior is of paramount importance when evaluating the potential of advanced/alternative vehicle technologies. Accurately characterizing real world vehicle operation assists in properly allocating advanced technologies, playing a role in determining initial payback period and return on investment. In addition, this information contributes to the design and deployment of future technologies as the result of increased awareness regarding tractive power requirements associated with typical operating behavior. In this presentation, the concept of vehicle duty cycles and their relation to advanced technologies will be presented and explored. Additionally, current research attempts to characterize school bus operation will be examined, and existing computational analysis and evaluation tools associated with these efforts discussed. Presenter Adam Duran, National Renewable Energy Laboratory

Historically, the opposed-piston, two-stroke (OP2S) diesel engine set combined records for fuel efficiency and power density that have yet to be met by any other engine type. However, with modern emissions standards, wide-spread development of this engine for on-highway use stopped. At Achates Power, state-of-the-art analytical tools and engineering methods have produced an OP2S engine that, when compared to a leading medium-duty engine, has demonstrated a 21% fuel efficiency gain and engine-out emissions levels meeting U.S. EPA10 with conventional after-treatment. Among the presentation topics covered are thermodynamic efficiency, demonstrated engine results, cost and weight advantages, and overcoming two-stroke engine challenges. Presenter David Johnson, Achates Power Inc.

Abstract Effects of process parameters such as rotational speed, feed rate, and drill diameters on the drilling behavior of basalt-epoxy-based composites including 2.5 wt.% Al2O3 particles manufactured by mixing and compression method were investigated by Taguchi’s technique. The experimental results showed that the burr height (BH) increased considerably almost linearly with an increase in the drill diameter, while it remained stable with speed and decreased the feed rate slightly. There was an excellent correlation between the control factors and responses, BH of basalt fiber-reinforced plastics (BFRPs) through the Taguchi approach. The model had an adjusted R2 value of 96.3%. Generally, the inclusion of Al2O3 particles in BFRP increased its cutting force properties. Optimized drilling conditions for the input variables to produce the lowest response of the BH for composites were rotational speed of 560 rpm and feed rate of 0.28 mm/rev and a drill diameter of 4.5 mm.

Abstract Automated guided vehicle systems (AGVS) are the prominent one in modern material handling systems used in small manufacturing enterprises (SMEs) due to their exciting features and benefits. This article pinpoints the need of AGVS in SMEs by describing the material handling selection in SMEs and enlightening recent technological developments and approaches of the AGVS. Additionally, it summarizes the analytical and simulation-based tools utilized in design problems of AGVS along with the influence of material handling management and key hurdles of AGVS. The current study provides a limelight towards making smart automated guided vehicles (AGVs) with the simplified and proper routing system and favorable materials and more importantly reducing the cost and increasing the flexibility.

Abstract In an automated machining process, monitoring the conditions of the tool is essential for deciding to replace or repair the tool without any manual intervention. Intelligent models built with sensor information and machine learning techniques are predicting the condition of the tool with good accuracy. In this study, statistical models are developed to identify the conditions of the abrasive grinding wheel using the Acoustic Emission (AE) signature acquired during the surface grinding operation. Abrasive grinding wheel conditions are identified using the abrasive wheel wear plot established by conducting experiments. The piezoelectric sensor is used to capture the AE from the grinding process, and statistical features of the abrasive wheel conditions are extracted in time and wavelet domains of the signature. Machine learning algorithms, namely, Classification and Regression Trees (CART) and Support Vector Classifiers (SVC), are used to build statistical models.

Abstract The proposed approach present the development of a computer tool that allows, in the first phase, the modeling of the electric vehicle power chain. This phase is based on a library developed under the Matlab-Simulink simulation environment. This library contains all the components of the power chain; it offers the selection of the desired configuration of each component. In the second phase, the tool solves the autonomy optimization problem. This problem is resolved by a program based on genetic algorithms. This program permits to optimize the configuration parameters maximizing the vehicle autonomy of the chosen chain. This tool is based on a graphical interface developed under the Matlab simulation environment.

This SAE Aerospace Information Report is to supplement content from ARP4163 pertaining to error analysis on the use of multiple drive adapter applications, on both vertical and horizontal balance machines. This new Aerospace Information Report will serve as a practical resource that offers guidance to the Machine Operator and Process Engineer.

to provide industry with a reference document highlighting the necessary design considerations and configuration option for an aircraft fully enclosed test facility (Hush House).

The goal of this new document is to provide criteria for managing, auditing, and controlling the use of rotating balancing tooling and associated support tools. A variety of subjects will be addressed including serialization and marking requirements, critical inspection criteria, performance tracking through tooling compensation trend analysis, handling of gage standards (rotor simulators, master blades, dummy blades, etc.), recommendations for periodic and preventive maintenance intervals, test recommendations to evaluate rotating tooling performance, requirements for traceable measures (such as torques, runouts, eccentricity, etc.), repeatability characterization, and criteria for return to service.

Porous materials are extensively used in the construction of automotive sound package parts, due to their intrinsic capability of dissipating energy through different mechanisms. The issue related to the optimization of sound package parts (in terms of weight, cost, performances) has led to the need of models suitable for the analysis of porous materials' dynamical behavior and for this, along the years, several analytical and numerical models were proposed, all based on the system of equations initially developed by Biot. In particular, since about 10 years, FE implementations of Biot's system of equations have been available in commercial software programs but their application to sound package parts has been limited to a few isolated cases. This is due, partially at least, to the difficulty of smoothly integrating this type of analyses into the virtual NVH vehicle development.

The materials defined by this U.S. CAR / S.A.E Recommended Practice are low VOC water based coatings for automotive tooling and general maintenance.

Digital human modeling allows for the evaluation of equipment designs before physically building and testing prototypes. This paper presents an example of how digital human modeling was used to perform biomechanical studies on four new designs for future infantry headwear systems. Range of Motion (ROM) and cervical spine forces and moments were compared using static and dynamic simulations in a virtual environment. Results confirmed that headwear system prototypes with optimal overall mass and Centre of Mass (CM) location, as determined by previous human subject trials, exerted the least amount of biomechanical loading. Facial protection was favorable when considering forces and moments in the cervical spine, however when considering ROM, the rigid prototype mandible guards used in this evaluation are not recommended. The shape of a more accommodating mandible guard was developed, and the option to remove facial protection for some tasks was recommended.

This paper focuses on full body dynamical analysis of car ingress/egress motion. It aims at proposing an experimental protocol adapted for analysing joint loads using inverse dynamics. Two preliminary studies were first performed in order to 1/ define the main driver/car interactions so as to allow measuring the contact forces at all possible contact zones and 2/ identify the design parameters that mainly influence the discomfort. In order to verify the feasibility of the protocol, a laboratory study was carried out, during which two subjects tested two car configurations. The experimental equipment was composed of a variable car mock-up, an optoelectronic motion tracking system, two 6D-force plates installed on the ground next to the doorframe and on the car floor, a 6D-Force sensor between the steering wheel and the steering column, and two pressure maps on the seat. Motions were reconstructed from measured surface markers trajectories using inverse kinematics.

Inferential sensing, as it relates to the equipment operator, can be viewed as human intuition [1]. The person operating the equipment can sense there is something wrong while their intuition tells them when and what needs troubleshooting and repair. Attempts have been made to implement this human intuition model to monitor a vehicle operation and detect abnormalities. In many approaches traditional sensors are added to the vehicle which increases cost, complexity, and another failure point. After years of developments and techniques, there are few highly reliable on-board systems that can duplicate the human intuition model since the specific failure cannot be directly measured but must be inferred from a variety of symptoms. This paper describes an engineering approach using Physics of Failure (PoF) for specific subsystems, developing the applicable fatigue models, and then collecting, monitoring, and manipulating the real-time on-vehicle data to complement the “operator intuition”.

Model-Based Design with production code generation has been extensively utilized throughout the automotive software engineering community because of its ability to address complexity, productivity, and quality challenges. With new applications such as lane departure warning or electromechanical steering, engineers have begun to consider Model-Based Design to develop embedded software for applications that need to comply with safety standards such as IEC 61508. For in-vehicle applications, IEC 61508 is often considered state-of-the-art or generally accepted rules of technology (GART) for development of high-integrity software [6, 11]. In order to demonstrate standards compliance, the objectives and recommendations outlined in IEC 61508-3 [8] must be mapped onto processes and tools for Model-Based Design. This paper discusses a verification and validation workflow for developing in-vehicle software components which need to comply with IEC 61508-3 using Model-Based Design.