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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.

This paper describes rationale for determining the apportionment of variable or ‘shuttered’ airflow and non-variable or static airflow through openings in the front of a vehicle as needed for vehicle cooling. Variable airflow can be achieved by means of a shutter system, which throttles airflow through the front end and into the Condenser, Radiator, and Fan Module, (CRFM). Shutters originated early in the history of the auto industry and acted as a thermostat [1]. They controlled airflow as opposed to coolant flow through the radiator. Two benefits that are realized today are aerodynamic and thermal gains, achieved by restricting unneeded cooling airflow. Other benefits exist and justify the use of shutters; however, there are also difficulties in both execution and practical use. This paper will focus on optimizing system performance and execution in terms of the two benefits of reduced aerodynamic drag and reduced mechanical drag through thermal control.

This paper presents subjective and objective methods for evaluating transient vehicle dynamics characteristics in four sections: (1) Definition of transient behavior in terms of four traits-agility, stability, precision, and roll support; (2) Description of subjective evaluation methods; (3) Implementation of Design for Six Sigma principles to the development of a steering robot controlled objective test for transient performance; (4) The final section of this paper uses data from simulation and road tests to demonstrate how chassis design parameters can affect transient handling performance.

Delivering the appropriate material data for CAE analysis of plastic components is not as straight forward as it would seem to be. While a few of the properties typically used by resin manufacturers and material engineers to describe a plastic are useful to the analysis community (density, CLTE), most are not (flexural modulus, notched izod). In addition some properties such as yield stress are defined differently by the analysis community than by the materials community. Lastly, secondary operations such as painting or chrome plating significantly change the behavior of components with plastic substrates. The materials engineering community and the CAE analysis community must work together closely to develop the material data necessary to increase the capability of the analysis. This paper will examine case studies where these issues have required modifications to the material property data to increase the fidelity of the CAE analysis.

In this paper, a low-cost means to improve fuel economy in conventional vehicles by employing ultracapacitor based Active Energy Recovery Buffer (AERB) scheme will be presented. The kinetic energy of the vehicle during the coast down events is utilized to charge the ultracapacitor either directly or through a dc-dc converter, allowing the voltage to increase up to the maximum permissible level. When the vehicle starts after a Stop event, the energy stored in the capacitor is discharged to power the accessory loads until the capacitor voltage falls below a minimum threshold. The use of stored capacitor energy to power the accessory loads relieves the generator torque load on the engine resulting in reduced fuel consumption. Two different topologies are considered for implementing the AERB system. The first topology, which is a simple add-on to the conventional vehicle electrical system, comprises of the ultracapacitor bank and the dc-dc converter connected across the dc bus.

Due to the multitude of external design constraints, such as increasing fuel economy standards, and the increasing number of global vehicle programs, developers of automotive transmission controls have had to cope with increasing levels of system complexity while at the same time being forced by the marketplace to improve system quality, reduce development costs, and improve time to market. General Motors Powertrain (GMPT) chose to meet these challenges through General Motors Company's Road-to-Lab-to-Math (RLM) strategy, particularly the Math-based method of a virtual vehicle simulation environment called System Simulation. The use of System Simulation to develop transmission control algorithms has enabled GMPT to improve product quality and reduce development times and costs associated with the dependence on physical prototypes. Additionally, System Simulation has facilitated the reuse of GMPT controls development assets, improving overall controls development efficiency.

The Chevrolet Volt is an electric vehicle (EV) that operates exclusively on battery power as long as useful energy is available in the battery pack under normal conditions. After the battery is depleted of available energy, extended-range (ER) driving uses fuel energy in an internal combustion engine (ICE), an on-board generator, and a large electric driving motor. This extended-range electric vehicle (EREV) utilizes electric energy in an automobile more effectively than a plug-in hybrid electric vehicle (PHEV), which characteristically blends electric and engine power together during driving. A specialized EREV powertrain, called the "Voltec," drives the Volt through its entire range of speed and acceleration with battery power alone, within the limit of battery energy, thereby displacing more fuel with electricity, emitting less CO₂, and producing less cold-start emissions than a PHEV operating in real-world conditions.

Aluminum sheet is commercially available in three surface finishes, mill finish (MF), electric discharge texture (EDT), and dull finish (DF). This surface finish impacts the friction behavior during sheet metal forming. A study was done to compare ten commercially available sheet samples from several suppliers. The friction behavior was characterized in the longitudinal and transverse directions using a Draw Bead Simulator (DBS) test, resulting in a coefficient of friction (COF) value for each material. Characterization of the friction behavior in each direction provides useful data for formability analysis. To quantitatively characterize the surface finish, three-dimensional MicroTexture measurements were done with a WYKO NT8000 instrument. In general, the MF samples have the smoothest surface, with Sa values of 0.20-0.30 μm and the lowest COF values. The EDT samples have the roughest surface, with Sa values of 0.60-1.00 μm, and the highest COF values.

As mass reduction becomes an increasingly important enabler for fuel economy improvement, having a robust structural development process that can comprehend Vehicle Dynamics-specific requirements is correspondingly important. There is a correlation between the stiffness of the body structure and the performance of the vehicle when evaluated for ride and handling. However, an unconstrained approach to body stiffening will result in an overly-massive body structure. In this paper, the authors employ loads generated from simulation of quasi-static and dynamic vehicle events in ADAMS, and exercise structural finite element models to recover displacements and deflected shapes. In doing so, a quantitative basis for considering structural vehicle dynamics requirements can be established early in the design/development process.

The environmental issues confronting the automotive industry are legion at a time when the industry has not been in the best position to respond. Concerns have been raised that the industry needs to be producing “green mobility products” without definition, specificity, or expression of customer need. Business infrastructure and the regulatory landscapes are uncertain, but likely to be restrictive for the automotive sector, especially with regard to the environment and green issues. Actions the automotive industry could consider include: develop a common dictionary of terms related to “green mobility products”; address the issues affecting the industry before regulations are imposed; make the Mobility Sector part of the solution; focus on being environmentally responsive, cost-saving, and time-sensitive; and assure that the Mobility Sector is recognized as a leader for new, green technology.

This work is to propose a new Iterative Learning Observer (ILO)-based strategy for State Of Charge (SOC) estimation. The ILO is able to estimate the SOC in real time while identifying modeling errors and/or disturbances at the same time. An Electrical-Circuit Model (ECM) is adopted to characterize the Lithium-ion battery behavior. The ILO is designed based on this ECM and the stability is proved. Several experiments are conducted and the collected data is used to extract ECM parameters. The effectiveness of the estimated SOCs via ILO is verified by the experimental results. This implies that the ILO-based SOC determination scheme is effective to identify the SOC in real time.

This paper presents a method to reduce the number of occurrences of vehicle deceleration disturbances due to the reduction of regenerative braking in the presence of wheel slip. Usually, regenerative braking is disabled when wheel slip is detected in order to allow the ABS system to efficiently cycle brake pressure. When this happens, the vehicle will momentarily lose deceleration due to the reduction in both regenerative brake torque and friction brake pressure, until friction brake pressure is reapplied. Some ABS activations can be defined as nuisance events, in which full ABS control is not necessary and is exited rapidly; for example, a vehicle driving through a pothole. In these cases it is desirable to continue regenerative braking in order to keep vehicle deceleration as smooth as possible.

Industry standards and practices define a number of mathematical and physical methods to estimate the cargo carrying volume capacity of a vehicle. While some have roots dating back decades, others try to assess the utility of the space for cargo by subjective measurements. Each these methods have their own inherent merits and deficiencies. The purpose of this paper is to highlight the differences in calculated cargo volume amongst the following practices: Society of Automobile Engineers (SAE) J1100[1] International Organization for Standardization (ISO 3832)[2], Global Car manufacturer's Information Exchange group (GCIE)[3], Consumer Reports[4]. This paper provides a method and associated rationale for constructing a new cargo volume calculation practice that attempts to harmonize these procedures into a more contiguous practice. This homologation will benefit publishing industry, vehicle manufacturers and customers alike.

The imperative to get to the market faster with new and better products, has determined all automotive OEM to rethink their product development cycle, and, as a result, many hardware based processes were replaced and/or augmented with virtual, software based ones. However, the virtualization itself does not guaranties better and faster products. In the area of vehicle dynamics, we concentrate on improving the multi-body model development process, facilitating comprehensive virtual testing, and verifying the robustness of the design. The authors present a highly flexible and efficient environment that encourages, enforces, and facilitates model sharing, reusing of components, and parallelization of vehicle dynamics simulations, developed on top of an existing commercial off-the-shelf engineering software application.

GM has recently developed two kinds of vehicle electrification architectures. First is VOLTec, a heavy electrification architecture, and second is eAssist, a light electrification architecture. An overview, of IGBT power modules & inverters used in VOLTec and eAssist, is presented. Alternative power modules from few cooperative suppliers are also described in a benchmarking study using key metrics. Inverter test set up, procedure and instrumentation used in GM Power Electronics Development Lab, Milford are described. GM electrification journey depends on Power Electronics lab' passive test benches; double pulse tester, inductive resistive load bench and active emulator test cell without electric machines. Such test benches are preferred before dyne test cells are used for inverter software/hardware integration and motor durability tests cycles. Specific test results are presented.

This paper details the design and operating attributes of a triple input clutch, layshaft automatic transmission (TCT) with a torque converter in a rear wheel drive passenger vehicle. The objectives of the TCT design are to reduce fuel consumption while increasing acceleration performance through the design of the gearing arrangement, shift actuation system and selection of gear ratios and progression. A systematic comparison of an 8-speed TCT design is made against a hypothetical 8-speed planetary automatic transmission (AT) with torque converter using an energy analysis model based upon empirical data and first principles of vehicle-powertrain systems. It was found that the 8-speed TCT design has the potential to provide an approximate 3% reduction in fuel consumption, a 3% decrease in 0-100 kph time and 30% reduction in energy loss relative to a comparable 8-speed planetary AT with an idealized logarithmic ratio progression.

The design of an existing GM exhaust system is analyzed for possible design modifications that may result in lower shipping costs between the supplier facility that manufactures the exhaust system and the assembly plant that installs the system. Investment, changes in piece cost, and other factors are examined in order to determine design changes based upon a rate of return on the investment.

In designing vehicles with significant electric driving range, optimizing vehicle energy efficiency is a key requirement to maximize the limited energy capacity of the onboard electrochemical energy storage system. A critical factor in vehicle energy efficiency is the vehicle mass. Optimizing mass allows for the possibility of either increasing electric driving range with a constant level of electrochemical energy storage or holding the range constant while reducing the level of energy storage, thus reducing storage cost. In this paper, a methodology is outlined to study the tradeoff between the battery cost savings achieved by vehicle mass reduction for a constant electric driving range and the cost associated with lightweighting a vehicle. This methodology enables informed business decisions about the available engineering options for lightweighting early in the vehicle development process. The methodology was applied to a compact extended-range electric vehicle (EREV) concept.

As customer dissatisfaction with interior trim components is tracked by the JDPowers question on “surface durability”, there is a need to increase the durability of the parts that are molded in color. In particular, door trim panel lowers are susceptible to surface damage which results in an unfavorable appearance. To address this issue, an assessment of the various factors that can affect surface durability was conducted using talc filled TPO materials in order to determine the optimum set of physical properties. The team used Design for Six Sigma (DFSS) methodology. A Taguchi orthogonal experiment was used and included control system factors of material, grain, gloss, and color. Noise factors included molding process parameters, aging, and piece to piece variation. The output was a measure of the scratch resistance of the molded plaque which was defined by a Delta L calculation.

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.