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The simulation of a crash event in the design stage of a vehicle facilitates the optimization of crashworthiness and significantly reduces the design cost and time. The development of a fracture material card used in crash simulation is heavily dependent on laboratory testing data. In this paper, the experimental characterization process to generate fracture data for fracture model calibration is discussed. A third-generation advanced high strength steel (AHSS), namely the XG3TM steel, is selected as the example material. For fracture model calibration, fracture locus and load-displacement data are obtained using mechanical testing coupled with digital image correlation (DIC) technique. Test coupons with designed geometries are deformed under different deformation modes including shear, uniaxial tension, plane strain and biaxial stretch conditions. Mini-shear, sub-sized tensile, and Marciniak cup tests are employed to achieve these strain conditions.

For the past decades, the adoption of empirical equations in the forming limit curve (FLC) calculation for conventional steels has greatly simplified the forming severity assessment in both forming simulations and on the stamping shop floor. Keeler’s equation based on the n-value and sheet thickness is the most popular one used in North America. However, challenges have been encountered on the validity of the equation for advanced high strength steels (AHSS) since Keeler’s equation was developed based on the FLC data mostly from mild steels and conventional high strength steels. In this study, forming limits of various AHSS grades under different strain conditions are experimentally determined using digital image correlation technique. Both Marciniak cup and Nakazima dome tests are exercised to demonstrate the differences in the resultant forming limits determined with different test methods.

Three computational gas and fluid dynamic methods, CV/UP (Control Volume/Uniform Pressure), CPM (Corpuscular Particle Method), and ALE (Arbitrary Lagrangian and Eulerian), were investigated in this research in an attempt to predict the responses of side crash pressure sensors. Acceleration-based crash sensors have been used extensively in the automotive industry to determine the restraint system firing time in the event of a vehicle crash. The prediction of acceleration-based crash pulses by using computer simulations has been very challenging due to the high frequency and noisy responses obtained from the sensors, especially those installed in crush zones. As a result, the sensor algorithm developments for acceleration-based sensors are largely based on prototype testing. With the latest advancement in the crash sensor technology, side crash pressure sensors have emerged recently and are gradually replacing acceleration-based sensor for side crash applications.

Digital image correlation (DIC) technique has been proved as a potent tool to determine the forming limit curve (FLC) of sheet metal. One of the major technical challenges using the DIC to generate FLC is to accurately pinpoint the onset of localized necking from the DIC data. In addition to the commonly applied ISO 12004-2 standard, a plethora of other DIC data analysis approaches have been developed and used by various users and researchers. In this study, different approaches, including spatial, temporal and hybrid approaches, have been practiced to determine the limit strains at the onset of localized necking. The formability of a 980GEN3 sheet steel was studied in this work using the Marciniak cup test coupled with a DIC system. The resulting forming limits determined by different approaches were compared. Strengths and limitations of each approach were discussed. In addition, the conventional finger-touch approach was excised using specimens with perceivable localized necks.

Fracture strain data provide essential information for material selection and serve as an important failure criterion in computer simulations of crash events. Traditionally, the fracture strain was measured by evaluating the thinning at fracture using tools such as a microscope or a point micrometer. In the recent decades, digital image correlation (DIC) has evolved as an advanced optical technique to record full-field strain history of materials during deformation. Using this technique, a complete set of the fracture strains (including major, minor, and thickness strains) can be approximated for the material. However, results directly obtained from the DIC can be dependent on the experiment setup and evaluation parameters, which potentially introduce errors to the reported values.

Motivated by a combination of increasing consumer demand for fuel efficient vehicles, more stringent greenhouse gas, and anticipated future Corporate Average Fuel Economy (CAFE) standards, automotive manufacturers are working to innovate in all areas of vehicle design to improve fuel efficiency. In addition to improving aerodynamics, enhancing internal combustion engines and transmission technologies, and developing alternative fuel vehicles, reducing vehicle weight by using lighter materials and/or higher strength materials has been identified as one of the strategies in future vehicle development. Weight reduction in vehicle components, subsystems and systems not only reduces the energy needed to overcome inertia forces but also triggers additional mass reduction elsewhere and enables mass reduction in full vehicle levels.

The objective of this paper focused on the modeling of an adaptive energy absorbing steering column which is the first phase of a study to develop a modeling methodology for an advanced steering wheel and column assembly. Early steering column designs often consisted of a simple long steel rod connecting the steering wheel to the steering gear box. In frontal collisions, a single-piece design steering column would often be displaced toward the driver as a result of front-end crush. Over time, engineers recognized the need to reduce the chance that a steering column would be displaced toward the driver in a frontal crash. As a result, collapsible, detachable, and other energy absorbing steering columns emerged as safer steering column designs. The safety-enhanced construction of the steering columns, whether collapsible, detachable, or other types, absorb rather than transfer frontal impact energy.

This paper presents the final phase of a study to develop the modeling methodology for an advanced steering assembly with a safety-enhanced steering wheel and an adaptive energy absorbing steering column. For passenger cars built before the 1960s, the steering column was designed to control vehicle direction with a simple rigid rod. In severe frontal crashes, this type of design would often be displaced rearward toward the driver due to front-end crush of the vehicle. Consequently, collapsible, detachable, and other energy absorbing steering columns emerged to address this type of kinematics. These safety-enhanced steering columns allow frontal impact energy to be absorbed by collapsing or breaking the steering columns, thus reducing the potential for rearward column movement in severe crashes. Recently, more advanced steering column designs have been developed that can adapt to different crash conditions including crash severity, occupant mass/size, seat position, and seatbelt usage.

With a goal to help develop pressure sensor calibration and deployment algorithms using computer simulations, an Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this research to predict the responses of side crash pressure sensors for unitized vehicles. For occupant protection, acceleration-based crash sensors have been used in the automotive industry to deploy restraint devices when vehicle crashes occur. With improvements in the crash sensor technology, pressure sensors that detect pressure changes in door cavities have been developed recently for vehicle crash safety applications. Instead of using acceleration (or deceleration) in the acceleration-based crash sensors, the pressure sensors utilize pressure change in a door structure to determine the deployment of restraint devices. The crash pulses recorded by the acceleration-based crash sensors usually exhibit high frequency and noisy responses.

In an attempt to assist pressure sensor algorithm and calibration development using computer simulations, an Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this study to predict the responses of side crash pressure sensors for body-on-frame vehicles. Acceleration based, also called G-based, crash sensors have been used extensively to deploy restraint devices, such as airbags, curtain airbags, seatbelt pre-tensioners, and inflatable seatbelts, in vehicle crashes. With advancements in crash sensor technologies, pressure sensors that measure pressure changes in vehicle side doors have been developed recently and their applications in vehicle crash safety are increasing. The pressure sensors are able to detect and record the dynamic pressure change when the volume of a vehicle door changes as a result of a crash.

To improve the energy absorption capacity of front-end structures during a vehicle crash, a novel 12-sided cross-section was developed and tested. Computer-aided engineering (CAE) studies showed superior axial crash performance of the 12-sided component over more conventional cross-sections. When produced from advanced high strength steels (AHSS), the 12-sided cross-section offers opportunities for significant mass-savings for crash energy absorbing components such as front or rear rails and crush tips. In this study, physical crash tests and CAE modeling were conducted on tapered 12-sided samples fabricated from AHSS. The effects of crash trigger holes, different steel grades and bake hardening on crash behavior were examined. Crash sensitivity was also studied by using two different part fabrication methods and two crash test methods. The 12-sided components showed regular folding mode and excellent energy absorption capacity in axial crash tests.

The frame rail has an impact on the crash performance of body-on-frame (BOF) and uni-body vehicles. Recent developments in materials and forming technology have prompted research into improving the energy absorption and deformation mode of the frame rail design. It is worthwhile from a timing and cost standpoint to predict the behavior of the front rail in a crash situation through finite element techniques. This study focuses on improving the correlation of the frame component Finite Element model to physical test data through sensitivity analysis. The first part of the study concentrated on predicting and improving the performance of the front rail in a frontal crash [1]. However, frame rails in an offset crash or side crash undergo a large amount of bending. This paper discusses appropriate modeling and testing procedures for front rails in a bending situation.

The front rail plays an important role in the performance of body-on-frame (BOF) vehicles in frontal crashes. New developments in materials and forming technology have led to the exploration of different configurations to improve crash performance. This paper presents the initial stages of an ongoing study to investigate the effects of the cross section of steel columns on crash performance in automotive applications. Because accurate prediction of the performance of these rails can help reduce the amount of physical crash testing necessary, the focus of this paper is on appropriate testing and modeling procedures for different rail configurations. In the first part of this paper, the Finite Element Analysis (FEA) methodology is presented with respect to correlation with real world tests. The effects of various parameters are described, along with the optimum configuration for model correlation.

Resistance to dents and dings, caused by plant handling and in-service use, is generally recognized as an important performance requirement for automotive outer body panels. This paper examines the dent resistance improvements that can be achieved by maximizing surface stretch, through adjustments to the press settings, and substitution of a higher strength steel grade. Initially, the stamping process was optimized using the steel supplied for production: a Ti/Nb-stabilized, ultra low carbon (ULC) grade. The stamping process was subsequently optimized with a Nb-stabilized, rephosphorized ULC steel, at various thicknesses. The formed panels were evaluated for percent surface stretch, percent thinning, in-panel yield strength after forming, and dent performance. The results showed that dent resistance can be significantly improved, even at a reduced steel thickness, thus demonstrating a potential for weight savings.