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The increased use of zinc coatings on steels has led to a decrease in their weldability. Weld current and time need to be increased in order to achieve sound welds on these materials compared to uncoated steels, and electrode tip life suffers greatly due to rapid alloying and degradation. In this work, typical uncoated Class II electrodes were tested along with a TiC metal matrix composite (MMC) coated electrode. Tests were conducted to study the weldability and process of nugget formation for both electrodes on HDG (hot dipped galvanized) HSLA (high strength low alloys) steels. Current and time ranges were constructed for both types of electrodes by varying either the weld current or weld time while holding all other parameters constant. Analysis of weld microstructures was conducted on cross-sectioned welds using SEM (scanning electron microscopy). Using the coated electrodes reduced weld current and times needed to form MWS (minimum weld size) on the coated steels.

The present work investigates weld failure modes during formability tests of multi-gauge aluminum Tailor Welded Blanks (TWBs). The limiting dome height test is used to evaluate formability of TWBs. Three gauge combinations utilizing aluminum alloy 5754 sheets are considered (2 to 1 mm, 1.6 to 1 mm and 2 to 1.6 mm). Three weld orientations have been considered: transverse, longitudinal and 45°. Interaction of several factors determines the type of failure that occurs in a TWB specimen. These factors are weld orientation, morphology and distribution of weld defects, and the magnitude of constraint imposed by the thicker sheet to the thin sheet. The last factor depends on the difference in thickness of the sheet pair and is usually expressed in terms of gauge ratio. In general TWBs show two different types of fracture: weld failure and failure of the thin aluminum sheet. Only the former will be discussed in this paper.

Dynamic modelling of the contact between the tires of automobiles and the road surface is crucial for accurate and effective vehicle dynamic simulation and the development of various driving controllers. Furthermore, an accurate prediction of the rolling resistance is needed for powertrain controllers and controllers designed to reduce fuel consumption and engine emissions. Existing models of tires include physics-based analytical models, finite element based models, black box models, and data driven empirical models. The main issue with these approaches is that none of these models offer the balance between accuracy of simulation and computational cost that is required for the model-based development cycle. To address this issue, we present a volumetric approach to model the forces/moments between the tire and the road for vehicle dynamic simulations.

This paper proposes a vehicle performance/safety method using combined active steering and differential braking to achieve yaw stability and rollover avoidance. The advantages and disadvantages of active steering and differential braking control methods are identified under a variety of input signals, such as J-turn, sinusoidal, and fishhook inputs by using the implemented linear 4 DOF model. Also, the nonlinear model of the vehicle is evaluated and verified through individual and integrated controller. Each controller gives the correction steering angle and correction moment to the simplified steering and braking actuators. The integrated active steering and differential braking control are shown to be most efficient in achieving yaw stability and rollover avoidance, while active steering and differential braking control has been shown to improve the vehicle performance and safety only in yaw stability and rollover avoidance, respectively.

The development and calibration of stress state-dependent failure criteria for advanced high-strength steel (AHSS) and aluminum alloys requires characterization under proportional loading conditions. Traditional tests to construct a forming limit diagram (FLD), such as Marciniak or Nakazima tests, are based upon identifying the onset of strain localization or a tensile instability (neck). However, the onset of localization is strongly dependent on the through-thickness strain gradient that can delay or suppress the formation of a tensile instability so that cracking may occur before localization. As a result, the material fracture limit becomes the effective forming limit in deformation modes with severe through-thickness strain gradients, and this is not considered in the traditional FLD. In this study, a novel bending test apparatus was developed based upon the VDA 238-100 specification to characterize fracture in plane strain bending using digital image correlation (DIC).

Electromagnetic forming of aluminum alloys provides improved forming limits, minimal springback and rapid implementation. The ability to predict the minimum energy required in electromagnetic forming is essential in developing an efficient process. Understanding the development of the strain distribution over time in the blank is also highly desired. A numerical model is needed that offers insight into these areas and the electromagnetic forming process in general that cannot easily be extracted from experiments. To address these concerns, ANSYS/EMAG is used to model the time varying currents that are discharged through the coil in order to obtain the transient magnetic forces acting on the blank. The body forces caused by electromagnetic induction are then used as the boundary condition to model the high velocity deformation of the blank with LS-DYNA, an explicit dynamic finite element code.

Robust lane marking detection remains a challenge, particularly in temperate climates where markings degrade rapidly due to winter conditions and snow removal efforts. In previous work, dynamic Bayesian networks with heuristic features were used with the feature distributions trained using semi-supervised expectation maximization, which greatly reduced sensitivity to initialization. This work has been extended in three important respects. First, the tracking formulation used in previous work has been corrected to prevent false positives in situations where only poor RANSAC hypotheses were generated. Second, the null hypothesis is reformulated to guarantee that detected hypotheses satisfy a minimum likelihood. Third, the computational requirements have been greatly reduced by computing an upper bound on the marginal likelihood of all part hypotheses upon generation and rejecting parts with an upper bound less likely than the null hypothesis.

Battery packs of electric vehicles are typically composed of lithium-ion batteries with aluminum and copper acting as cell terminals. These terminals are joined together in series by means of connector tabs to produce sufficient power and energy output. Such critical electrical and structural cell terminal connections involve several challenges when joining thin, highly reflective and dissimilar materials with widely differing thermo-mechanical properties. This may involve potential deformation during the joining process and the formation of brittle intermetallic compounds that reduce conductivity and deteriorate mechanical properties. Among various joining techniques, laser welding has demonstrated significant advantages, including the capability to produce joints with low electrical contact resistance and high mechanical strength, along with high precision required for delicate materials like aluminum and copper.

It is imperative to have accurate tire models when trying to control the trajectory of a vehicle. With the emergence of autonomous vehicles, it is more important than ever before to have models that predict how the vehicle will operate in any situation. Many different types of tire models have been developed and validated, including physics-based models such as brush models, black box models, finite element-based models, and empirical models driven by data such as the Magic Formula model. The latter is widely acknowledged to be one of the most accurate tire models available; however, collecting data for this model is not an easy task. Collecting data is often accomplished through rigorous testing in a dedicated facility. This is a long and expensive procedure which generally destroys many tires before a comprehensive data set is acquired. Using a Vehicle Measurement System (VMS), tires can be modeled through on-road data alone.

Stretch flange features are commonly found in the corner regions of commercial parts, such as window cutouts, where large strains can induce localization and necking. In this study, laboratory-scale stretch flange forming experiments on AA5182 and AA5754 were conducted to address the formability of these aluminum alloys under undergoing this specific deformation process. Two distinct cracking modes were found in the stretch flange samples. One is radial cracking at the inner edge of flange (cutout edge) while the other is circumferential cracking away from the inner edge at the punch profile radius. Numerical simulation of the stretch flange forming operations was conducted with an explicit finite element code-LS-DYNA. A coalescence-suppressed Gurson-based material model is used in the finite element model. Void coalescence and final failure in stretch flange is simulated through measured second-phase particle fields with a so-called damage percolation model.

Vehicle weight reduction through the use of components made of magnesium alloys is an effective way to reduce carbon dioxide emission and improve fuel economy. In the design of these components, which are mostly under cyclic loading, notches are inevitably present. In this study, surface strain distribution and crack initiation sites in the notch region of AZ31B-H24 magnesium alloy notched specimens under uniaxial load are measured via digital image correlation. Predicted strains from finite element analysis using Abaqus and LS-DYNA material types 124 and 233 are then compared against the experimental measurements during quasi-static and cyclic loading. It is concluded that MAT_233, when calibrated using cyclic tensile and compressive stress-strain curves, is capable of predicting strain at the notch root. Finally, employing Smith-Watson-Topper model together with MAT_233 results, fatigue lives of the notched specimens are estimated and compared with experimental results.

A so-called damage percolation model is coupled with Gurson-based finite element (FE) approach in order to accommodate the high strain gradients and localized ductile damage. In doing so, void coalescence and final failure are suppressed in Gurson-based FE modeling while a measured second phase particle field is mapped onto the most damaged mesh area so that percolation modeling can be performed to capture ductile fracture in real sheet forming operations. It is revealed that void nucleation within particle clusters dominates ductile fracture in aluminum alloy sheet forming. Coalescence among several particle clusters triggered final failure of materials. A stretch flange forming is simulated with the coupled modeling.

Motorized shoulder belt tensioning is an occupant protection technology that has promise to reduce automotive crash injuries. The objective of this study was to model the response of a diverse forward-leaning occupant population (6-year-old child, 5th female, 50th male, 95th male) to shoulder belt tensioning during straight line pre-crash braking. The lumped mass model was based on experimental volunteer data for motorized shoulder belt tensioning gathered in a previous quasistatic study. The three dimensional model incorporated the biomechanical properties of the occupant populations, a motorized shoulder belt tensioner (DC motor and controller) and shoulder belt webbing models. Model validation was achieved against the volunteer experiments for angular torso position, torso velocity and shoulder belt moment applied to the torso.

Direct injected natural gas diesel engines are currently being developed. Numerical analyses results are presented for 20.0 MPa (≈ 3000 psia; 200 atm), 444 K, natural gas injection into 4.0 MPa cylinder air where the ambient turbulence field is representative of diesel engines. Two very important non-intuitive, observations are made. First, the seemingly reasonable spatially uniform velocity profile currently used at the injector exit is not appropriate, rather a double-hump profile is correct. Second, a spatially uniform, injector exit, temperature profile results in local temperature overestimates as large as 300 K. Considering the strong role of temperature on chemical kinetics, this second observation may have profound implications on the validity of conclusions reached using uniform exit profiles.

Today, commercially available drones have limited use-cases in the rapidly evolving community. However, with advances in drone and software technology, it is possible to utilize these aerial machines to solve problems in a variety of industries such as mining, medical, construction, and law enforcement. For example, in order to reduce time of investigation, Indiana State Police are currently utilizing ad-hoc commercial drones to reconstruct crash scenes for insurance and legal purposes. In this paper, we illustrate how to effectively integrate drones for in-vehicle services and real-time prediction for automotive applications. In order to accomplish this, we first integrate simpler controls such as voice-commands to control the drone from the vehicle. Next, we build smart prediction software that monitors vehicle behavior and reacts in real-time to collisions.

A compact sized vehicle that has a narrow track could solve problems caused by vehicle congestion and limited parking spaces in a mega city. Having a smaller footprint reduces the vehicle's total weight which would decrease overall vehicle power consumption. Also a smaller and narrower vehicle could travel easily through tight and congested roads that would speed up the traffic flow and hence decrease the overall traffic volume in urban areas. As an additional benefit of having a narrow track length, a driver can experience similar motorcycle riding experience without worrying about bad weather conditions since a driver sits in a weather protected cabin. However, reducing the vehicle's track causes instability in vehicle dynamics, which leads to higher possibility of rollovers if the vehicle is not controlled properly. A three wheel personal vehicle with an active tilting system is designed in MapleSim.

This paper presents the numerical validation of the impact response of a hot formed B-pillar component with tailored properties. A laboratory-scale B-pillar tool is considered with integral heating and cooling sections in an effort to locally control the cooling rate of an austenitized blank, thereby producing a part with tailored microstructures to potentially improve the impact response of these components. An instrumented falling-weight drop tower was used to impact the lab-scale B-pillars in a modified 3-point bend configuration to assess the difference between a component in the fully hardened (martensitic) state and a component with a tailored region (consisting of bainite and ferrite). Numerical models were developed using LS-DYNA to simulate the forming and thermal history of the part to estimate the final thickness and strain distributions as well as the predicted microstructures.

Vehicles designed for the Baja SAE competition operate on challenging off-road terrain and may be required to withstand accidental impacts with other vehicles and obstacles. Although significant injuries are not commonly observed in this competition, it is important to understand the performance of these vehicles in crash scenarios to optimize frame design and vehicle performance. A finite element model comprising the vehicle chassis and associated subsystem weights, a Hybrid III occupant, and safety systems was developed to evaluate vehicle impact performance in frontal crash. Impacts velocities up to 36 kph were considered, and no significant risk of head, neck or thoracic injury was predicted. Neck injury (as predicted by Nij) and chest acceleration were found to be the most critical, reaching 66% and 75% of their threshold values, respectively, in the most severe crashes considered.

This paper presents a model for fatigue life prediction for metals subjected to variable amplitude service loading. The model, which is based on crack growth and crack closure mechanisms for short fatigue cracks, incorporates a strain-based damage parameter, EΔε*, determined from the effective or open part of a strain cycle along with a fatigue resistance curve that takes the form: EΔε* = A(Nf)b, where E is the elastic modulus, Nf is the number of cycles to failure, and A and b are experimentally determined material constants. The fatigue resistance curve is generated for a SAE 1045 steel and the model is used successfully to predict the fatigue lives of smooth axial specimens subjected to two variable amplitude strain histories. The model is also used to predict the magnitude of non-damaging cycles that can be omitted from the strain histories to accelerate fatigue testing.

Electrical steel, also known as silicon steel, is a ferromagnetic material that is often used in electric vehicles (EVs) for stator and rotor applications. Since the design and manufacturing of rotors require the use of laminated thin electrical steel sheets, the fatigue characterization of these single sheets is of interest. In this study, a 0.27mm thick non-oriented electrical steel sheet was tested under cyclic loading in the load-controlled mode with the load ratio R = 0.1 at room temperature. The specimens were prepared using the Computer Numerical Control (CNC) machining method. The Smith-Watson-Topper mean stress correction was used to find the equivalent fully reversed stress-life (S-N) curve. The Basquin equation was used to describe the fatigue strength of the electrical steel and the fatigue parameters were extracted. Furthermore, a design curve with a reliability of 90% and a confidence level of 90% was generated using Owen’s Tolerance Limit method.