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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.

Cast austenitic stainless steels, such as 1.4837Nb, are widely used for turbo housing and exhaust manifolds which are subjected to elevated temperatures. Due to assembly constraints, geometry limitation, and particularly high temperatures, thermomechanical fatigue (TMF) issue is commonly seen in the service of those components. Therefore, it is critical to understand the TMF behavior of the cast steels. In the present study, a series of fatigue tests including isothermal low cycle fatigue tests at elevated temperatures up to 1100°C, in-phase and out-of-phase TMF tests in the temperature ranges 100-800°C and 100-1000°C have been conducted. Both creep and oxidation are active in these conditions, and their contributions to the damage of the steel are discussed.

The qualification requirements of automakers derive from track testing in which road load and moment inputs to a part in x, y and z directions are recorded over a set of driving conditions selected to represent typical operation. Because recorded histories are lengthy, often comprising many millions of time steps, past industry practice has been to specify simplified block cycle schedules for purposes of durability testing or analysis. Simplification, however, depends on imprecise human judgement, and risks fidelity of the inferred life and failure mode relative to actual. Fortunately, virtual methods for fatigue life prediction are available that are capable of processing full, real-time, multiaxial road load histories. Two examples of filled natural rubber ride bushings are considered here to demonstrate. Each bushing is subject to a schedule of 11 distinct recorded track events.

As passenger vehicle design evolves and accelerates, the use of multi-body dynamics solvers has proven to be invaluable in the engineering workflow. MBD solvers allow engineers to build virtual vehicle models that can accurately simulate vehicle responses and calculate internal forces, which previously could only be assessed using physical prototype builds with hundreds of measurement transducers. Evaluation and selection of solvers within an engineering environment is inherently a multi-dimensional activity that can include ease of use, retention of previously developed expertise, accuracy, speed, and integration with existing analysis processes. We discuss here some of the challenges present in developing capability and accumulating data to support each of these criteria. Developing a pilot model that is capable of being applied to a comprehensive set of use cases, and then verifying those use cases, required significant project management activity.

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.

Cast aluminum cylinder blocks are frequently used in gasoline and diesel internal combustion engines because of their light-weight advantage. However, the disadvantage of aluminum alloys is their relatively low strength and fatigue resistance which make aluminum blocks prone to fatigue cracking. Engine blocks must withstand a combination of low-cycle fatigue (LCF) thermal loads and high-cycle fatigue (HCF) combustion and dynamic loads. Reliable computational methods are needed that allow for accurate fatigue assessment of cylinder blocks under this combined loading. In several publications, the mechanism-based thermomechanical fatigue (TMF) damage model DTMF describing the growth of short fatigue cracks has been extended to include the effect of both LCF thermal loads and superimposed HCF loadings. This approach is applied to the finite life fatigue assessment of an aluminum cylinder block. The required material properties related to LCF are determined from uniaxial LCF tests.

Semi-Permanent Mold (SPM) cast aluminum alloy cylinder heads are commonly used in gasoline and diesel internal combustion engines. The cast aluminum cylinder heads must withstand severe cyclic mechanical and thermal loads throughout their lifetime. The casting process is inherently prone to introducing casting defects and microstructural heterogeneity. Porosity, which is one of the most dominant volumetric defects in such castings, has a significant detrimental effect on the fatigue life of these components since it acts as a crack initiation site. A reliable analytical model for Thermo-Mechanical Fatigue (TMF) life prediction must take into account the presence of these defects. In previous publications, it has been shown that the mechanism-based TMF damage model (DTMF) is able to predict with good accuracy crack locations and the number of cycles to propagate an initial defect into a critical crack size in aluminum cylinder heads considering ageing effects.

Turbocharger housings in internal combustion engines are subjected to severe mechanical and thermal cyclic loads throughout their life-time or during engine testing. The combination of thermal transients and mechanical load cycling results in a complex evolution of damage, leading to thermo-mechanical fatigue (TMF) of the material. For the computational TMF life assessment of high temperature components, the DTMF model can provide reliable TMF life predictions. The model is based on a short fatigue crack growth law and uses local finite-element (FE) results to predict the number of cycles to failure for a technical crack. In engine applications, it is nowadays often acceptable to have short cracks as long as they do not propagate and cause loss of function of the component. Thus, it is necessary to predict not only potential crack locations and the corresponding number of cycles for a technical crack, but also to determine subsequent crack growth or even a possible crack arrest.

Battery Electric Vehicles (BEVs) are becoming more competitive day by day to achieve maximum peak power and energy requirement. This poses challenges to the design of Thermal Interface Material (TIM) which maintains the cell temperature and ensure retention of cell and prevent electrolyte leak under different crash loads. TIM can be in the form of adhesives, gels, gap fillers. In this paper, TIM is considered as structural, and requires design balance with respect to thermal and mechanical requirements. Improving structural strength of TIM will have negative impact on its thermal conductivity; hence due care needs to be taken to determine optimal strength that meets both structural and thermal performance. During various crash conditions, due to large inertial force of cell and module assembly, TIM is undertaking significant loads on tensile and shear directions. LS-DYNA® is used as simulation solver for performing crash loading conditions and evaluate structural integrity of TIM.

Felt-based dash panel insulation materials have traditionally been used as a sound barrier between the engine and passenger compartments in a vehicle to reduce the transmission of engine noise to the occupant space. Their structural performance has been mainly ignored due to the typically low stiffness and strength characteristics. Consequently, studies of the acoustic properties of these materials have been found in literature while no information was found on their mechanical behavior especially in dynamic loading conditions. More stringent requirements for occupant and pedestrian safety imposed by government regulations and the position of these materials in the impact zones of pedestrian head impact have brought attention to the material contribution to the energy absorption during the impact and the need to assess the mechanical properties of these materials.

Accurate measurements of brake friction materials are critical to understanding brake behaviors during testing. Current methods typically utilize a hand gauge (or a machine, in some cases) to sample various discrete points on the brake lining. This approach limits measurements to planar wear characteristics, taper and thickness, and excludes more complex measurements such as cupping. The limited number of points means that a single errant point measurement or the choice of point locations can have a large impact on the reported wear measurement. This paper will describe a method for utilizing a Coordinate Measurement Machine (CMM) fitted with a laser line scanning tool to generate a point cloud of data that can then be compared to an earlier measurement of the same piece or to a math model. This method produces thousands of data points which allows for more accurate volumetric wear calculations and color maps of the entire friction face.

The automotive industry is continuously striving to reduce vehicle mass by reducing the mass of components including wheel bearings. A typical wheel bearing assembly is mostly steel, including both the wheel and knuckle mounting flanges. Mass optimization of the wheel hub has traditionally been accomplished by reducing the cross-sectional thickness of these components. Recently bearing suppliers have also investigated the use of alternative materials. While bearing component performance is verified through analysis and testing by the supplier, additional effects from system integration and performance over time also need to be comprehended. In a recent new vehicle architecture, the wheel bearing hub flange was reduced to optimize it for low mass. In addition, holes were added for further mass reduction. The design met all the supplier and OEM component level specifications.

Fatigue failure is one of the major failure modes for internal combustion engines, especially with reduction in engine size and increase in combustion pressure and operating temperature. Dynamometer tests are devised to ensure engine durability for high and low cycle fatigue. With the advent of CAE technology, the dynamometer test behavior can be simulated using CAE analysis and engine durability can be assessed. The data generated in CAE analyses can be used to predict failure of the engines or future engine design modifications. The present paper has two parts - first is running finite element analysis (FEA) to get stress, strain data and running high cycle fatigue analysis to get safety factors and second is creating a predictive tool to assess failures using data from the first part as inputs. Using advancements in the field of machine learning, the paper presents use of support vector machine (SVM) algorithm to predict failure of the engine based on inputs.

The objective of this project was to establish a process to perform reliability-based design optimization for improved robustness and understanding of variability inside door slam durability performance. The existing analysis process assesses only the nominal door design. The updated process was automated to include a large-scale DOE which defines the range of durability performance. Then a large-scale Monte Carlo simulation is run to provide a probabilistic distribution of the predicted durability performance. Many variables are included in the DOE based on manufacturing build tolerance, material & weld properties, and material thickness variation due stamping/thinning. 300 finite element model runs are done to complete the DOE and define the fatigue performance domain. From these full FEA model runs, Kriging surfaces are created to quickly provide estimated performance for 4096 Monte Carlo simulation data points.

For the cases where perfect interface is not assumed and crack propagation path is unknown, the fully embedded zero-thickness cohesive element model (FECEM) is an alternative simulation method to model crack growth. In our newly developed FECEM model, the common element is triangle 3-node element under two-dimensional condition and the interface element is a quadrilateral cohesive element with zero thickness. From the simulation by FECEM, it is found that the elastic modulus of the second phase particle in a ductile matrix has a significant effect on crack propagation behavior. When the particle encounters the propagating crack, if it is softer than the matrix, the crack will be attracted towards the particle and then will puncture into it. If the particle is harder than the matrix, it will slow down the propagation of the crack.

Cast Al-Si alloys are widely used in automotive industry to produce structural components, such as engine block and cylinder head, because of the increasing demands in reducing mass for improved fuel efficiency. The fatigue performance of the castings is critical in their application. Porosity is highly detrimental to the fatigue behavior of cast Al-Si alloys. Therefore, accurate measurement of pore sizes is important in order to develop the correlations between porosity and fatigue strength. However, quantification of porosity is challenging and shows large variation depending on the measurement methods, particularly for micro-shrinkage porosity due to the torturous and complex morphology. The conventional metallographic image analysis method in the 2D polished surface often underestimates the actual pore size particularly when the porosity morphology is complex.

Arc brazing welding (ABW) is widely used in automotive vehicle body and chassis structure along with Arc welding - MIG (Metal Inert Gas) or TIG (Tungsten Inert Gas) and spot welds. MIG welding or ABW (Arc Brazing welding) fracture in vehicle development process is one of the critical phenomena in quasi static structural simulation, like Roof Strength, Seat/Belt Anchorage and Child Restraint Anchorage (CRS). MIG/ABW Fracture has an impact on structural performance. Advantages of ABW over MIG weld is made at relatively lower temperatures. Significant advantage is welding thin sheet metal, no melting of parent metal and retains significant physical properties. This characteristic of ABW enables selection of ABW against MIG welded joint on automotive thin sheet metals. Good ABW joint can be as strong or stronger than MIG welded joint. Joint efficiency (JE) is defined as the ratio between the fracture strength of the joint and the fracture strength of parent metal.

Thermoplastics find application in many automotive components. Off late, hardware testing is supplemented by analysis using finite element (FE) codes. One of the factors determining the analysis accuracy is the representation of the components with suitable material models. While a uniaxial tensile test on the specimens typically provides engineering stress-strain data, material plasticity models in commercial FE solvers, such as LS-DYNA and ABAQUS, require equivalent plastic strain versus true stress as input. Engineering stress and strain can be converted to the corresponding true stress and true strain using equations based on the constant volume assumption; however, these equations are valid only up to the point of necking.

Third generation advanced high strength steels (AHSS) that rely on the transformation of austenite to martensite have gained growing interest for implementation into vehicle architectures. Previous studies have identified a dependency of the rate of austenite decomposition on the amount of strain and the associated strain path imposed on the sheet. The rate and amount of austenite transformation can impact the work hardening behavior and tensile properties. However, a deeper understanding of the impact on toughness, and thus crash performance, is not fully developed. In this study, the strain path and strain amounts were systematically controlled to understand the associated correlation to impact toughness in the end application condition (strained and baked). Impact toughness was evaluated using an instrumented Charpy machine with a single sheet v-notch sample configuration.

The past five years have seen significant research into autonomous vehicles that employ a by-wire steering rack actuator and no steering wheel. There is a clear synergy between these advancements and the parallel development of complete Steer-by-Wire systems for human-operated passenger vehicle applications. Steer-by-Wire architectures presented thus far in the literature require multiple layers of electrical and/or mechanical redundancy to achieve the safety goals. Unfortunately, this level of redundancy makes it difficult to simultaneously achieve three key manufacturer imperatives: safety, reliability, and cost. Hindered by these challenges, as of 2020 only one production car platform employs a Steer-by-Wire system. This paper presents a Steer-by-Wire architectural solution featuring fail-operational steering control architected with the objective of achieving all system safety, reliability, and cost goals.