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This paper summarizes the Fast Fourier Transform (FFT) methodology, special equipment, set-up and testing that is recommended to properly characterize the surface of bearing journals that will not result in objectionable noise or vibration. Traditional surface profiles and finish callouts do not capture some of the key characteristics for addressing what is often the customer's greatest complaint, noise. Noise can vary based on the sensitivity of the vehicle but understanding how to accurately describe (design, test, and measure) a surface for a given vehicle can result in an optimized design and reduce process time during manufacturing. Furthermore, this paper will recommend techniques for determining the proper limits of the FFT callouts.

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.

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.

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.

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.

Hybrid high voltage battery pack is not only heavy mass but also large in dimension. It interacts with the vehicle through the battery tray. Thus the battery tray is a critical element of the battery pack that interfaces between the battery and the vehicle, including the performances of safety/crash, NVH (modal), and durability. The tray is the largest and strongest structure in the battery pack holding the battery sections and other components including the battery disconnect unit (BDU) and other units that are not negligible in mass. This paper describes the mass optimization work done on one of the hybrid batteries using CAE simulation. This was a multidisciplinary optimization project, in which modal performance and fatigue damage were accessed through CAE analysis at both the battery pack level, and at the vehicle level.

The engineering of electric propulsion systems requires time and cost efficient methodologies to determine system characteristics as well as potential component integration issues. A significant part of this analysis is the identification of the electromagnetic fields present in the propulsion system. Understanding of the electromagnetic fields during system operation is a significant design consideration due to the use of components that require large current(s) and high voltage(s) in the proximity of other control system items (such as sensors) that operate with low current(s) and voltage(s). Therefore, it is critical to quantify the electromagnetic fields produced by these components within the design and how they may interact with other system components. Often overlooked (and also extremely important) is an evaluation of how the overall system architecture can generate or react to electromagnetic fields (which may be a direct result of packaging approaches).

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.

The On Board Jump Start feature utilized on GM's Belt Alternator Starter (BAS) hybrids takes advantage of the High Voltage (HV) battery and other HV propulsion systems to supplement a low 12V battery during starting events. This feature has the potential to eliminate the need for an off vehicle 12V power source, such as a 2nd vehicle, to start the vehicle when the 12V battery is low.

Plug-in electric vehicles are becoming increasingly popular as the U.S. and other nations look for ways to reduce the usage of petroleum fuels and reduce the carbon emission footprint. Though plug-in electric vehicles offer many advantages over conventional vehicles, they also present some unique potential hazards due to the presence of high voltage in the vehicle. Specifically, potential high voltage hazards can occur if the electric vehicle is crashed by another vehicle during its plug-in charging session. High voltage hazards include the possibility of electrical shock and thermal events as a result of electrical arcing that can cause injury or death to persons that operate or work around plug-in electric vehicles. Automotive Safety Integrity Level (ISO 26262), often abbreviated as ASIL, is used by the automotive industry for determining the ranking of safety hazards.

An Extended Range Electric vehicle brings a wealth of new features since it is capable of driving on battery alone, has a range extending engine, and has a high voltage battery pack that can be recharged by plugging into wall power. The customer is able to interact with the vehicle's plug-in charging system through mobile applications. Along with all these new features is the challenge of designing a driver interface to provide important information to the customer. This paper will describe the unique customer interface features added to the vehicle, and will include some additional specifics related to the hardware used to provide the information.

As the auto industry becomes more dependent upon Electric Vehicles (Plug-In Hybrid Electric Vehicles, Battery Electric Vehicles, and Extended Range Electric Vehicles), the Plug-In Charging Feature will become an integral part of the driver's daily routine. The Plug-In Charging feature enables off-board electrical power grid (grid based) power to be used immediately or at a later time by on-vehicle functions. The primary use of this grid power is to charge the vehicle's High Voltage (HV) battery, but other uses also do exist. These functions will mainly be active when the vehicle is off.

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.

As the automotive industry moves toward producing more advanced hybrid/electric vehicles, high voltage Rechargeable Energy Storage Systems (RESS) are now being implemented as the main power source of the vehicle, replacing the need for the traditional Internal Combustion Engine (ICE) altogether or just during certain parts of a drive cycle. With this type of architecture, it is becoming a necessity to equip these vehicles with devices that can draw their power from the high voltage (HV) RESS. These HV devices are not only used to support the propulsion of the vehicle but to perform other necessary vehicle functions as well. With demands of high voltage power from multiple systems ranging from RESS thermal conditioning, cabin thermal conditioning, RESS charging, and vehicle propulsion, power demands can exceed the available power of the vehicle. This creates a perplexing problem of how to manage the high voltage power consumption between the different vehicle systems.

Extended Range Electric Vehicles (EREVs), which are Off board charging capable Electric Vehicles (EV) with an on board charging generator, rely on very complex Rechargeable Energy Storage Systems (RESS) and High Voltage (HV) distribution systems to enable operation as both an EV and an EREV. The connect feature manages the connection and disconnection of a High Voltage (HV) Rechargeable Energy Storage System (RESS) to and from the high voltage components in the vehicle. The RESS is connected to the vehicle's high voltage system to enable vehicle operation. The HV connect feature is a part of occupant, service personnel and first responder safety for all General Motors vehicles that contain high voltage systems. Implementation of the connect feature is the method deployed in GM vehicles to meet high voltage FMVSS requirements.

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.