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Hood insulators are widely used in automotive industry to improve noise insulation, pedestrian impact protection and to provide aesthetic appeal. They are attached below the hood panel and are often complex in shape and size. Pedestrian head impacts are highly dynamic events with a compressive strain rate experienced by the insulator exceeding 300/s. The energy generated by the impact is partly absorbed by the hood insulators thus reducing the head injury to the pedestrian. During this process, the insulator experiences multi-axial stress states. The insulators are usually made of soft multi-layered materials, such as polyurethane or fiberglass, and have a thin scrim layer on either side. These materials are foamed to their nominal thickness and are compression molded to take the required shape of the hood. During this process they undergo thickness reduction, thereby increasing their density.

Premium instrument panels (IPs) contain passenger airbag (PAB) systems that are typically comprised of a stiff plastic substrate and a soft ‘skin’ material which are adhesively bonded. During airbag deployment, the skin tears along the scored edges of the door holding the PAB system, the door opens, and the airbag inflates to protect the occupant. To accurately simulate the PAB deployment dynamics during a crash event all components of the instrument panel and the PAB system, including the skin, must be included in the model. It has been recognized that the material characterization and modeling of the skin tearing behavior are critical for predicting the timing and inflation kinematics of the airbag. Even so, limited data exists in the literature for skin material properties at hot and cold temperatures and at the strain rates created during the airbag deployment.

Stamped components play an important role in supporting various sub-systems within a typical engine and transmission assembly. In some cases, the stamped components will not initially meet the design criteria, and material may need to be added to strengthen it. However, in other cases the component may be overdesigned, and there will be opportunities to reduce mass while still meeting all design criteria. In this latter case, multiple CAE simulations are often performed to enhance the component design by varying design parameters such as thickness, bend radius, material, etc., The conventional process will assess changes in one parameter at a time, while holding other parameters constant. Though this helps in meeting the design criteria, it is often very difficult to produce the best optimized design within the limited time span with this approach. With the aid of Altair-HyperMorph techniques, multiple design parameters can be varied simultaneously.

The main objective of crash sensing is to predict a vehicle collision early in the event and command vehicle’s occupant protection systems to take appropriate actions to reduce the severity of crash injury. Currently Computer Aided Engineering (CAE) models are being used to predict the sensing signals with sensors placed at front end structure of the vehicle. The front-end structure as well as other critical components packaged in the front end play important role in absorbing energy and provide sensing signals during impact, headlamp being one such critical components. The headlamp with its lens being the exterior surface, experience large magnitude of loads from barrier during full frontal, angled and offset impact. The impact with barrier usually results in scattered damage to the headlamp and its lens. In this paper, CAE model of headlamp has been improved to reflect similar deformation pattern as observed in physical tests.

Finding room to package enough energy at today’s battery energy densities, while preserving performance and configuration requirements is a common problem for electric vehicles. This issue was recently addressed at General Motors by a small team utilizing agile concept development methods, constitutive material model development, and performance simulation tools to create a structural strategy for a family of unique electric light duty trucks. The desire to create a flexible architecture rather than a single vehicle, coupled with an underbody dominant, and rectilinear structural design space precluded any great topological novelty, so a basic principles approach was taken instead. A concept was devised whereby conventional truck frame rails were abandoned in favor of a series of three connected box-like structures along the length of the vehicle. For this to work effectively however, stable shear panels were required as a basic building block.

Third generation advanced high strength steels (3GAHSS) are increasingly used in automotive for light weighting and safety body structure components. However, high material strength usually introduces higher springback that affects the dimensional accuracy. The ability to accurately predict springback in simulations is very important to reduce time and cost in stamping tool and process design. In this work, tension and compression tests were performed and the results were implemented to generate Isotropic/Kinematic hardening (I/KH) material models on a 3GAHSS steel with 980 MPa minimum tensile strength. Systematic material model parametric studies and evaluations have been conducted. Case studies from full-scale industrial parts are provided and the predicted springback results are compared to the measured springback data. Key variables affecting the springback prediction accuracy are identified.

Steel crankshafts are subjected to an induction heat treatment process for improving the operational life. Metallurgical phase transformations during the heat treatment process have direct influence on the hardness and residual stress. To predict the structural performance of a crankshaft using Computer Aided Engineering (CAE) early in the design phase, it is very important to simulate the complete induction heat treatment process. The objective of this study is to establish the overall analysis procedure, starting from capturing the eddy current generation in the crank shaft due to rotating inductor coils to the prediction of resultant hardness and the induced residual stress. In the proposed methodology, a sequentially coupled electromagnetic and thermal model is developed to capture the resultant temperature distribution due to the rotation of the inductor coil.

In the recent decades, tremendous effort has been made in automotive industry to reduce vehicle mass and development costs for the purpose of improving fuel economy and building safer vehicles that previous generations of vehicles cannot match. An accurate modeling approach of sheet metal fracture behavior under plastic deformation is one of the key parameters affecting optimal vehicle development process. FLD (Forming Limit Diagram) approach, which plays an important role in judging forming severity, has been widely used in forming industry, and localized necking is the dominant mechanism leading to fracture in sheet metal forming and crash events. FLD is limited only to deal with the onset of localized necking and could not predict shear fracture. Therefore, it is essential to develop accurate fracture criteria beyond FLD for vehicle development.

The market for electric vehicles and hybrid electric vehicles is expected to grow in the coming years, which is increasing interest in design optimization of electric motors for automotive applications. Under demanding duty cycles, the moving part within a motor, the rotor, may experience varying stresses induced by centrifugal force, a necessary condition for fatigue. Rotors contain hundreds of electrical steel laminations produced by stamping, which creates a characteristic edge structure comprising rollover, shear and tear zones, plus a burr. Fatigue properties are commonly reported with specimens having polished edges. Since surface condition is known to affect fatigue strength, an experiment was conducted to evaluate the effect of sample preparation on tensile and fatigue behavior of stamped specimens. Tensile properties were unaffected by polishing. In contrast, polishing was shown to increase fatigue strength by approximately 10-20% in the range of 105-107 cycles to failure.

The Hybrid Cellular Automaton (HCA) algorithm is a generative design approach used to synthesize conceptual designs of crashworthy vehicle structures with a target mass. Given the target mass, the HCA algorithm generates a structure with a specific acceleration-displacement profile. The extended HCA (xHCA) algorithm is a generalization of the HCA algorithm that allows to tailor the crash response of the vehicle structure. Given a target mass, the xHCA algorithm has the ability to generate structures with different acceleration-displacement profiles and target a desired crash response. In order to accomplish this task, the xHCA algorithm includes two main components: a set of meta-parameters (in addition target mass) and surrogate model technique that finds the optimal meta-parameter values. This work demonstrates the capabilities of the xHCA algorithm tailoring acceleration and intrusion through the use of one meta-parameter (design time) and the use of Kriging-assisted optimization.

Commercially available Generation 3 (GEN3) advanced high strength steels (AHSS) have inherent capability of replacing press hardened steels (PHS) using cold stamping processes. 980 GEN3 AHSS is a cold stampable steel with 980 MPa minimum tensile strength that exhibits an excellent combination of formability and strength. Hot forming of PHS requires elevated temperatures (> 800°C) to enable complex deep sections. 980 GEN3 AHSS presents similar formability as 590 DP material, allowing engineers to design complex geometries similar to PHS material; however, its cold formability provides implied potential process cost savings in automotive applications. The increase in post-forming yield strength of GEN3 AHSS due to work and bake hardening contributes strongly toward crash performance in energy absorption and intrusion resistance.

Adiabatic heating during plastic straining can slow the diffusionless shear transformation of austenite to martensite in steels that exhibit transformation induced plasticity (TRIP). However, the extent to which the transformation is affected over a strain rate range of relevance to automotive stamping and vehicle impact events is unclear for most third-generation advanced high strength TRIP steels. In this study, an 1180MPa minimum tensile strength TRIP steel with carbide-free bainite is evaluated by measuring the variation of retained austenite volume fraction (RAVF) in fractured tensile specimens with position and strain. This requires a combination of servo-hydraulic load frame instrumented with high speed stereo digital image correlation for measurement of strains and ex-situ synchrotron x-ray diffraction for determination of RAVF in fractured tensile specimens.

This article covers an application of third-generation advanced high-strength steel (3GAHSS) grades to vehicle lightweight body structure development. Design optimization of a vehicle body structure using a multi-scale material model is discussed. The steps in the design optimization and results are presented. Results show a 30% mass reduction potential over a baseline mid-size sedan body side structure with the use of 3GAHSS.

To achieve high robustness and quality, automotive ECUs must initialize from low-power states as quickly as possible. However, microprocessor and memory advances have failed to keep pace with software image size growth in complex ECUs such as in Infotainment and Telematics. Loading the boot image from non-volatile storage to RAM and initializing the software can take a very long time to show the first screen and result in sluggish performance for a significant time thereafter which both degrade customer perceived quality. Designers of mobile devices such as portable phones, laptops, and tablets address this problem using Suspend mode whereby the main processor and peripheral devices are powered down during periods of inactivity, but memory contents are preserved by a small “self-refresh” current. When the device is turned back “on”, fully initialized memory content allows the system to initialize nearly instantaneously.

Understanding customer expectations is critical to satisfying customers. Holding customer clinics is one approach to set winning targets for the engineering functional measures to drive customer satisfaction. In these clinics, customers are asked to operate and interact with vehicle systems or subsystems such as doors, lift gates, shifters, and seat adjusters, and then rate their experience. From this customer evaluation data, engineers can create customer loss or preference functions. These functions let engineers set appropriate targets by balancing risks and benefits. Statistical methods such as cumulative customer loss function are regularly applied for such analyses. In this paper, a new approach based on the Taguchi method is proposed and developed. It is referred to as Taguchi Customer Loss Function (TCLF).

Twist spring-back would interfere with stamping or assembling procedures for advanced high strength steel. A “homeopathic” resolution for controlling the twist spring-back is proposed using unbalanced post-stretching configuration. Finite element forming simulation is applied to evaluate and compare the performance for each set of unbalanced post-stretching setup. The post-stretching is effectuated by stake bead application. The beads are separated into multiple independent segments, the height and radii of which can be adjusted individually and asymmetrically. Simulation results indicate that the twist spring-back can be effectively controlled by reducing the post-stretching proximate to the asymmetric part area. Its mechanism is qualitatively revealed by stress analyses, that an additional but acceptable cross-sectional spring-back re-balances the sprung asymmetrical geometry to counter the twist effect.

Understanding process induced fiber orientation distribution of composite body panels using nondestructive techniques is of prime interest. A compression molded sheet molding compound (SMC) panel is a good example of composite panels which are heavily affected by the molding process. Determination of the directionally dependent local coefficient of linear thermal expansion by digital image correlation yields information that is utilized to determine the local fiber misorientation and calculate the local SMC tensile modulus. In our current study, this methodology is utilized to determine the directional CLTE, permitting evaluation of the SMC properties in a multitude of directions not possible in destructive testing techniques. After obtaining the directionally dependent CLTE, a micromechanical approach is utilized to calculate the local SMC tensile modulus and glass fiber misorientation angle.

Automotive liftgate latches have been subject to regulation for minimum strength and inertial resistance requirements since the late 1990’s in the US and globally since the early 2000’s, possibly due to liftgate ejections stemming from the first generation Chrysler minivans which employed latches that were not originally designed with this hazard in mind. Side door latches have been regulated since the 1960’s, and the regulation of liftgate, or back door latches, have been based largely on side door requirements, with the exception of the orthogonal test requirement that is liftgate specific. Based on benchmarking tests of liftgate latches, most global OEM’s design their latches to exceed the minimum regulatory requirements. Presumably, this is based on the need to keep doors closed during crashes and specifically to do so when subjected to industry standard tests.

This paper presents development of a multi-scale material model for a 980 MPa grade transformation induced plasticity (TRIP) steel, subject to a two-step quenching and partitioning heat treatment (QP980), based on integrated computational materials engineering principles (ICME Model). The model combines micro-scale material properties defined by the crystal plasticity theory with the macro-scale mechanical properties, such as flow curves under different loading paths. For an initial microstructure the flow curves of each of the constituent phases (ferrite, austenite, martensite) are computed based on the crystal plasticity theory and the crystal orientation distribution function. Phase properties are then used as an input to a state variable model that computes macro-scale flow curves while accounting for hardening caused by austenite transformation into martensite under different straining paths.

With the increasing use of aluminum shape castings in structural applications in automobiles, assurance of cast product integrity and performance has become critical in both design and manufacturing. In this paper, the latest understanding of the relationship between casting quality and mechanical properties of aluminum castings is summarized. Examples of newly developed technologies for alloy design, melting and melt treatment, casting and heat treatment processes in aluminum casting are reviewed. Robust design and development of high integrity aluminum castings through an Integrated Computational Materials Engineering (ICME) approach is also discussed.