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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.

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.

During sheet metal forming, the friction and surface roughness change as the sheet slides, bends and stretches against the tools. This study assessed evolution of friction and surface roughness changes on aluminum sheet with two surface finish conditions, mill finish (MF) and electron discharge texture (EDT), in both the longitudinal and the transverse rolling directions of the sheet. The sheets were tested using a three pin Draw Bead Simulator (DBS). Surface roughness of the sheet evolved as a result of bending at the first shoulder, reverse bending at the middle pin, bending at the second shoulder and unbending at the exit. Stretching conditions and sheet-pin contact were also varied to see the impact on surface roughness. In general, the largest surface roughness change for the transverse direction was observed at the convex side of the exit shoulder pin and on the convex side of the first shoulder for the longitudinal direction.

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.

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.

An iterative learning control (ILC) algorithm has been developed for a test cell electro-hydraulic, fully flexible valve actuation system to track valve lift profile under steady-state and transient operation. A dynamic model of the plant was obtained from experimental data to design and verify the ILC algorithm. The ILC is implemented in a prototype controller. The learned control input for two different lift profiles can be used for engine transient tests. Simulation and bench test are conducted to verify the effectiveness and robustness of this approach. The simple structure of the ILC in implementation and low cost in computation are other crucial factors to recommend the ILC. It does not totally depend on the system model during the design procedure. Therefore, it has relatively higher robustness to perturbation and modeling errors than other control methods for repetitive tasks.

Corrosion inhibitors (CIs) have been used for years to protect the supply and distribution hardware used for transportation of fuel from refineries and to buffer the potential organic acids present in an ethanol blended fuel to enhance storage stability. The impact of these inhibitors on spark-ignition engine fuel systems, specifically intake valve deposits, is known and presented in open literature. However, the relationship of the corrosion inhibitors to the powertrain intake valve deposit performance is not understood. This paper has two purposes: to present and discuss a second market place survey of corrosion inhibitors and how they vary in concentration in the final blended fuel, specifically E85 (Ethanol Fuel Blends); and, to show how the variation in the concentrations of the components of the CIs impacts the operation and performance of vehicles, specifically, the effects on intake valve deposit formation.

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.

An engineering approach was developed to extract the failure plastic strain, thinning failure strain, and major in plane failure strain for finite element simulation applications. This approach takes into account the failure strain dependency on the element size when element deletion scheme is invoked in the simulation of material fracture. Both localized necking fracture and tensile shear fracture can be predicted when appropriate elements and material models are used in LS-DYNA simulations. This leads to a more accurate prediction of fracture and tearing in the finite element simulation of vehicle structure and crash loading conditions.

This paper outlines a process to assess the aerodynamic performance of different vehicle exterior surfaces. The initial section of the paper summarizes the details of white-light scanning process that maps entire vehicle to points in Cartesian co-ordinate system which is followed by the conversion of scanned points to theme surface. The concept of point-cloud modeling is employed to generate a smooth theme surface from scanned points. Theme surfaces thus developed are stitched to under-body/under-hood (UB/UH) parts of the base vehicle and the numerical simulations were carried out to understand the aerodynamic efficiency of the surfaces generated. Specifics of surface/volume mesh generated, boundary conditions imposed and numerical scheme employed are discussed in detail. Flow field over vehicle exterior is thoroughly analyzed. A comparison study highlighting the effect of front grilles in unblocked condition along with air-dam on flow field has been provided.

For decades, the industry standard for laboratory durability simulations has been based on reproducing quantified vehicle responses. That is, build a running vehicle, measure its responses over a variety of durability road surfaces and reproduce those responses in the laboratory for durability evaluation. To bring a vehicle to market quickly, the time between tightening the last bolt on a prototype test vehicle and starting the durability evaluation test must be minimized. A method to derive 4-Post simulator displacements without measuring or predicting vehicle responses is presented.

Current manufacture of alternative energy sources for automobiles, such as fuel cells and lithium-ion batteries, uses repeating energy modules to achieve targeted balances of power and weight for varying types of vehicles. Specifically for lithium-ion batteries, tens to hundreds of identical plastic parts are assembled in a repeating fashion; this assembly of parts requires complex dimensional planning and high degrees of quality control. This paper will address the aspects of dimensional quality for repeated, injection molded thermoplastic battery components and will include the following: First, dimensional variation associated with thermoplastic components is considered. Sources of variation include the injection molding process, tooling or mold, lot-to-lot material differences, and varying types of environmental exposure. Second, mold tuning and cavity matching between molds for multi-cavity production will be analyzed.

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.

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 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.

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.

Accurate material property data in both the elastic and plastic ranges of deformation is essential for accurate material representation in finite element simulations of vehicle systems. Variation of post formed material properties across a part are often of interest in different types of analyses, such as metal forming or fatigue life, for example. Depending on a part's shape it is not always possible to cut standard size tensile test specimens from all areas of interest across the part. Smaller size specimens with curved or tapered gage section may have to be used to promote strain localization and fracture at or near the gage center. This paper presents comparison of quasi-static tensile properties determined using two specimen gage section geometries, straight and tapered. Specifically, the following questions are addressed. How do the engineering strains computed from two-dimensional strain fields obtained by DIC compare to strains measured during standard tensile tests?

Dynamic modal frequency structural analysis incorporating ADAMS/Flex dynamic load prediction and structural modal stress can provide accurate dynamic stress history for fatigue analysis and synthesis. The amount of data input to finite element analysis is reduced significantly compared to traditional modal & direct transient finite element analysis techniques. Compared to traditional dynamic loads prediction, no additional simulation effort is required except for incorporating flexible body models of structural components into the ADAMS model. This structural analysis technique seamlessly comprehends the correct geometry and force boundary conditions together for long duration dynamic stress calculations. This technique also provided the solution for the deficiency of traditional quasi-static inertia relief method, which is particularly significant for structural system with either significant deformation or articulation.