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In an Automotive air conditioning system, the air flow distribution in the cabin from the HVAC (Heating, ventilation and air conditioning), ducts and outlets is evaluated by the velocity achieved at driver and passenger mannequin aim points. Multiple simulation iterations are being carried out before finalizing the design of HVAC panel duct and outlets until the target velocity is achieved. In this paper, a parametric modeling of the HVAC outlet is done which includes primary and secondary vane creation using CATIA. Java macro files are created for simulation runs in STAR CCM+. ISIGHT is used as an interface tool between CATIA and STARCCM+. The vane limits of outlet and the target velocity to be achieved at mannequin aim points are defined as the boundary conditions for the analysis. Based on the optimization technique and the number of iterations defined in ISIGHT, the vane angle model gets updated automatically in CATIA followed by the simulation runs in STARCCM+.

This paper describes a comprehensive methodology for the simulation of vehicle body panel buckling in an electrophoretic coat (electro-coat or e-coat) and/or paint oven environment. The simulation couples computational heat transfer analysis and structural analysis. Heat transfer analysis is used to predict temperature distribution throughout a vehicle body in curing ovens. The vehicle body temperature profile from the heat transfer analysis is applied as an input for a structural analysis to predict buckling. This study is focused on the radiant section of the curing ovens. The radiant section of the oven has the largest temperature gradients within the body structure. This methodology couples a fully transient thermal analysis to simulate the structure through the electro-coat and paint curing environments with a structural, buckling analysis.

Automotive vehicle body electrophoretic (e-coat) and paint application has a high degree of complexity and expense in vehicle assembly. These steps involve coating and painting the vehicle body. Each step has multiple coatings and a curing process of the body in an oven. Two types of heating methods, radiation and convection, are used in the ovens to cure coatings and paints during the process. During heating stage in the oven, the vehicle body has large thermal stresses due to thermal expansion. These stresses may cause permanent deformation and weld/joint failure. Body panel deformation and joint failure can be predicted by using structural analysis with component surface temperature distribution. The prediction will avoid late and costly changes to the vehicle design. The temperature profiles on the vehicle components are the key boundary conditions used to perform structure analysis.

Reliable testing of a mechanical system requires the procedures used for the evaluation to be repeatable and reproducible. However, it is never possible to exactly repeat or reproduce the tests that are used for evaluation. To overcome this limitation, a statistical evaluation procedure can generally be used. However, most of the statistical procedures use scalar values as input without the ability to handle vectors or time-histories. To overcome these limitations, two numerical/statistical methods for determining if the impact time-history response of a mechanical system is repeatable or reproducible are evaluated and elaborated upon. Such a system could be a vehicle, a biological human surrogate, an Anthropometric Test Device (ATD or dummy), etc. The responses could be sets of time-histories of accelerations, forces, moments, etc., of a component or of the system. The example system evaluated is the BioRID II rear impact dummy.

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).

This paper reports a 2010 study undertaken to determine generic acceleration pulses for testing and evaluating advanced batteries for application in electric passenger vehicles. These 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. The crash test data were gathered from the following test modes and sources: 1 Frontal rigid flat barrier test at 35 mph (NHTSA NCAP) 2 Frontal 40% offset deformable barrier test at 40 mph (IIHS) 3 Side moving deformable barrier test at 38 mph (NHTSA side NCAP) 4 Side oblique pole test at 20 mph (US FMVSS 214/NHTSA side NCAP) 5 Rear 70% offset moving deformable barrier impact at 50 mph (US FMVSS 301). The accelerometers used were from locations in the vehicle where deformation is minor or non-existent, so that the acceleration represents the “rigid-body” motion of the vehicle.

Nij, a function of upper neck forces and moment, plays a dominant role in the vehicle's star rating under the new NHTSA NCAP front impact program. This is mainly due to an artifact in the mapping of the Nij into the “risk” value used in the star rating, and the fact that the neck region is not weighted appropriately to reflect its real world significance relative to the other body regions in the NCAP rating. New test data also show that compared with the 50th male driver Nij, the 5th female passenger Nij is significantly more challenging to contain and therefore it is more dominant in the star rating. This paper describes the Hybrid III dummy head and neck impact response and provides a method to determine the external force acting on the head. The force and its acting point on the head are determined from head acceleration, angular acceleration, and the upper neck forces.

This paper discusses steps for identifying, evaluating and recommending a quantifiable design metric or metrics for Side Airbag (SAB) development. Three functionally related and desirable attributes of a SAB are assumed at the onset, namely, effective SAB coverage, load distribution and efficient energy management at a controlled force level. The third attribute however contradicts the “banana shaped” force-displacement response that characterizes the ineffective energy management reality of most production SAB. In this study, an estimated ATD to SAB interaction energy is used to size and recommend desired force-deformation characteristic of a robust energy management SAB. The study was conducted in the following three phases and corresponding objectives: Phase 1 is a SAB assessment metric identification and estimation, using a uniform block attached to a horizontal impact machine.

This paper is the second in the series of documents designed to record the progress of a series of SAE documents - SAE J2836™, J2847, J2931, & J2953 - within the Plug-In Electric Vehicle (PEV) Communication Task Force. This follows the initial paper number 2010-01-0837, and continues with the test and modeling of the various PLC types for utility programs described in J2836/1™ & J2847/1. This also extends the communication to an off-board charger, described in J2836/2™ & J2847/2 and includes reverse energy flow described in J2836/3™ and J2847/3. The initial versions of J2836/1™ and J2847/1 were published early 2010. J2847/1 has now been re-opened to include updates from comments from the National Institute of Standards Technology (NIST) Smart Grid Interoperability Panel (SGIP), Smart Grid Architectural Committee (SGAC) and Cyber Security Working Group committee (SCWG).

One method of understanding the general mechanical response of a complex system such as a vehicle, a human surrogate, a bridge, a boat, a plane, etc., is to subject it to an input, such as an impact, and obtain the response time-histories. The responses can be accelerations, velocities, strains, etc. In general, when experiments of this type are run the responses are contaminated by sample-to-sample variation, test-to-test variability, random noise, instrumentation noise, and noise from unknown sources. One common method of addressing the noise in the system to obtain the underlying response is to run multiple tests on different samples that represent the same system and add them together obtaining an average. This functionally reduces the random noise. However, if the fundamental response of each sample is not the same, then it is not altogether clear what the average represents. It may not capture the underlying physics.

This paper is the first in a series of documents designed to record the progress of the SAE J2293 Task Force as it continues to develop and refine the communication requirements between Plug-In Electric Vehicles (PEV) and the Electric Utility Grid. In February, 2008 the SAE Task Force was formed and it started by reviewing the existing SAE J2293 standard, which was originally developed by the Electric Vehicle (EV) Charging Controls Task Force in the 1990s. This legacy standard identified the communication requirements between the Electric Vehicle (EV) and the EV Supply Equipment (EVSE), including off-board charging systems necessary to transfer DC energy to the vehicle. It was apparent at the first Task Force meeting that the communications requirements between the PEV and utility grid being proposed by industry stakeholders were vastly different in the type of communications and messaging documented in the original standard.

Ten sled tests were conducted with a Hybrid III 10-year-old dummy under a 3-point belt only restraint condition to evaluate its performance. The results of the Hybrid III 10-year-old in these tests indicate that there are artifactural noise spikes observable in the transducer responses. A number of metal-to-metal contacts in the shoulder area were identified as one of the sources for the chest acceleration spikes. Noise spikes were also observed in the response from multiple body regions; however, the source of the spikes could not be determined. Compared to the other Hybrid III dummies, non-characteristic dummy chest deflection responses were also observed. This limited analysis indicates that the Hybrid III 10-year-old dummy requires additional development work to eliminate the metal-to-metal contacts in the shoulder area and to understand and correct the other sources of the noise spikes. More investigation is needed to determine if the chest deflection response is appropriate.