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Commercially available Third Generation Advanced High Strength Steels (GEN3 AHSS) are qualified by automakers worldwide. With an excellent combination of strength and ductility, GEN3 AHSS are cold-formable and have shown potential to replace press hardenable steels (PHS) in structural applications. With overall formability equivalent to 590DP, U. S. Steel 980 GEN3 AHSS (980 XG3™ AHSS) may achieve cold-formed component geometries similar to those achieved by hot-formed PHS. Furthermore 980 GEN3 AHSS demonstrates a substantial increase in post-forming yield strength due to the combined effects of work-hardening and bake-hardening-thereby contributing strongly toward crash energy management performance. The technical challenges and attributes of cold-formed 980 GEN3 AHSS are explored in this paper for an automotive rear rail application (currently PHS), including: formability analysis, wrinkling elimination and springback compensation.

A brake is a mechanical device that inhibits the motion by absorbing energy from a moving system. It is used for slowing or stopping a moving vehicle, wheel, axle, or to prevent its motion, most often accomplished by friction energy. Commonly, most brakes use friction between two surfaces pressed together to convert the kinetic energy of the moving object into heat, though other methods of energy conversion may be employed. If braking is repeated or sustained in high load or high-speed conditions, the motion will be unstable and can lead to a loss of stopping power because the disc capability for braking is not enough. These phenomena are generally defined as brake fading. Brake fade is caused by an overheating brake system. This paper describes the thermal modeling and process to predict the disk temperature under a condition which causes the fade characteristics.

Recently, customers' demands for future mobility have increased, such as movement in narrow spaces, increased driving freedom, and ease of parking. The key technology to meet these demands is the four-wheel independent steering system. In this study, we introduce the concept design process for a four-corner steering module and how to prove the design. In addition, we introduce a control method for basic driving modes, such as short U-turn, diagonal driving, crab driving, and zero radius turning. Finally, we propose a special driving mode using the instantaneous rotation center of the 4WS system.

Rising gas prices and increasingly stringent vehicle emissions standards have pushed automakers to increase fuel economy. Mass reduction is the most practical method to increase fuel economy of a vehicle. New materials and CAE technology allow for lightweight automotive components to be designed and manufactured, which outperform traditional component designs. Topology optimization and other design optimization techniques are widely used by designers to create lightweight structural automotive parts. Other design optimization techniques include free-size, gauge, and size optimization. These optimization techniques are typically used in sequence or independently during the design process. Performing various types of design optimization simultaneously is only practical in certain cases, where different parts of the structure have different manufacturing constraints.

The powertrain durability test mode often defines the method by reflecting figures such as frequency of use or severity, but in complex systems, durability is difficult to verify in real life conditions under simple conditions. Therefore, in this session, a new analysis method modeled for each driving unit is presented, rather than analyzing time series data in time to extract representative driving pattern from the perspective of the powertrain load reflecting driving situation and driver’s will by applying machine learning technique, and to develop realistic durability test evaluation mode.

Limited fossil fuel resources, air pollution, and global warming all drive strengthening of fuel economy and vehicle emission standards globally. Much R&D continues to be dedicated to improve fuel efficiency of automobiles and to reduce exhaust gasses. These include improvement of engine/driveline performance for higher efficiency, development of alternative energy, and minimization of air resistance through aerodynamic design optimization. OEM weight reduction-focused research has extended into chassis components (steering knuckle, brakes, control arms, etc.) in sequence from body-in-white(BIW). Wheel bearings, one of the core components of a driveline and part of a vehicle’s unsprung mass, are also being required to reduce weight. Conventionally, wheel bearings have achieved “lightweighting” primarily through design optimization methods. They have been highly optimized today using steel based materials.

As demand for fuel efficiency rises, an increasing number of automotive companies are replacing their existing metal designs with carbon-fiber-reinforced polymer (CFRP) redesigns. Due to the handling and manufacturing processes associated with CFRP materials, engineers have more design freedom to create complex, light-weight designs, which would be infeasible to manufacture using metal. Additionally, it is likely that by redesigning with CFRP, many steel assemblies can be consolidated to significantly fewer parts, simplifying or potentially eliminating the assembly process. When designing an automotive crossmember using CFRP materials, designers often aim for a two-piece design (top and bottom), while utilizing reinforcement material where needed. The joining of these two pieces is typically accomplished with many mechanical fasteners and adhesives, significantly increasing the part count and the manufacturing complexity.

With the electrification trend in the automotive industry, the main contributors to in-vehicle noise profile are represented by drivetrain, road and wind noise. To tackle the problem in an early stage, the industry is developing advanced techniques guaranteeing modularity and independent description of each contributor. Component-based Transfer Path Analysis (C-TPA) allows individual characterization of substructures that can be assembled into a virtual vehicle assembly, allowing the manufacturers to switch between different designs, to handle the increased number of vehicle variants and increasing complexity of products. A major challenge in this methodology is to describe the subsystem in its realistic operational boundary conditions and preload. Moreover, to measure such component, it should be free at the connection interfaces, which logically creates significant difficulties to create the required conditions during the test campaign.

The automotive industry’s journey towards fully autonomous vehicles brings more and more vehicle control systems. Additionally, the reliability and robustness of all these systems must be guaranteed for all road and weather conditions before release into the market. However, the ever-increasing number of such control systems, in combination with the number of road and weather conditions, makes it unfeasible to test all scenarios in real life. Thus, the performance and robustness of these systems needs to be proven virtually, via vehicle simulations. The key challenge for performing such a range of simulations is that the tire performance is significantly affected by the road/weather conditions. An end user must therefore have access to the corresponding tire models. The current solution is to test tires under all road surfaces and operating conditions and then derive a set of model parameters from measurements.

As the automotive industry accelerates its virtual engineering capabilities, there is a growing requirement for increased accuracy across a broad range of vehicle simulations. Regarding control system development, utilizing vehicle simulations to conduct ‘pre-tuning’ activities can significantly reduce time and costs. However, achieving an accurate prediction of, e.g., stopping distance, requires accurate tire modeling. The Magic Formula tire model is often used to effectively model the tire response within vehicle dynamics simulations. However, such models often: i) represent the tire driving on sandpaper; and ii) do not accurately capture the transient response over a wide slip range. In this paper, a novel methodology is developed using the MF-Tyre/MF-Swift tire model to enhance the accuracy of ABS braking simulations.

Fiber-reinforced plastics (FRPs), produced through injection molding, are increasingly preferred over steel in automotive applications due to their lightweight, moldability, and excellent physical properties. However, the expanding use of FRPs presents a critical challenge: deformation stability. The occurrence of warping significantly compromises the initial product quality due to challenges in part mounting and interference with surrounding parts. Consequently, mitigating warpage in FRP-based injection parts is paramount for achieving high-quality parts. In this study, we present a holistic approach to address warpage in injection-molded parts using FRP. We employed a systematic Design of Experiments (DOE) methodology to optimize materials, processes, and equipment, with a focus on reducing warpage, particularly for the exterior part. First, we optimized material using a mixture design in DOE, emphasizing reinforcements favorable for warpage mitigation.

This study deals with the fatigue life prediction methodology of welding simulation components involving arc welding. First, a method for deriving the cyclic deformation and fatigue properties of the weld metal (that is also called ER70S-3 in AWS, American Welding Standard) is explained using solid bar specimens. Then, welded tube specimens were used with two symmetric welds and subjected to axial, torsion, and combined in-phase and out-of-phase axial-torsion loads. In most previous studies the weld bead’s start/stop were arbitrarily removed by overlapping the starting and stop point. Because it can reduce fatigue data scatter. However, in this study make the two symmetric weld’s start/stops exposed to applying load. Because the shape of the weld bead generated after the welding process can act as a notch (Ex. root notch at weld start / Crater at weld stop) to an applied stress. Accordingly, they were intentionally designed to cause stress concentrations on start/stops.

This study delves into the microstructural and mechanical characteristics of AlSi10Mg alloy produced through the Laser Powder Bed Fusion (L-PBF) method. The investigation identified optimal process parameters for AlSi10Mg alloy based on Volume Energy Density (VED). Manufacturing conditions in the L-PBF process involve factors like laser power, scan speed, hatching distance, and layer thickness. Generally, high laser power may lead to spattering, while low laser power can result in lack-of-fusion areas. Similarly, high scan speeds may cause lack-of-fusion, and low scan speeds can induce spattering. Ensuring the quality of specimens and parts necessitates optimizing these process parameters. To address the low elongation properties in the as-built condition, heat treatment was employed. The initial microstructure of AlSi10Mg alloy in its as-built state comprises a cell structure with α-Al cell walls and eutectic Si.

While conventional methods like classical Transfer Path Analysis (TPA), Multiple Coherence Analysis (MCA), Operational Deflection Shape (ODS), and Modal Analysis have been widely used for road noise reduction, component-TPA from Model Based System Engineering (MBSE) is gaining attention for its ability to efficiently develop complex mobility systems. In this research, we propose a method to achieve road noise targets in the early stage of vehicle development using component-level TPA based on the blocked force method. An important point is to ensure convergence of measured test results (e.g. sound pressure at driver ear) and simulation results from component TPA. To conduct component-TPA, it is essential to have an independent tire model consisting of tire blocked force and tire Frequency Response Function (FRF), as well as full vehicle FRF and vehicle hub FRF.