This work puts forward an original autonomous planning and control framework addressing inherent modeling complexity limit through efficient heterosis between latency-connective graph estimation and generative exploration with an aim to enhance trajectory quality and resiliency in unpredicted conditions. The holistic approach encompasses state and cost prediction facilitated via morphable signature mechanism utilizing anti-cloak characteristics derived from environmental graph. In principle, a dynamic graph neural network is proposed with regards to adaptively capture essential influence caused by interactive agents and reciprocal belief augmentation. Moreover, high efficiency exploration is concerted with signature-enhanced prediction system for non-ideal perception conditions. The exploration scheme takes advantage of confidence optimization function to generate trajectory refinement over non-conventional operating circumstances.
Mo free 1.6GPa bolt was developed for The Variable Compression Turbo (VC-Turbo) engine, which is effective for environmental friendliness and improving fuel efficiency and output. Mo contributes not only to the improvement of temper softening resistance, but also the improvement of delayed fracture resistance by precipitating fine carbides during high-temperature tempering and effecting as trap sites for hydrogen, so the main issue is to achieve both high strength and delayed fracture resistance. Therefore, developed steel is added Si to improve tempering softening resistance and achieve a microstructure superior to delayed fracture resistance to achieve both high strength and delayed fracture resistance. The delayed fracture test was done by Hc/He method. Hc means the limit of the diffusible hydrogen contents without causing delayed fracture under tightening, and He means diffusible hydrogen contents entering under the hydrogen charging condition equivalent to actual environment.
Automotive body structures are being increasingly made in multi-material system consisting of steel, aluminum (Al) and fiber-reinforced plastics (FRP). Therefore, many joining tech-niques such as self-piercing riveting (SPR) and adhesive bonding have been developed. On the other hand, OEMs want to minimize the number of joining techniques to reduce the manufacturing complexity. Amount all joining methods, resistance Spot welding (RSW) is the most advanced and cost-effective one for body-in-white. However, RSW cannot be applied for joining dissimilar materials. Therefore, a novel Rivet Resistance Spot Welding method (RRSW) was developed in which Al or FRP Components can be directly welded to steel structures with existing welding systems. RRSW uses rivet-like steel elements as a welding adapter which are formed into Al or FRP components dur-ing their forming process. After that, they are welded to the steel components by RSW. This paper shows at first the results on Steel – Al RRSW.
The microstructure and mechanical properties of the Al-Si-Mg alloy with bulk and lattice structure produced by Laser-powder bed fusion additive manufacturing were systematically investigated. And then, the microstructure behavior of Al-Si-Mg alloys according to As-built and heat treatment was closely analyzed. Firstly, through grain size analysis, the cause of mechanical properties higher than casting materials and similar to forging materials could be analyzed. Secondly, mechanical changes according to the Mg2Si reinforced phase and cell-wall morphology after heat treatment were investigated. The Al-Si-Mg bulk and lattice structures are composed of a cell structure consisting of α-Al and eutectic Si. With heat treatment, needle-shape Mg2Si precipitates in the α-Al matrix. Simultaneously, collapse of the cell-wall morphology occurs.
Vibrations constitute a pivotal factor affecting passenger comfort and overall vehicle performance in both Conventional Internal Combustion Engine (ICE) vehicles and Electric Vehicles (EVs). These vibrations emanate from various sources, including vehicle design and construction, road conditions, and driving patterns, thereby leading to passenger discomfort and fatigue. In the pursuit of mitigating these issues, natural fibers, known for their exceptional damping properties, have emerged as innovative materials for integration into the automotive industry. Notably, these natural fiber-based materials offer a cost-effective alternative to traditional materials for vibration reduction. This research focuses on evaluating natural fibers mainly hemp, banana and cotton fibers for their damping characteristics when applied to a steel plate commonly used in the automotive sector.
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 in diverse automotive components presents a critical challenge: deformation stability. The occurrence of warping significantly compromises the initial product quality due to challenges in component mounting and interference with surrounding parts. Consequently, addressing warping in fiber-reinforced plastic-based injection parts is paramount for achieving high-quality parts. In this study, we present a comprehensive approach to address warpage issues in injection-molded components using FRPs. 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 of a delivery EV.
Lithium-ion batteries (LIBs) serve as the main power source for contemporary electric vehicles (EVs). Safeguarding these batteries against damage is paramount, as it can trigger accelerated performance deterioration, potential fire hazards, environmental threats, and more. This study explores the damage progression of a commercial vehicle LIB module containing prismatic cells under crush loading. We employed computational simulations of mechanical loading tests to investigate this behavior. Physical tests involved subjecting modules to low-speed (0.05 m/s) indentations using a V-shaped stainless-steel wedge, under 6 unique loading conditions. During the tests, the force and voltage change with wedge displacement were monitored. Utilizing experimental insights, we constructed a finite element (FE) model, which included the key components of the battery module, such as the prismatic cells, steel frames and various plastic parts.
Hot-rolled AHSS grades are utilized in automotive parts where high formability is required. However, these grades can fail below their predicted formability limit due to edge cracking. Microstructure and sheared-edge face quality contribute to the initiation of micro-cracks that lead to edge cracking. While it is established that strain incompatibilities between phases and micro-constituents with differing hardness promote edge cracking, microstructural properties governing edge ductility are not fully understood. The edge ductility of eight hot-rolled automotive AHSS grades with tensile strengths of 600 and 800 MPa, achieved with single- or multi-phase microstructures, are being investigated. The experimental and structural single-phase grades include microstructures comprised of ferritic matrices with composite micro-alloyed nano-precipitates and cementite micro-constituents.
Austenitic stainless steel (1.4837Nb) is widely used for turbo housing and other components which are subjected to elevated temperature conditions. Due to assembly constraints, geometry limitation, and particularly high temperatures, thermomechanical fatigue (TMF) issue is commonly seen in the service of the components. Therefore, it is critical to understand the TMF behavior of the steel. In the present study, a series of fatigue tests including isothermal low cycle fatigue (LCF) test at elevated temperatures up to 1000°C, in-phase and out-of-phase TMF tests in different temperature ranges have been conducted. Both creep and oxidation are active in these conditions, and their contributions to the damage of the steel are evaluated. A Chaboche viscoplasticity model for constitutive simulation, and a DTMF damage model for life prediction are developed and validated at specimen level.
The transition towards electrified vehicles marks the release of new products in the automotive market and a continuing effort to optimize their performance. The electric motor is a key component in the electric drive where a further optimization of power loss, power density and cost can be achieved. In the laminated core of the electric motor additional benefits can be realized. This paper presents a new method to produce laminated stacks with a new combination of processes that distinguishes it from conventional methods. The manufacturing sequence includes a unique order of precision blanking, dedicated heat treatment and gluing. The separate and combined effects of these processes are compared with available state-of-the-art solutions. Such solutions typically contain some of the individual features but not the combination that enhances the overall effect. The heat treatment reduces power losses by releasing process stresses which decreases hysteresis losses.
Fracture characterization of automotive metals under simple shear deformation is critical for the calibration of advanced fracture models employed in forming and crash simulations. Great strides in shear fracture characterization have been made over the past decade with several novel geometries proposed. However, in-plane shear tests of high ductility materials have proved challenging since the edge fails first in uniaxial tension before the shear fracture limit is reached in the center of the sample. Although through-thickness machining is undesirable, particularly for extrusions and castings, it appears required to promote higher strains within the shear zone to avoid edge cracking in materials where the shear fracture limit significantly exceeds that of uniaxial tension. The objective of the present study is to adapt existing in-plane shear geometries, which have otherwise been successful for many automotive materials, to have a local shear zone with a reduced thickness.
With the recent development of electric vehicles, the demands of Lithium-ion batteries and advanced battery technologies are growing. Today, Lithium-ion batteries mainly use liquid electrolyte, which contains organic compounds such as dimethyl carbonate and ethylene carbonate as solvents for the Lithium salts. Thermal runaway is a complex process which can involve electrolyte decomposition and subsequent venting of combustible gases that could be readily ignited when mixed with air, leading to pronounced heat release from the combustion of the mixture. The chemical behavior of electrolyte during thermal runaway of Lithium-ion batteries is a critical process and needs to be part of thermal runaway modeling. Well validated, small size chemical kinetic mechanisms of the electrolyte components are required to describe this process in CFD simulations. In this work, sub-mechanisms of dimethyl carbonate and ethylene carbonate were developed and adopted in Ansys Model Fuel Library (MFL).
High cycle fatigue (HCF) S-N curves of steels are often requested by customers for direct evaluation of the products' durability or as an input to their CAE for design purpose. It has been found that the existing models for S-N data resulting HCF test might have difficulties in properly depicting the entire spectrum of fatigue lives. To overcome these difficulties, a new equation has been developed based on the relationship between the behaviors of short and long fatigue lives. The new equation was applied to model S-N data resulting from recent HCF testing of several steels and was compared with the 3 existing popular models. The comparison in the preliminary validations indicated that the new equation has high potential for application in more accurate S-N data modeling and fatigue limit prediction.
At the dawn of battery electric vehicles (BEVs), protection of automotive battery systems as well as passengers, especially from severe side impact, has become one of the latest and most challenging topics in the BEV crashworthiness designs. Accordingly, two material-selection concepts are being justified by the automotive industry: either heavy-gauge extruded aluminum alloys or light-gauge advanced high-strength steels (AHSSs) shall be the optimal materials to fabricate the reinforcement structures to satisfy both the safety and lightweight requirements. In the meantime, such a justification also motivated an ongoing C-STARTM (Cliffs Steel Tube as Reinforcement) Protection project, in which the all-AHSS(s) reinforcement beams, essentially a series of modularized steel tube assemblies, were demonstrated both experimentally and virtually to be more cost-efficient, sustainable, design-flexible, and manufacturable than the equivalent extruded aluminum alloy beams.
During the vehicle lifecycle, customers are able to directly perceive the outer panel stiffness of vehicles in various environmental conditions. The outer panel stiffness is an important factor for customers to perceive the robustness of the vehicle. In the real test of outer panel stiffness after prototype production, evaluators manually press the outer panel in advance to identify vulnerable areas to be tested and evaluate the performance only in those area. However, when developing the outer panel stiffness performance using FEA before releasing the drawing, it is not possible to filter out these areas, so the entire outer panel must be evaluated. This requires a significant amount of computing resources and manpower. In this study, an approach utilizing artificial intelligence was proposed to streamline the outer panel stiffness analysis and improve development reliability.
A multi-material design strategy of steel and aluminium alloy is a key solution in response to stringent emission requirements and to offset the additional weight of batteries in electric vehicles. However, dissimilar Al/steel welding is mainly challenging due to the formation of brittle and hard intermetallic compounds (IMC). To resolve the issue of IMC formation for dissimilar Al/steel, the present study proposed an alternative manufacturing method consisting of friction surfacing deposition and arc welding. The proposed method involves two steps for dissimilar welding: step 1, friction surfacing deposition of aluminium alloy on the steel surface and step 2, arc welding of friction surface deposited steel and aluminium alloy. Auxiliary friction surfacing deposition acts as a preliminary bonding and avoids the direct contact between steel and aluminium alloy during arc welding, which eludes the IMC formation at the interface.
Electrification is the future of the automotive industry and with the rapid growth of EV market, battery protection becomes more and more crucial. Side pole impact is one of the most challenging safety load cases. Rocker assembly, as the first line of defense, plays a significant role during the event. This presentation will discuss Cleveland-Cliffs Steel Tubes as Reinforcement (C-STARTM) protection as an application for rocker reinforcement. For a component level assessment, three-point bending is used as a testing method to replicate pole impact. The performance is compared with aluminum baseline with respect to peak force and energy absorption. A precise, calibrated CAE model is utilized to predict the robustness of various steel designs using different grade, gauge and geometry. It is shown that C-STARTM is a configurable and scalable advanced high-strength steel tube system.
Rotor and stator of electric motors consist of multiple materials, of which, steel forms the majority of mass and volume. In order to reduce the eddy current losses in the motor, the steel is in the form of thin sheets, stacked along the length of the rotor and stator. This stack of steel is often bonded or welded together for structural integrity. Predictive simulations of these laminated stacks can become computationally intense because the steel sheets are thin, and the motor often contains hundreds of them. In this paper, we present an alternate method of modelling this laminated stack as a single body using homogeneous and anisotropic material property. This can provide realistic predictions while keeping the computational time significantly lower than modelling separate steel sheets.
Multiple hybrid bead designs were investigated in this study to control the springback on DP780 samples using post-stretching technique. The performances of the four different hybrid bead designs were evaluated by measuring the minimum blank lock tonnage required to control the springback during U-channel stamping process. A finite element model of the U-channel stamping process using the different hybrid beads was also developed to simulate the process and predict the minimum blank lock tonnage required for spring back control using each of the hybrid bead designs. It is shown that the developed finite element model predicts the required minimum blank lock tonnage for post-stretching and the springback profile with a good accuracy.