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With the introduction of plug-in electric vehicles (PEVs), the conventional mindset of “fill-up time” will be challenged as customers top off their battery packs. For example, using a standard 120VAC outlet, it may take over 10hrs to achieve 40-50 miles of EV range-making range anxiety a daunting reality for EV owners. As customers adapt to this new mindset of charge time, it is critical that automotive OEMs supply the consumer with accurate charge time estimates. Charge time accuracy relies on a variety of parameters: battery pack size, power source, electric vehicle supply equipment (EVSE), on-board charging equipment, ancillary controller loads, battery temperature, and ambient temperature. Furthermore, as the charging events may take hours, the initial conditions may vary throughout a plug-in charge (PIC). The goal of this paper is to characterize charging system sensitivities and promote best practices for charge time estimations.

Spine degeneration can lower injury tolerance and influence injury outcomes in vehicle crashes. To date, limited information exists on the effect of age and sex on thoracic spine 3-dimensional geometry. The purpose of this study is to quantify thoracic spinal column and canal geometry using selected geometrical measurement from a large sample of CT scans. More than 33,488 scans were obtained from the International Center for Automotive Medicine database at the University of Michigan under Institutional Review Board approval (HUM00041441). The sample consisted of CT scans obtained from 31,537 adult and 1,951 pediatric patients between the ages of 0 to 99 years old. Each scan was processed semi-automatically using custom algorithms written in MATLAB (The Math Works, Natick, MA). Five geometrical measurements were collected including: 1) maximum spinal curvature depth (D), 2) T1-to-T12 vertical height (H), 3) Kyphosis Index (KI), 4) kyphosis angle, and 5) spinal canal radius.

The energy dissipated by the fracture of wooden utility poles during vehicle impacts is not currently well documented, is dependent upon non-homogenous timber characteristics, and can therefore be difficult to quantify. While there is significant literature regarding the static and quasi-static properties of wood as a building material, there is a narrow body of literature regarding the viscoelastic properties of timber used for utility poles. Although some theoretical and small-scale testing research has been published, full-scale testing has not been conducted for the purpose of studying the vehicle-pole interaction during impacts. The parameters that define the severity of the impact include the acceleration profile, vehicle velocity change, and energy dissipation. Seven full-scale crash tests were conducted at Exponent's Arizona test facility utilizing both moving deformable and non-deformable barriers into new wooden utility poles.

Forward Collision Alert (or Forward Collision Warning) systems provide alerts intended to assist drivers in avoiding or mitigating the harm caused by rear-end crashes. These systems currently use front-grille mounted, forward-looking radar devices as the primary sensor. In contrast, Lane Departure Warning (LDW) systems employ forward-looking cameras mounted behind the windshield to monitor lane markings ahead and warn drivers of unintended lane violations. The increasing imaging sensor resolution and processing capability of forward-looking cameras, as well recent important advances in machine vision algorithms, have pushed the state-of-the-art for camera-based features. Consequently, camera-based systems are emerging as a key crash avoidance system component in both a primary and supporting sensing role. There are currently no production vehicles with cameras used as the sole FCA sensing device.

Handling and tire performance continue to evolve due to significant improvements in vehicle, electronics, and tire technology over the years. This paper examines the trends in handling and tire performance metrics for production cars and trucks since the 1980's. This paper is based on a significant number of directional response and tire tests conducted during that period. It describes ranges of these parameters and shows how they have changed over the past thirty years.

General Motors' (GM) eAssist powertrain builds upon the knowledge and experience gained from GM's first generation 36Volt Belt-Alternator-Starter (BAS) system introduced on the Saturn VUE Green Line in 2006. Extensive architectural trade studies were conducted to define the eAssist system. The resulting architecture delivers approximately three times the peak electric boost and regenerative braking capability of 36V BAS. Key elements include a water-cooled induction motor/generator (MG), an accessory drive with a coupled dual tensioner system, air cooled power electronics integrated with a 115V lithium-ion battery pack, a direct-injection 2.4 liter 4-cylinder gasoline engine, and a modified 6-speed automatic transmission. The torque-based control system of the eAssist powertrain was designed to be fully integrated with GM's corporate common electrical and controls architectures, enabling the potential for broad application across GM's global product portfolio.

Conventional HVAC systems adjust the position of a temperature door, to achieve a required air temperature discharged into the passenger compartment. Such systems are based upon the fact that a conventional (non-hybrid) vehicle's engine coolant temperature is controlled to a somewhat constant temperature, using an engine thermostat. Coolant flow rate through the cabin heater core varies as the engine speed changes. EREVs (Extended Range Electric Vehicles) & PHEVs (Plug-In Hybrid Electric Vehicles) have two key vehicle requirements: maximize EV (Electric Vehicle) range and maximize fuel economy when the engine is operating. In EV mode, there is no engine heat rejection and battery pack energy is consumed in order to provide heat to the passenger compartment, for windshield defrost/defog and occupant comfort. Energy consumption for cabin heating must be optimized, if one is to optimize vehicle EV range.

As vehicle fuel economy continues to grow in importance, the ability to accurately measure the level of efficiency on all driveline components is required. A standardized test procedure enables manufacturers and suppliers to measure component losses consistently and provides data to make comparisons. In addition, the procedure offers a reliable process to assess enablers for efficiency improvements. Previous published studies have outlined the development of a comprehensive test procedure to measure transfer case speed-dependent parasitic losses at key speed, load, and environmental conditions. This paper will take the same basic approach for the Power Transfer Units (PTUs) used on Front Wheel Drive (FWD) based All Wheel Drive (AWD) vehicles. Factors included in the assessment include single and multi-stage PTUs, fluid levels, break-in process, and temperature effects.

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 battery system in the Chevrolet Volt is very complex and must balance a variety of performance criteria, including the safety of vehicle occupants and other users. In order to assure a thorough approach to battery system safety, a system safety engineering process was applied and found to provide a useful framework. This methodical approach began with the preliminary hazard analysis and continued through requirements definition, design development and, finally, validation. Potentially hazardous conditions related directly to functional safety (for example, charge control) and primary physical safety (for example, short circuit conditions) can all be addressed in this manner. Typical battery abuse testing, as well as newly defined limit testing, supported the effort. Extensive documentation, traceability and peer reviews helped to verify that all issues were addressed.

Modular instrumentation is being widely used in noise and vibration measurement systems that demand higher channel counts and the wider dynamic range that 24-bit delta-sigma ADCs make available at lower costs. This is an overview how flexible modular instrumentation employing the latest software technology can be used in making high precision noise and vibration measurements where higher sampling rates, higher channel counts, increased dynamic range, and distributed architectures were needed in smaller packages. An example where this is being used is in acoustic beam forming in aircraft pass by noise tests to measure and distinguish engine and airframe noise sources.

LIN is a low-cost, low-speed vehicle communication sub-bus becoming increasingly pervasive in automotive subsystems. It is a simple, UART-based master-slave protocol designed as a low-speed supplement to a CAN or FlexRay bus. Its primary application is cabin comfort and human interface hardware such as dashboard controls, power seat harnesses, and power door/window systems. As automotive network designers attempt to reduce wiring complexity and lower system cost, modular, inexpensive sub-buses like LIN become an attractive option. This paper presents an overview of the LIN standard and its applications, and then proposes an architecture for rapid development of LIN networks via hardware simulations of LIN nodes. Using inexpensive, off-the-shelf hardware, LIN sensor and actuator applications can be tested in-place without microcode development, speeding overall network development time.

Companies typically invest significant time and money in choosing the proper test equipment for new automotive test systems. Yet, the architecture for proper data storage and management of the mounds of data these systems produce is often times an afterthought. Although data management may not appear as an obstacle during initial design, as the system expands, changes, and interfaces with other systems, the ability to easily access and exchange technical data becomes a critical challenge to overcome. This paper will introduce new technologies giving engineers the power to search and mine data sets to find key information and trends in the data for to rapidly turn the raw data into results.

In many measurement applications, there is a need to correlate data acquired from different systems or synchronize systems together with precise timing. Signal Based and Time Based are the two basic methods of synchronizing instrumentation. In Signal Based synchronization, clocks and triggers are physically connected between systems. Typically this provides the highest precision synchronization. In many NVH applications size and distance constrains physically connecting the systems needed for making measurements though the inter-channel phase information of simultaneously sampled signals is crucial. In Time Based synchronization, system components have a common reference of what time it is. Events, triggers and clocks can be generated based on this time.

Several advanced signal processing algorithms beyond the FFT such as time-frequency analysis, quefrency, cestrum, wavelet analysis, and AR modeling uses are outlined. These advanced algorithms can solve some sound and vibration challenges that FFT-based algorithms cannot solve. Looking at signal characteristics of a unit under test in the time-frequency plane, it is possible to get a better understanding of signal characteristics. This is an overview of these algorithms and some application examples, such as speaker testing, bearing fault detection, dashboard motor testing, and engine knock detection where they can be applied to NVH applications.

This paper examines Smart Electric Power Management as it pertains to when the vehicle charging system is active. Over the past decade there have been several factors at play which have stressed the demands placed upon the vehicle electrical power system. Many of these factors present challenges to electrical power that are at cross-purposes with one another. For example, demands of new and existing electrical loads, customer expectations about load performance and battery life, and the push by governments' world-wide for increased fuel economy (FE) and reduced CO2 emissions all have direct impact and can be directly impacted by decisions made in electric power design. As the electrification of the vehicle has progressed we now have much more specific vehicle state data available and the means to share this information among on-board computers through serial data link connectivity.

Rechargeable energy storage systems with Lithium-ion pouch cells are subject to various ambient temperature conditions and go through thousands of charge-discharge cycles during the life time of operation. The cells may change their thickness with internal heat generation, cycling and any other mechanisms. The stacked prismatic cells thus experience face pressure and this could impact the pack electrical performance. The pack consists of stiff end plates keeping the pack in tact using bolts, cooling fins to maintain cell temperature and foam padding in between cells. The pack level thermal requirements limit the amount of temperature increase during normal operating conditions. Similarly, the structural requirements state that the stresses and the deflection in the end plates should be minimal. Uncertainties in cell, foam mechanical and thermal properties might add variation to the pack performance.

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.

Recent trends in the automotive industry show growing demands for the introduction of new in-vehicle features (e.g., smart-phone integration, adaptive cruise control, etc.) at increasing rates and with reduced time-to-market. New technological developments (e.g., in-vehicle Ethernet, multi-core technologies, AUTOSAR standardized software architectures, smart video and radar sensors, etc.) provide opportunities as well as challenges to automotive designers for introducing and implementing new features at lower costs, and with increased safety and security. As a result, the design of Electrical/Electronic (E/E) architectures is becoming increasingly challenging as several hardware resources are needed. In our earlier work, we have provided top-level definitions for three relevant metrics that can be used to evaluate E/E architecture alternatives in the early stages of the design process: flexibility, scalability and expandability.

Digital human models (DHM) are now widely used to assess worker tasks as part of manufacturing simulation. With current DHM software, the simulation engineer or ergonomist usually makes a manual estimate of the likely worker standing location with respect to the work task. In a small number of cases, the worker standing location is determined through physical testing with one or a few workers. Motion capture technology is sometimes used to aid in quantitative analysis of the resulting posture. Previous research has demonstrated the sensitivity of work task assessment using DHM to the accuracy of the posture prediction. This paper expands on that work by demonstrating the need for a method and model to accurately predict worker standing location. The effect of standing location on work task posture and the resulting assessment is documented through three case studies using the Siemens Jack DHM software.