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Automotive structural components are exposed to high loads, impact situations and corrosion. In addition, there may be temperature excursions that introduce creep as well as reduced modulus (stiffness). These issues have limited the use of light metals in automotive structural applications primarily to aluminum alloys, and primarily to cast wheels and knuckles (only a few of which are forged), cast brake calipers, and cast control arms. This paper reports on research performed at Chongqing University, Chongqing China, under the auspices of General Motors engineering and directed by the first author, to develop a protocol that uses wrought magnesium in control arms. The goal was to produce a chassis part that could provide the same engineering function as current cast aluminum applications; and since magnesium is 33% less dense than aluminum, would be lighter.

In July 2007, GM announced that it would produce the Chevy Volt, the first high-production volume electric vehicle with extended range capability, by 2010. In January 2009, General Motors announced that the Chevrolet Volt's lithium ion Battery Pack, capable of propelling the Chevy Volt on battery-supplied electric power for up to 40 miles, would be designed and assembled in-house. The T-shaped battery, a subset of the Voltec propulsion system, comprises 288 cells, weighs 190 kg, and is capable of supplying over 16 kWh of energy. Many technical challenges presented themselves to the team, including the liquid thermal management of the battery, the fast battery pack development timeline, and validation of an unproven high-speed assembly process. This paper will first present a general overview of the approach General Motors utilized to bring the various engineering organizations together to design, develop, and manufacture the Volt battery.

There is an increasing demand in automated manufacturability analysis of metal castings at the initial stages of their design. This paper presents a system developed for virtual manufacturability analysis of casting components. The system can be used by a casting designer to evaluate manufacturability of a part designed for various manufacture processes including casting, heat treatment, and machining. The system uses computational geometrics and geometric reasoning to extract manufacturing features and geometry characteristics from a part CAD model. It uses an expert system and a design database consisting of metal casting, heat treatment and machining process knowledge and rules to present manufacturability analysis results and advice to the designer. Application of the system is demonstrated for the manufacturability assessment of automotive cast aluminum components.

Mid 2006 a study group at General Motors developed the concept for the electric vehicle with extended range (EREV),. The electric propulsion system should receive the electrical energy from a rechargeable energy storage system (RESS) and/or an auxiliary power unit (APU) which could either be a hydrogen fuel cell or an internal combustion engine (ICE) driven generator. The study result was the Chevrolet VOLT concept car in the North American Auto Show in Detroit in 2007. The paper describes the requirements, concepts, development and the performance of the battery used as RESS for the ICE type VOLTEC propulsion system version of the Chevrolet Volt. The key requirement for the RESS is to provide energy to drive an electric vehicle with “no compromised performance” for 40 miles. Extended Range Mode allows for this experience to continue beyond 40 miles.

This paper presents Telematics Battery Monitoring (TBM). TBM is a multi-faceted approach of collecting and analyzing electric power and vehicle data used to ultimately determine battery state of charge (SOC) and battery state of health (SOH) in both pre- and post-sale environments. Traditional methods of battery SOC analysis include labor intensive processes such as going out to the site of individual vehicle(s), gaining access to the vehicle battery, and then after the vehicle electrical system obtains its quiescent current level, performing a battery voltage check. This time-consuming manual method can practically only cover a small percentage of the vehicle population. In using the vehicle communication capabilities of Telematics, electric power and vehicle data are downloaded, compiled, and post-processed using decision-making software tools.

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.

Recently, an increased emphasis has been seen for improving the cooling uniformity and efficiency of HEV battery pack in an effort to increase the battery performance and life. This study examined the effects of geometry changes in cooling systems of battery packs on thermal behavior of battery cells and pressure drop across the battery pack. Initially, a multi-physics battery thermal model was correlated to physical test data. An analytical design of experiments (DOE) approach using Latin-hypercube technique was then developed by integrating the correlated battery thermal model with a commercial optimization code, iSIGHT, and a morphing code, DEP Morpher. The design concepts of battery pack cooling systems were finally identified by performing analytical DOE/optimization studies to estimate the effects of cooling flow and geometries of cooling ducts on the battery temperature variation and pressure drop across the battery pack.

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.

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.

The bright surface finish of exterior automotive moldings made from stainless steel can become hazed and reflections distorted as a result of forming done during the manufacturing processes. Bright moldings are frequently used to give styling differentiation accents to vehicle exteriors. Stainless steel provides cost effective differentiation with a material that is durable and relatively easy to form to shapes desired by the stylist. Because of the desirable attributes of stainless steel, an understanding of the threshold of unacceptable surface appearance is necessary to maximize showroom appeal and avoid customer complaints that result in warranty claims. This paper quantifies the effect that manufacturing strain and strain rate have on the surface finish of 436M2 stainless steel. Controlled experiments were conducted on production grade stainless steel strips subjected to a variety of strain and strain rates typical of manufacturing processes.

Temperature effects on the deformation and fracture of a commercially produced transformation-induced plasticity (TRIP) steel subject to a two-step quenching and partitioning (Q&P) heat treatment are investigated. Strain field evolution at room temperature is quantified in this 980 MPa grade Q&P steel with a stereo digital image correlation (DIC) technique from quasi-static tensile tests of specimens with 0°, 45°, and 90° orientations. Baseline tensile properties along with the variation of the instantaneous hardening index with strain were computed. Variations of the bake-hardening index were explored under simulated paint bake conditions. Tensile properties were measured at selected temperatures between -100°C and 200°C and the TRIP effect was found to be temperature-dependent due to stress-induced martensitic transformation at lower temperatures versus strain-induced transformation at higher temperatures.

Experimental decklids for the Cadillac STS sedan were made with Al AA5083 sheet outer panels and Mg AZ31B sheet inner panels using regular-production forming processes and hardware. Joining and coating processes were developed to accommodate the unique properties of Mg. Assembled decklids were evaluated for dimensional accuracy, slam durability, and impact response. The assemblies performed very well in these tests. Explicit and implicit finite element simulations of decklids were conducted, and showed that the Al/Mg decklids have good stiffness and strength characteristics. These results suggest the feasibility of using Mg sheet closure panels from a structural perspective.

Magnesium and aluminum alloys offer lightweighting opportunities in automotive applications. Joining of dissimilar materials, however, generally requires methods that do not involve fusion. This paper explores the use of self-pierce riveting (SPR) to join magnesium to aluminum alloys for structural and closure applications. The preliminary results indicate that SPR is a viable option for joining aluminum extrusions to magnesium die castings, as well as stamped sheet aluminum to quick-plastic-formed (QPF) sheet magnesium.

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.

Great work has been done already in developing robust engineering techniques to improve ideal functions for systems and sub systems. Characterizing an ideal function as a dynamic response type is most preferred way to build quality into a product over a range of input signal values. However, when it is difficult to measure ideal functions, symptomatic outputs such as oil leaks, vibrations, and squeaks, are selected and treated as “Smaller-the-Better” response in non-dynamic response manner. A better approach is to reduce the symptomatic responses over the entire usage range. In order to accomplish this goal, engineers often switch output response and signal axes and apply dynamic response formulation for making the design robust. In this paper, a new and better formulation is proposed and compared with the other formulation. These two formulations were applied on a real automotive case study of decklid bobble and inaccuracies associated with the other formulation were discussed.

This paper presents ‘Virtual Shaker Table’: a CAE method that enables random frequency structural response and random vibration fatigue analyses of a battery system. The Virtual Shaker Table method is a practical and systematic procedure that effectively assesses battery system vibration performance prior to final design, build and testing. A random structural frequency response analysis identifies the critical frequencies and modes at which the battery system is excited by random inputs. Fatigue life may be predicted after PSD stresses have been ascertained. This method enables frequency response analysis techniques to be applied quickly and accurately, thereby allowing assessment of multiple design alternatives. Virtual Shaker Table facilitates an elegant solution to some of the significant challenges inherent to complex battery system design and integration.

The development and validation of an electric vehicle presents numerous issues that are not normally encountered during the development of a traditional internal combustion powered vehicle. Many of the issues that are encountered involve components that are common to both electric and internal combustion vehicles but are utilized in new or unique ways that may present challenges during the development process. The integration of the electric motors, power supply, batteries, and associated content into a traditional vehicle can bring new and challenging issues to light. This paper discusses the solution for an issue that arose during the testing and development of the chassis and powertrain hardware of an electric vehicle. In particular, the large rotational inertia of the electric drive motor presented significant challenges when it was accelerated by forces that were external to the drive unit.

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.