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Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

Health Ready Components are essential to unlocking the potential of Integrated Vehicle Health Management (IVHM) as it relates to real-time diagnosis and prognosis in order to achieve lower maintenance costs, greater asset availability, reliability and safety. IVHM results in reduced maintenance costs by providing more accurate fault isolation and repair guidance. IVHM results in greater asset availability, reliability and safety by recommending preventative maintenance and by identifying anomalous behavior indicative of degraded functionality prior to detection of the fault by other detection mechanisms. The cost, complexity and effectiveness of the IVHM system design, deployment and support depend, to a great extent, on the degree to which components and subsystems provide the run-time data needed by IVHM and the design time semantic data to allow IVHM to interpret those messages.

The United States Department of Transportation (USDOT) and the Crash Avoidance Metrics Partnership-Vehicle Safety Communications 2 (CAMP-VSC2) Consortium (Ford, General Motors, Honda, Mercedes-Benz, and Toyota) initiated, in December 2006, a three-year collaborative effort in the area of wireless-based safety applications under the Vehicle Safety Communications-Applications (VSC-A) Project. The VSC-A Project developed and tested Vehicle-to-Vehicle (V2V) communications-based safety systems to determine if Dedicated Short Range Communications (DSRC) at 5.9 GHz, in combination with vehicle positioning, would improve upon autonomous vehicle-based safety systems and/or enable new communications-based safety applications.

The diverse and complex requirements of next-generation energy optimized aircraft (EOA) demand detailed transient and dynamic model-based design (MBD) to ensure the proper operation of numerous interconnected and interacting subsystems. In support of the U.S. Air Force's Integrated Vehicle Energy Technology (INVENT) program, several software tools have been developed and are in use that aid in the efficient MBD of next-generation EOA. Among these are subsystem model libraries, automated subsystem model verification test scripts, a distributed co-simulation application, and tools for system configuration, EOA mission building, data logging, plotting, post-processing, and visualization, and energy flow analysis. Herein, each of these tools is described. A detailed discussion of each tool's functionality and its benefits with respect to the goal of achieving successful integrated system simulations in support of MBD of EOA is given.

Model-Based Development processes in the automotive industry typically use high-level modeling languages to build the reference models of embedded controllers. One can use formal verification tools to exhaustively verify these design models against their requirements, ensuring high quality models and a reduction in the cost and effort of functional testing. However, there is a gap, in terms of processes and tools, between the informal requirements and the formal specifications required by the verification tools. In this paper, we propose an approach that tries to bridge this gap by (i) identifying the verifiable requirements through a categorization process, (ii) providing a set of templates to easily express the verifiable requirements, and (iii) generating monitors that can be used as specifications in design verification tools. We demonstrate our approach using the Simulink Design Verifier tool for design verification of Simulink/Stateflow models.

Fully autonomous systems are seen as the ultimate solution to all manufacturing problems due to their consistent quality and ability to improve rates, but they also have one key disadvantage: Limited equipment versatility. This shortcoming becomes most apparent when trying to apply automation to aircraft final assembly. The variety of jobs is great and would necessitate the development of many unique solutions. Therefore a robotic system designed for one job on one aircraft version might be useless on the next version. Also there are many tight spaces and complex jobs where automation is just not practical, meaning that workers with portable tools will always have some presence in production. The modern smart portable tool as exemplified by the Novator PM Series orbital drill motor is capable of matching the quality and speed of a robotic system while still maintaining the ability to be applicable over a wide variety of jobs.

To cope with the increasing number of advanced features (e.g., smart-phone integration and side-blind zone alert.) being deployed in vehicles, automotive manufacturers are designing flexible hardware architectures which can accommodate increasing feature content with as fewer as possible hardware changes so as to keep future costs down. In this paper, we propose a formal and quantitative definition of flexibility, a related methodology and a tool flow aimed at maximizing the flexibility of an automotive hardware architecture with respect to the features that are of greater importance to the designer. We define flexibility as the ability of an architecture to accommodate future changes in features with no changes in hardware (no addition/replacement of processors, buses, or memories). We utilize an optimization framework based on mixed integer linear programming (MILP) which computes the flexibility of the architecture while guaranteeing performance and safety requirements.

The Time Variant Discrete Fourier Transform was implemented as a real-time order tracking method using developed software and commercially available hardware. The time variant discrete Fourier transform (TVDFT) with the application of the orthogonality compensation matrix allows multiple tachometers to be tracked with close and/or crossing orders to be separated in real-time. Signal generators were used to create controlled experimental data sets to simulate tachometers and response channels. Computation timing was evaluated for the data collection procedure and each of the data processing steps to determine how each part of the process affects overall performance. Many difficulties are associated with a real-time data collection and analysis tool and it becomes apparent that an understanding of each component in the system is required to determine where time consuming computation is located.

This paper reports on the experimental study of carbide and polycrystalline diamond (PCD) drills used for drilling composite/titanium stacks. Materials systems used in this study were multi-directional carbon fiber in an epoxy matrix and titanium 6Al-4V. The drill materials included tungsten carbide (WC; 9%Co ultra fine grain) and polycrystalline diamond (PCD; bimodal grade). Torque and thrust force were measured during the drilling experiments. Tool wear of both drills was periodically examined during the drilling tests using various microscopic techniques such as optical and Scanning Electron Microscope (SEM). Effect of tool materials and process condition on hole quality parameters such as hole diameter, surface roughness, and titanium burrs, were examined. Dissimilar mechanical and thermal properties of the stacks affected the tool life and resulted in the decreased hole quality for both cutting tool materials, although to a differing degree.

Key fobs, also known as remote keys or remote transmitters, have become a common piece of equipment in today's vehicle, being ubiquitous in every market segment. Once limited to remote locking and unlocking operations, today's key fobs can be used to control many comfort and security features beyond locking and unlocking, such as alarm system operation, vehicle locate, approach lighting, memory seat recall, and remote starting systems. Key fobs are designed to be easy to use as well as easy to carry and transport in personal containers, such as purses, pockets, wallets, and the like. Accordingly, as with other personal effects, key fobs and other portable remote devices can be lost or misplaced or can be otherwise difficult to find. Even with careful tracking of a remote device, children and pets, among other factors, can make location difficult. Moreover, multiple remote devices are often distributed with each vehicle.

The usage of multi-body dynamics tools for the prediction of vehicle system/sub-system loads, has significantly reduced the need to measure vehicle loads at proving grounds. The success of these tools is limited by the quality of the digital representations being used to simulate the physical test roads. The development of these digital roads is not a trivial task due to the large quantity of data and processing required. In the end, the files must be manageable in size, have a globally common format, and be simulation-friendly. The authors present a methodology for the development of high quality 3-dimensional (3-D) digital proving ground profiles. These profiles will be used in conjunction with a multi-body dynamics software package (ADAMS) and the FTire™ model. The authors present a case study below.

As an innovative electric vehicle with some new approaches to energy usage and vehicle performance balance, the Chevy Volt required a special relationship between the OEM and tire supplier community. This paper details this relationship and how advanced tools and technology were leveraged between OEM and supplier to achieve tire component and overall vehicle performance results.

For many years, the computer aided math model has been the foundation for lowering cost and reducing time to market for many manufacturing industries. The automotive industry applies a variety of tools and methods to evaluate the expected vehicle performance to a forever expanding set of requirements. These mathematical predictions of performance are then repeated for both a set of design cycles and a multitude of vehicles in the product portfolio. This paper presents a CAE perspective of the unique problems of the large scale virtual vehicle engineering factory and a set of solutions. Different strategies to create the various complex math models required are explored. These strategies include using COTS FEA pre-processers, producing FEA models internal to the CAD tools, as well as custom built tools, macros and process automation tools.

As part of standardizing the global portfolio, General Motors (GM) created an electrical architecture that will support the GM global product feature set. Introduced in 2009, this common electrical architecture is already being applied to multiple platforms in GM's regional engineering centers. The electrical architecture will be updated regularly to address the needs of new features in the automotive market and to take advantage of the latest technology advancements. The functional requirements of these new features result in technology challenges. In addition, many new features may result in challenges to the vehicle electrical architecture or the vehicle development process. The challenges have been evaluated so that needs and initiatives can be better understood.

Automotive HW/SW architectures are becoming increasingly complex to support the deployment of new safety, comfort, and energy-efficiency features. Such architectures include several software tasks (100+), messages (1000+), computational and communication resources (70+ CPUs, 10+ buses), and (smart) sensors and actuators (20+). To cope with the increasing system complexity at lowest development and product costs, highest safety, and fastest time to market, model-based rapid-prototyping development processes are essential. The processes, coupled with optimization steps aimed at reducing the number of software and hardware resources while satisfying the safety requirements, enable reduction of the system complexity and ease downstream testing/validation efforts. This paper describes a novel model-based design exploration and optimization process for the deployment of a set of software tasks on a dual-processor control module implementing a fail-safe strategy.

Vehicle development typically occurs by independently documenting requirements for individual subsystems, then packaging these subsystems into the vehicle and testing the feature operation at a higher level, across multiple subsystems. Many times, this independent development process results in integration problems at the vehicle level, such as incomplete feature execution, unexpected operation and information disconnects. The development team is left to debug and create inefficient patches at the vehicle level due to time constraints and / or planned release dates. Without architecting solutions at the feature level, miscommunication of expected feature operation leads to wasted time, re-work and customer dissatisfaction. While the development of vehicle level technical specifications provide feature expectations at the vehicle level, they do not solve the problem of how this operation is to be applied across multiple systems.

A numerical and corresponding experimental study was undertaken to identify the ability to accurately predict combustion performance using our 3-D numerical tools for a direct-injection homogeneous-charge engine. To achieve a significant range of combustion rates, the evaluation was conducted for the engine operating with and without enhanced charge motion. Five charge motion configurations were examined, each having different levels of swirl and tumble flow leading to different turbulence generation and decay characteristics. A detailed CFD analysis provides insight into the in-cylinder flow requirements as well as the accuracy of the submodels. The in-cylinder air-fuel distribution, the mass-averaged swirl and tumble levels along with mean flow and turbulent kinetic energies are calculated throughout the induction and compression processes.

The Sensory Prognostics and Management Systems (SPMS) program sponsored by the Federal Aviation Administration and Boeing developed and evaluated designs to integrate advanced diagnostic and prognostic (i.e., Integrated Vehicle Health Management (IVHM) or Health Management (HM)) capabilities onto commercial airplanes. The objective of the program was to propose an advanced HM system appropriate for legacy and new aircraft and examine the technical requirements and their ramifications on the current infrastructure and regulatory guidance. The program approach was to determine the attractive and feasible HM applications, the technologies that are required to cost effectively implement these applications, the technical and certification challenges, and the system level and business consequences of such a system.

The SAE J2716 SENT (Single Edge Nibble Transmission) Protocol has entered production with a number of announced products. The SENT protocol is a point-to-point scheme for transmitting signal values from a sensor to a controller. It is intended to allow for high resolution data transmission with a lower system cost than available serial data solution. The SAE SENT Task Force has developed a number of enhancements and clarifications to the original specification which are summarized in this paper.

Recent trends in signal processing have led to the discovery and implementation of wavelets as tools of many different applications. This paper focuses on their use as a tool for transient extraction. From the Discrete Wavelet Transform (DWT), specific coefficients are picked using a coherence-based criterion. These coefficients are then taken back to the time domain as the extracted transient. If the extracted transient is a response from a measured input, then a frequency response function can be formulated.