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Technical Paper

A Special User Shell Element for Coarse Mesh and High-Fidelity Fatigue Modeling of Spot-Welded Structures

2024-04-09
2024-01-2254
A special spot weld element (SWE) is presented for simplified representation of spot joints in complex structures for structural durability evaluation using the mesh-insensitive structural stress method. The SWE is formulated using rigorous linear four-node Mindlin shell elements with consideration of weld region kinematic constraints and force/moments equilibrium conditions. The SWEs are capable of capturing all major deformation modes around weld region such that rather coarse finite element mesh can be used in durability modeling of complex vehicle structures without losing any accuracy. With the SWEs, all relevant traction structural stress components around a spot weld nugget can be fully captured in a mesh-insensitive manner for evaluation of multiaxial fatigue failure.
Technical Paper

Approaches for Developing and Evaluating Emerging Partial Driving Automation System HMIs

2024-04-09
2024-01-2055
Level 2 (L2) partial driving automation systems are rapidly emerging in the marketplace. L2 systems provide sustained automatic longitudinal and lateral vehicle motion control, reducing the need for drivers to continuously brake, accelerate and steer. Drivers, however, remain critically responsible for safely detecting and responding to objects and events. This paper summarizes variations of L2 systems (hands-on and/or hands-free) and considers human drivers’ roles when using L2 systems and for designing Human-Machine Interfaces (HMIs), including Driver Monitoring Systems (DMSs). In addition, approaches for examining potential unintended consequences of L2 usage and evaluating L2 HMIs, including field safety effect examination, are reviewed. The aim of this paper is to guide L2 system HMI development and L2 system evaluations, especially in the field, to support safe L2 deployment, promote L2 system improvements, and ensure well-informed L2 policy decision-making.
Technical Paper

Estimating How Long In-Vehicle Tasks Take: Static Data for Distraction and Ease-of-Use Evaluations

2024-04-09
2024-01-2505
Often, when assessing the distraction or ease of use of an in-vehicle task (such as entering a destination using the street address method), the first question is “How long does the task take on average?” Engineers routinely resolve this question using computational models. For in-vehicle tasks, “how long” is estimated by summing times for the included task elements (e.g., decide what to do, press a button) from SAE Recommended Practice J2365 or now using new static (while parked) data presented here. Times for the occlusion conditions in J2365 and the NHTSA Distraction Guidelines can be determined using static data and Pettitt’s Method or Purucker’s Method. These first approximations are reasonable and can be determined quickly. The next question usually is “How likely is it that the task will exceed some limit?”
Technical Paper

Investigation of Truck Tire Rubber Material Definitions Using Finite Element Analysis

2024-04-09
2024-01-2648
This paper investigates the tire-road interaction for tires equipped with two different solid rubber material definitions within a Finite Element Analysis virtual environment, ESI PAMCRASH. A Mixed Service Drive truck tire sized 315/80R22.5 is designed with two different solid rubber material definitions: a legacy hyperelastic solid Mooney-Rivlin material definition and an Ogden hyperelastic solid material definition. The popular Mooney-Rivlin is a material definition for solid rubber simulation that is not built with element elimination and is not easily applicable to thermal applications. The Ogden hyperelastic material definition for rubber simulations allows for element destruction. Therefore, it is of interest and more suited for designing a tire model with wear and thermal capabilities.
Technical Paper

Comprehensive Evaluation of Behavioral Competence of an Automated Vehicle Using the Driving Assessment (DA) Methodology

2024-04-09
2024-01-2642
With the development of vehicles equipped with automated driving systems, the need for systematic evaluation of AV performance has grown increasingly imperative. According to ISO 34502, one of the safety test objectives is to learn the minimum performance levels required for diverse scenarios. To address this need, this paper combines two essential methodologies - scenario-based testing procedures and scoring systems - to systematically evaluate the behavioral competence of AVs. In this study, we conduct comprehensive testing across diverse scenarios within a simulator environment following Mcity AV Driver Licensing Test procedure. These scenarios span several common real-world driving situations, including BV Cut-in, BV Lane Departure into VUT Path from Opposite Direction, BV Left Turn Across VUT Path, and BV Right Turn into VUT Path scenarios.
Technical Paper

“Impact of Design Principles on End-of-Life and Recycling”

2024-01-16
2024-26-0163
Automotive industry is a major contributor to global carbon dioxide (CO2) emissions and waste generation. Not only do vehicles produce emissions during usage, but they also generate emissions during production phase and end of life disposal. There is an urgent need to address sustainability and circularity issues in this sector. This paper explores how circularity and CO2 reduction principles can be applied to design and production of automotive parts, with the aim of reducing the environmental impact of these components throughout their life cycle. Also, this paper highlights the impact of design principles on End-of-Life Management of vehicles. As Design decisions of Component impacts up to 80% of emissions [1], it is important to focus on this phase for major contribution in reduction of emissions.
Technical Paper

A Machine Learning Approach for Hydrogen Internal Combustion (H2ICE) Mixture Preparation

2024-01-16
2024-26-0254
The present work discusses the potential benefits of using computational fluid dynamics (CFD) simulation and artificial intelligence (AI) in the design and optimization of hydrogen internal combustion engines (H2ICEs). A Machine Learning (ML) model is developed and applied to the CFD simulation data to identify optimal injection system parameters on the Sandia H2ICE Engine to improve the mixing. This approach can aid in developing predictive ML models to guide the design of future H2ICEs. For the current engine configuration, it is observed that hydrogen (H2) gas injection contributes mixing of H2 with air. If the injector parameters are optimized, mixture preparation is better and eventually combustion. A base CFD model is validated from the Sandia H2ICE engine data against Particle Image Velocimetry (PIV) data for velocity and Planar Laser Induced Fluorescence (PLIF) data for H2 mass fraction.
Technical Paper

Development of Medium Duty H2 ICE for ON & OFF Highway Application

2024-01-16
2024-26-0170
Throughout the world the efforts are being carried out to reduce the GHG emissions from transportation sector. As Volvo Group is a signatory of SBTi and having internal target of carbon neutrality by 2040, we have intensified & also diversified our R&D efforts to develop powertrains of the future having mix of conventional, various alternate fuels, electric etc. There will not be a unique solution or strategy suiting for all the markets in the world. Each market will have its own motivation & factors which OEMs need to consider while deciding the short term, midterm & long-term strategy for powertrain technology. Accordingly, OEMs must be ready with product mix suitable for all global markets. This paper will talk about the efforts taken and lessons learned during development of Hydrogen fuelled IC Engine. We used 8L Diesel IC engine as a base to convert it to Hydrogen powered IC engine, in a retrofit spirit, so that with minimum changes we could make the working prototype.
Research Report

Implications of Off-road Automation for On-road Automated Driving Systems

2023-12-12
EPR2023029
Automated vehicles, in the form we see today, started off-road. Ideas, technologies, and engineers came from agriculture, aerospace, and other off-road domains. While there are cases when only on-road experience will provide the necessary learning to advance automated driving systems, there is much relevant activity in off-road domains that receives less attention. Implications of Off-road Automation for On-road Automated Driving Systems argues that one way to accelerate on-road ADS development is to look at similar experiences off-road. There are plenty of people who see this connection, but there is no formalized system for exchanging knowledge. Click here to access the full SAE EDGETM Research Report portfolio.
Technical Paper

Optical Diagnostic Study on Improving Performance and Emission in Heavy-Duty Diesel Engines Using a Wave-Shaped Piston Bowl Geometry and Post Injection Strategies

2023-08-28
2023-24-0048
This study explores the potential benefits of combining a wave-shaped piston geometry with post injection strategy in diesel engines. The wave piston design features evenly spaced protrusions around the piston bowl, which improve fuel-air mixing and combustion efficiency. The 'waves' direct the flames towards the bowl center, recirculating them and utilizing the momentum in the flame jets for more complete combustion. Post injection strategy, which involves a short injection after the main injection, is commonly used to reduce emissions and improve fuel efficiency. By combining post injections with the wave piston design, additional fuel injection can increase the momentum utilized by the flame jets, potentially further improving combustion efficiency. To understand the effects and potential of the wave piston design with post injection strategy, a single-cylinder heavy-duty compression-ignition optical engine with a quartz piston is used.
Technical Paper

A Comprehensive Study of the Impact of Tread Design on the Tire-Terrain Interaction using Advanced Computational Techniques

2023-04-11
2023-01-0018
This paper investigates the impact of tread design on the tire-terrain interaction of two similar-sized truck tires with distinctly different tread designs running over various terrains and operating conditions using advanced computation techniques. The two truck tires used in the research are off-road tires sized 315/80R22.5 wide which were designed through Finite Element Analysis (FEA). The truck tire models were validated in static and dynamic domains using several simulation tests and measured data. The terrain includes a flooded surface and a snowed surface which were modelled using Smoothed-Particle Hydrodynamics (SPH) technique and calibrated using pressure-sinkage and direct shear tests. Both truck tire models were subjected to rolling resistance and cornering tests over the various flooded surface and snowed surface terrain conditions on the PAM-CRASH software.
Technical Paper

An Optical Study of the Effects of Diesel-like Fuels with Different Densities on a Heavy-duty CI Engine with a Wave-shaped Piston Bowl Geometry

2023-04-11
2023-01-0261
The novel wave-shaped bowl piston geometry design with protrusions has been proved in previous studies to enhance late-cycle mixing and therefore significantly reduce soot emissions and increase engine thermodynamic efficiency. The wave-shaped piston is characterized by the introduction of evenly spaced protrusions around the inner wall of the bowl, with a matching number with the number of injection holes, i.e., flames. The interactions between adjacent flames strongly affect the in-cylinder flow and the wave shape is designed to guide the near-wall flow. The flow re-circulation produces a radial mixing zone (RMZ) that extends towards the center of the piston bowl, where unused air is available for oxidation promotion. The waves enhance the flow re-circulation and thus increase the mixing intensity of the RMZ.
Journal Article

A Standard Set of Courses to Assess the Quality of Driving Off-Road Combat Vehicles

2023-04-11
2023-01-0114
Making manned and remotely-controlled wheeled and tracked vehicles easier to drive, especially off-road, is of great interest to the U.S. Army. If vehicles are easier to drive (especially closed hatch) or if they are driven autonomously, then drivers could perform additional tasks (e.g., operating weapons or communication systems), leading to reduced crew sizes. Further, poorly driven vehicles are more likely to get stuck, roll over, or encounter mines or improvised explosive devices, whereby the vehicle can no longer perform its mission and crew member safety is jeopardized. HMI technology and systems to support human drivers (e.g., autonomous driving systems, in-vehicle monitors or head-mounted displays, various control devices (including game controllers), navigation and route-planning systems) need to be evaluated, which traditionally occurs in mission-specific (and incomparable) evaluations.
Journal Article

Estimates of In-Vehicle Task Element Times for Usability and Distraction Evaluations

2023-04-11
2023-01-0789
Engaging in visual-manual tasks such as selecting a radio station, adjusting the interior temperature, or setting an automation function can be distracting to drivers. Additionally, if setting the automation fails, driver takeover can be delayed. Traditionally, assessing the usability of driver interfaces and determining if they are unacceptably distracting (per the NHTSA driver distraction guidelines and SAE J2364) involves human subject testing, which is expensive and time-consuming. However, most vehicle engineering decisions are based on computational analyses, such as the task time predictions in SAE J2365. Unfortunately, J2365 was developed before touch screens were common in motor vehicles.
Research Report

Automated Vehicles: A Human/Machine Co-learning Perspective

2022-04-27
EPR2022009
Automated vehicles (AVs)—and the automated driving systems (ADSs) that enable them—are increasing in prevalence but remain far from ubiquitous. Progress has occurred in spurts, followed by lulls, while the motor transportation system learns to design, deploy, and regulate AVs. Automated Vehicles: A Human/Machine Co-learning Experience focuses on how engineers, regulators, and road users are all learning about a technology that has the potential to transform society. Those engaged in the design of ADSs and AVs may find it useful to consider that the spurts and lulls and stakeholder tussles are a normal part of technology transformations; however, this report will provide suggestions for effective stakeholder engagement. Click here to access the full SAE EDGETM Research Report portfolio.
Technical Paper

Evaluation of Strain Rate-Sensitive Constitutive Models for Simulation of Servo Stamping: Part 1 Theory

2020-10-01
2020-01-5073
Strain-rate sensitivity has been neglected in the simulation of the traditional stamping process because the strain rate typically does not significantly impact the forming behavior of sheet metals in such a quasi-static process, and traditional crank or link mechanical presses lack the flexibility of slide motion. However, the recent application of servo drive presses in stamping manifests improvement in formability and reduction of springback, besides increased productivity and energy savings. An accurate simulation of servo stamping entails constitutive models with strain-rate sensitivity. This study evaluated a few strain rate-sensitive models including the power-law model, the linear power-law model, the Johnson-Cook model, and the Cowper-Symonds model through the exercise of fitting these models to the experimental data of a deep draw quality (DDQ) steel.
Technical Paper

Accelerometer-Based Estimation of Combustion Features for Engine Feedback Control of Compression-Ignition Direct-Injection Engines

2020-04-14
2020-01-1147
An experimental investigation of non-intrusive combustion sensing was performed using a tri-axial accelerometer mounted to the engine block of a small-bore high-speed 4-cylinder compression-ignition direct-injection (CIDI) engine. This study investigates potential techniques to extract combustion features from accelerometer signals to be used for cycle-to-cycle engine control. Selection of accelerometer location and vibration axis were performed by analyzing vibration signals for three different locations along the block for all three of the accelerometer axes. A magnitude squared coherence (MSC) statistical analysis was used to select the best location and axis. Based on previous work from the literature, the vibration signal filtering was optimized, and the filtered vibration signals were analyzed. It was found that the vibration signals correlate well with the second derivative of pressure during the initial stages of combustion.
Technical Paper

Minimization of Electric Heating of the Traction Induction Machine Rotor

2020-04-14
2020-01-0562
The article solves the problem of reducing electric power losses of the traction induction machine rotor to prevent its overheating in nominal and high-load modes. Electric losses of the rotor power are optimized by the stabilization of the main magnetic flow of the electric machine at a nominal level with the amplitude-frequency control in a wide range of speeds and increased loads. The quasi-independent excitation of the induction machine allows us to increase the rigidity of mechanical characteristics, decrease the rotor slip at nominal loads and overloads and significantly decrease electrical losses in the rotor as compared to other control methods. The article considers the technology of converting the power of individual phases into a single energy flow using a three-phase electric machine equivalent circuit and obtaining an energy model in the form of equations of instantaneous active and reactive power balance.
Technical Paper

Innovative Additive Manufacturing Process for Successful Production of 7000 Series Aluminum Alloy Components Using Smart Optical Monitoring System

2020-04-14
2020-01-1300
Aircraft components are commonly produced with 7000 series aluminum alloys (AA) due to its weight, strength, and fatigue properties. Auto Industry is also choosing more and more aluminum component for weight reduction. Current additive manufacturing (AM) methods fall short of successfully producing 7000 series AA due to the reflective nature of the material along with elements with low vaporization temperature. Moreover, lacking in ideal thermal control, print inherently defective products with such issues as poor surface finish alloying element loss and porosity. All these defects contribute to reduction of mechanical strength. By monitoring plasma with spectroscopic sensors, multiple information such as line intensity, standard deviation, plasma temperature or electron density, and by using different signal processing algorithm, AM defects have been detected and classified.
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