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An actual trend in the automotive industry is to have global products in order to have economy of scale. This paper presents how a Belt Drive Rack EPS developed for the North American market had to be modified in order to be assembled in a Vehicle sold all around the world. Main technical challenges for achieving that goal were generated from different Architectures, whether electrical or mechanical, used in each vehicle, Packaging issues and Regional Requirements. Main features affected are Database Configuration, Electromagnetic Compatibility, Smooth Road Shake mitigation and Pull Compensation.

The die wear up to 80,800 hits on a prog-die setup for bare DP1180 steel was investigated in real production condition. In total, 31 die inserts with the combination of 11 die materials and 9 coatings were evaluated. The analytical results of die service life for each insert were provided by examining the evolution of surface wear on inserts and formed parts. The moments of appearance of die defects, propagation of die defects, and catastrophic failure were determined. Moreover, the surface roughness of the formed parts for each die insert was characterized using Wyko NT110 machine. The objectives of the current study are to evaluate the die durability of various tooling materials and coatings for flange operations on bare DP 1180 steel and update OEM tooling standards based on the experimental results. The current study provides the guidance for the die material and coating selections in large volume production for next generation AHSSs.

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.

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.

This paper presents the implementation of an off-line optimized torque vectoring controller on an electric-drive vehicle with four in-wheel motors for driver assistance and handling performance enhancement. The controller takes vehicle longitudinal, lateral, and yaw acceleration signals as feedback using the concept of state-derivative feedback control. The objective of the controller is to optimally control the vehicle motion according to the driver commands. Reference signals are first calculated using a driver command interpreter to accurately interpret what the driver intends for the vehicle motion. The controller then adjusts the braking/throttle outputs based on discrepancy between the vehicle response and the interpreter command.

With deflected-disc dampers, digressive force-velocity shapes are achieved via the combined effects of disc stack stiffness and hub-offset. The degree of digressiveness can be adjusted to alter vehicle performance by changing the proportion of these parameters. Optimizing this relationship can yield substantial vehicle performance improvements, but the time consuming iterative process of developing a new disc stack for each hub-offset discourages experimentation. To enable more efficient digressiveness comparisons, a regression-based computational method has been developed which converts disc stack stiffness from one hub-offset to other offsets directly, without iteration. Once an initial disc stack for one offset has been tuned by traditional methods, stacks for other offsets can be calculated that maintain overall damper control.

In recent years, there has been a growing interest in driver visibility. This is, in part, due to increasing emphasis placed on design factors influencing visibility such as: aerodynamics, styling, structural stiffness and vehicle packaging. During the development process of a vehicle, it is important to be able to quantify all of these factors. Visibility, however, owing to its sensory nature, has been harder to quantify. As a result, General Motors (GM) has undertaken a study to gain deeper insight into customer perceptions surrounding visibility. Clinics were conducted to help determine the relative importance of different metrics. The paper also explores several new metrics that can help predict customer satisfaction based on vehicle configuration.

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.

Determining Li-ion battery life through life modeling is an excellent tool in determining and estimating end-of-life performance. Achieving End-of-Life (EOL) can be challenging since it is difficult to achieve both cycle and calendar life during the same test without years of testing. The plan to correlate testing with the model included three (3) distinct temperature ranges, beginning with the four-Season temperature profile, an aggressive profile with temperatures in the 50 to 55°C range, and using a mid-temperature range (40-45°C) as a final comparison test. A high duty-cycle drive profile was used to cycle all of the batteries as quickly as possible to reach the one potential definition of EOL; significant increases in resistance or capacity fade.

FlexRay is a communication system targeted at, among other things, fault tolerant applications. In contrast to some other communication systems, FlexRay systems often contain a central device such as an active star. Due to their ability to isolate portions of the communication system central devices offer opportunities to mitigate certain faults. This paper presents several alternatives for the central device of a FlexRay system, specifically active stars, FlexRay switches, and Central Bus Guardians. The paper analyzes the fault detection, isolation and mitigation mechanisms of each central device based on available documentation and specifications.

Simscape is a physical modeling language developed by Mathworks Inc. The language uses equation statements instead of assignment statements to describe physical systems. The paper focuses on the Simscape language itself instead of using components in the Simscape libraries. The language will be introduced from a perspective different from the Mathworks' Physical Network point of view. Our perspective focuses on two types of variables at the connectors. In additional, internal variables are not separated into through and across variables. The alternative perspective is more general and easier to understand. The paper also illustrates how to develop components in a powertrain library following the proposed new perspective.

A Design for Six Sigma (DFSS) statistical approach is presented in this report to correlate a CFD cabin model with test results. The target is the volume-averaged hot-soak terminal temperature. The objective is to develop an effective correlation process for a simplified CFD cabin model so it can be used in practical design process. It is, however, not the objective in this report to develop the most accurate CFD cabin model that would be too expensive computationally at present to be used in routine design analysis. A 3-D CFD model of a vehicle cabin is the central part of the computer modeling in the development of automotive HVAC systems. Hot-soak terminal temperature is a thermal phenomenon in the cabin of a parked vehicle under the Sun when the overall heat transfer reaches equilibrium. It is often part of the simulation of HVAC system operation.

The projected frontal area of a vehicle has a significant impact on aerodynamic drag, and thus is an important parameter, for vehicle development, benchmarking, and modeling. However, determining vehicle frontal area can be tedious, time consuming, expensive, or inaccurate. Existing methods include analysis of engineering drawings, vehicle projections, 3D scanners, planimeter measurements from photographs, and estimations using vehicle dimensions. Currently accepted approximation methods can be somewhat unreliable. This study focuses on introducing a method to find vehicle frontal area using digital images and subtraction functions via MATLABs' Image Processing Toolbox. In addition to an overview of the method, this paper describes several variables that were examined to optimize and improve the process such as camera position, surface glare, and vehicle shadow effects.

This paper reports a study undertaken by the Crash Safety Working Group (CSWG) of the United States Council for Automotive Research (USCAR) to determine generic acceleration pulses for testing and evaluating advanced batteries subjected to inertial loading for application in electric passenger vehicles. These pulses were based on characterizing vehicle acceleration time histories from standard laboratory vehicle crash tests. Crash tested passenger vehicles in the United States vehicle fleet of the model years 2005-2009 were used in this study. Crash test data, in terms of acceleration time histories, were collected from various crash modes conducted by the National Highway Traffic Safety Administration (NHTSA) during their New Car Assessment Program (NCAP) and Federal Motor Vehicle Safety Standards (FMVSS) evaluations, and the Insurance Institute for Highway Safety (IIHS).

Insulation coordination requirements for electrical equipment applications are defined in various standards. The standards are defined for application to stationary mains connected equipment, like IT, power supply or industrial equipment. Protection from an electric shock is considered the primary hazard in these standards. These standards have also been used in the design of various automotive components. IEC 60664-1 is an example of the standard. Automobiles are used across the world, in various environments and in varied usage by the customers. Automobiles need to consider possible additional hazards including electric shock. This paper will provide an overview of how to adapt these standards for automotive application in the design of High Voltage (HV) automotive components, including High Voltage batteries and other HV components connected to the battery. The basic definitions from the standards and the principles are applied for usage in automotive applications.

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.

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.

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.