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Ultrasonic fatigue tests (testing frequency around 20 kHz) have been conducted on four different cast aluminum alloys each with a distinct composition, heat treatment, and microstructure. Tests were performed in dry air, laboratory air and submerged in water. For some alloys, the ultrasonic fatigue lives were dramatically affected by the environment humidity. The effects of different factors like material composition, yield strength, secondary dendrite arm spacing and porosity were investigated; it was concluded that the material strength may be the key factor influencing the environmental humidity effect in ultrasonic fatigue testing. Further investigation on the effect of chemical composition, especially copper content, is needed.

To date, model validation metric is prominently designed for non-dynamic model responses. Though metrics for dynamic responses are also available, they are specifically designed for the vehicle impact application and uncertainties are not considered in the metric. This paper proposes the validation metric for general dynamic system responses under uncertainty. The metric makes use of the popular U-pooling approach and extends it for dynamic responses. Furthermore, shape deviation metric was proposed to be included in the validation metric with the capability of considering multiple dynamic test data. One vehicle impact model is presented to demonstrate the proposed validation metric.

The design of structural components requires a knowledge of their crush characteristics, particularly the load-carrying capacity during dynamic crash. Although many attempts have been made to develop analytical techniques or methods for predicting these characteristics, experimental tests are still needed to provide data for real structures for either development or validation. This report describes an experimental method for determining the force-deflection characteristics during dynamic crush of square steel columns using a drop tower test facility. The custom-designed load cells were used for the measurements of the impact and the reaction forces at both ends of specimens, which were subjected to a 30 mph impact. Instrumentation for data acquisition and detailed data reduction for analysis are also presented.

Gas Metal Arc Welding (GMAW) is widely employed for joining relatively thick sheet steels in automotive body-in-white structures and frames. The GMAW process is very flexible for various joint geometries and has relatively high welding speed. However, fatigue failures can occur at welded joints subjected to various types of loads. Thus, vehicle design engineers need to understand the fatigue characteristics of welded joints produced by GMAW. Currently, automotive structures employ various advanced high strength steels (AHSS) such as dual-phase (DP) and transformation-induced plasticity (TRIP) steels to produce lighter vehicle structures with improved safety performance and fuel economy, and reduced harmful emissions. Relatively thick gages of AHSS are commonly joined to conventional high strength steels and/or mild steels using GMAW in current body-in-white structures and frames.

SIF value around weld nugget changes when specimen width is different. To investigate the influence of specimen width on SIF value around weld nugget of coach peel specimen (CP), a finite element model was established in this paper. In this model, a contour integral crack was used, and the area around the nugget was treated as crack tip. Results indicated that when specimen width was below 50mm, SIF decreased rapidly with the increase of specimen width. When specimen width was larger than 50mm, SIF almost remained constant with the variation of specimen width. To further study the influences of nugget diameter and sheet thickness on the Width-SIF curves, CP specimens with different nugget diameters (5mm, 6mm and 7mm) and sheet thicknesses (1.2mm, 1.6mm and 2.0mm) were established in ABAQUS. Simulation results of all CP specimens showed a similar relationship between specimen width and SIF.

Robust processing window and subsequent quality of part are major concerns during sheet metal stamping. The sheet restraining force is a key parameter controlling metal flow, thus influencing formability and quality of the resulting part. Recent advances in press and die building provided capability of altering the restraining force (RF) during a stamping stroke via pulsating blankholder force (PBF). An outcome of this technology would be an increase in the maximum drawing depth resulting from a decrease in the average blankholder force. In this study, laboratory and numerical experiments were performed in an effort to better understand the effect of various PBF trajectories on stamping performance. A working numerical model using explicit code was successfully developed for time effective simulation of drawn cups with pulsating binder force. Preliminary results of this ongoing project are presented. The pulsating force trajectory was found to have a beneficial effect on drawability.

The SS Bumper is a new concept in automobile systems that achieves a very significant weight reduction in steel bumper construction and is capable of meeting the 5 mph FMVSS U.S. Government impact standard. It offers a low cost method of achieving a double digit weight reduction with no cost premium for aluminum or plastic materials. This paper concentrates on describing the configuration of the SS Bumper and a simple, easy to apply procedure for car application which includes discrete equations for bending strengths, torsional strength and the new dent strength relationships which have been recently developed. One version of the SS Bumper applied to the 1983 Thunderbird is also described.

There has been a substantial increase in the use of advanced high strength steel (AHSS) in automotive structures in the last few years. The usage of these materials is projected to grow significantly in the next 5-10 years with the introduction of new safety and fuel economy regulations. AHSS are gaining popularity due to their superior mechanical properties and use in parts for weight savings potential, as compared to mild steels. These new materials pose significant manufacturing challenges, particularly for welding and stamping. Proper understanding of the weldability of these materials is critical for successful application on future vehicle programs. Due to the high strength nature of AHSS materials, higher weld forces and longer weld times are often needed to weld these advanced strength steels.

Computer programs and models are playing an increasing role in simulating vehicle crashworthiness, dynamic, and fuel efficiency. To maximize the effectiveness of these models, the validity and predictive capabilities of these models need to be assessed quantitatively. For a successful implementation of Computer Aided Engineering (CAE) models as an integrated part of the current vehicle development process, it is necessary to develop objective validation metric that has the desirable metric properties to quantify the discrepancy between multiple tests and simulation results. However, most of the outputs of dynamic systems are multiple functional responses, such as time history series. This calls for the development of an objective metric that can evaluate the differences of the multiple time histories as well as the key features under uncertainty.

This study presents the utilization of the hardware-in-the-loop (HIL) approach for regenerative braking (regen) control enhancement efforts for the power split hybrid vehicle architecture. The HIL stand used in this study includes a production brake control module along with the hydraulic brake system, constituted of an accelerator/brake pedal assembly, electric vacuum booster and pump, brake hydraulic circuit and four brake calipers. This work presents the validation of this HIL simulator with real vehicle data, during mild and heavy braking. Then by using the HIL approach, regen control is enhanced, specifically for two cases. The first case is the jerk in deceleration caused by the brake booster delay, during transitions from regen to friction braking. As an example, the case where the regen is ramped out at a low speed threshold, and the hydraulic braking ramped in, can be considered.

This study demonstrates the use of pressure sensing technology to predict the crash severity of frontal impacts. It presents an investigation of the pressure change in the front structural elements (bumper, crush cans, rails) during crash events. A series of subsystem tests were conducted in the laboratory that represent a typical frontal crash development series and provided empirical data to support the analysis of the concept. The pressure signal energy at different sensor mounting locations was studied and design concepts were developed for amplifying the pressure signal. In addition, a pressure signal processing methodology was developed that relies on the analysis of the air flow behavior by normalizing and integrating the pressure changes. The processed signal from the pressure sensor is combined with the restraint control module (RCM) signals to define the crash severity, discriminate between the frontal crash modes and deploy the required restraint devices.

Advanced high strength steels (AHSS) have been widely accepted as a material of choice in the automotive industry to balance overall vehicle weight and stringent vehicle crash test performance targets. Combined with efficient use of geometry and load paths through shape and topology optimization, AHSS has enabled vehicle manufacturers to obtain the highest possible ratings in safety evaluations by the Insurance Institute for Highway Safety (IIHS) and the National Highway Traffic Safety Administration (NHTSA). In this study, vehicle CAE side impact models were used to evaluate three side impact crash test conditions (IIHS side impact, NHTSA LINCAP and FMVSS 214 side pole) and the IIHS roof strength test condition and to identify several key components affecting the side impact test performance. HyperStudy® optimization software and LS-DYNA® nonlinear finite element software were utilized for shape and gauge optimization.

Finite Element (FE) models are widely used in automotive for vehicle design. Even with increasing speed of computers, the simulation of high fidelity FE models is still too time-consuming to perform direct design optimization. As a result, response surface models (RSMs) are commonly used as surrogates of the FE models to reduce the turn-around time. However, RSM may introduce additional sources of uncertainty, such as model bias, and so on. The uncertainty and model bias will affect the trustworthiness of design decisions in design processes. This calls for the development of stochastic model interpolation and extrapolation methods that can address the discrepancy between the RSM and the FE results, and provide prediction intervals of model responses under uncertainty.

Identification of the noise generating mechanisms of gravity action and vibrator stimulated sliding chutes has resulted in the development of practical and effective noise abatement treatments for both. In the case of gravity action chutes the application of foam-backed thin and narrow spring steel plates on the chute surface achieves the desired effect with noise reduction of 14 to 25 dB(A). With vibrator stimulated chutes progressive steps were taken to attenuate source noise, chute radiation noise and the non-productive component of the force vector from the vibrator, resulting in noise reduction of 25 to 30 dB(A).

In-plant trailers constitute a large portion of material handling system in manufacturing plants of the automotive industry. The trailers are among the most intensive noise sources, with radiated noise reaching 110 dBA (Leq). High dynamic loads are also generated on the floor and in the trailer structure. These dynamic loads lead to maintenance problems and inflated inventory of the trailers. Principal mechanisms responsible for generating noise and dynamic loads are identified and treatments to reduce noise and dynamic loads have been developed and investigated on standard trailers. Test results show: for an empty trailer, application of the proposed nonlinear suspension reduces noise 16–18 dBA (Leq) and dynamic load 10 times; for a trailer with an empty rack, application of the proposed nonlinear rack cushion leads to 3–5 dBA (Leq) noise reduction in addition to 8–10 dBA (Leq) reduction due to the suspension.

Multidimensional computations were carried out to simulate the in-cylinder fuel/air mixing process of a direct-injection spark-ignition engine using a modified version of the KIVA-3 code. A hollow cone spray was modeled using a Lagrangian stochastic approach with an empirical initial atomization treatment which is based on experimental data. Improved Spalding-type evaporation and drag models were used to calculate drop vaporization and drop dynamic drag. Spray/wall impingement hydrodynamics was accounted for by using a phenomenological model. Intake flows were computed using a simple approach in which a prescribed velocity profile is specified at the two intake valve openings. This allowed three intake flow patterns, namely, swirl, tumble and non-tumble, to be considered. It was shown that fuel vaporization was completed at the end of compression stroke with early injection timing under the chosen engine operating conditions.

Long fiber reinforced plastics (LFRP) have exhibited superior mechanical performance and outstanding design flexibility, bringing them with increasing popularity in the automotive structural design. Due to the injection molding process, the distribution of long fibers varies at different locations throughout the part, resulting in anisotropic and non-uniform mechanical properties of the final LFRP parts. Images from X-ray CT scan of the materials show that local volume fraction of the long fibers tends to be higher at core than at skin layer. Also fibers are bundled and tangled to form clusters. Most of the current micromechanical material models used for LFRP are extended from those for short fibers without adequate validation. The effect of the complexity of long fibers on the material properties is not appropriately considered. Thus, modeling of these materials is lagging behind the material manufacturing and design development, which in turn limits their further development.

Noise generating mechanisms connected with steel-blanking operation has been identified and their engineering treatments developed and tested. Use of rubber-metal laminates proved to be successful for cushioning impacts in kinematic pairs and joints. Use of plastic for the stripper plate construction was recommended. The “die stiffener” concept was developed to reduce main noise peak associated with punch breakthrough. Screening of the die cavity by a transparent curtain of overlapping PVC strips was shown to be effective. A pulse load simulator with adjustable load rate and amplitude has been developed to facilitate testing of presses.

Accurate determination of the forming limit strain of aluminum sheet metal is an important topic which has not been fully solved by industry. Also, the effects of draw beads (enhanced forming limit behaviors), normally reported on steel sheet metals, on aluminum sheet metal is not fully understood. This paper introduces an experimental study on draw bead effects on aluminum sheet metals by measuring the forming limit strain zero (FLD0) of the sheet metal. Two kinds of aluminum, AL 6016-T4 and AL 5754-0, are used. Virgin material, 40% draw bead material and 60% draw bead material conditions are tested for each kind of aluminum. Marciniak punch tests were performed to create a plane strain condition. A dual camera Digital Image Correlation (DIC) system was used to record and measure the deformation distribution history during the punch test. The on-set necking timing is determined directly from surface shape change. The FLD0 of each test situation is reported in this article.

Hybrid, plug-in hybrid, and electric vehicles have enthusiastically embraced rechargeable Li-ion batteries as their primary/supplemental power source of choice. Because the state of charge (SoC) of a battery indicates available remaining energy, the battery management system of these vehicles must estimate the SoC accurately. To estimate the SoC of Li-ion batteries, we derive a normalized state-space model based on Li-ion electrochemistry and apply a Bayesian algorithm. The Bayesian algorithm is obtained by modifying Potter's squareroot filter and named the Potter SoC tracker (PST) in this paper. We test the PST in challenging test cases including high-rate charge/discharge cycles with outlier cell voltage measurements. The simulation results reveal that the PST can estimate the SoC with accuracy above 95% without experiencing divergence.