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Important Update – Accessibility Enhancements on SAE Mobilus

We’re pleased to share that SAE Mobilus has recently completed a comprehensive set of accessibility improvements across the platform. As a result, Mobilus is now aligned with WCAG 2.2 Level AA standards in most key categories. These updates are part of our ongoing commitment to ensuring the platform is accessible to all users. Enhancements include improvements to keyboard navigation, screen reader compatibility, visual contrast, error handling, and overall usability across core areas of the site. An updated Voluntary Product Accessibility Template (VPAT v2.5 – March 2026) is now available, providing a detailed overview of our accessibility conformance. You can access the VPAT directly within the Help section. Accessibility is a continuous effort. We will continue to evaluate and improve the platform to better support all users and meet evolving standards. If you have any feedback or experience any accessibility issues, we welcome your input. - The SAE Mobilus Team

SAE AI Chat — Update and What's Next

* Important Update - SAE AI chatbot Beta program * The SAE AI Chatbot Beta program - Phase 1 will end on March 31, 2026. Following this date, the AI chatbot capabilities will be temporarily unavailable as we begin development of a significantly enhanced version. We sincerely thank all Phase 1 Beta participants for their engagement and valuable feedback - your insights have played an important role in shaping the next phase of this experience. The upcoming version of the SAE AI Chatbot will expand content coverage beyond current standards, incorporating additional critical resources from our digital library. It will also be made available to a broader audience across Mobilus. Want to be part of what's next? Register your interest here to receive updates and be considered for early access. For additional information, visit the FAQs. — The Mobilus Team

SAE International Digitization and AI Policy

SAE International prohibits the entry of SAE Content into any form of Artificial Intelligence (AI) tools, such as ChatGPT, OpenAI, or Microsoft Copilot. Additionally, creating derivatives of SAE Content using AI is also prohibited without express written permission from SAE International. In the case of such use, SAE International will suspend access to SAE Content, and further legal action will be considered.

Welcome to the new SAE Mobilus®

Welcome to the new era of SAE Mobilus®, redesigned with a modern, intuitive web interface featuring enhanced search capabilities to help you stay informed and easily discover content. Login today: To access content within your subscription and make the most of the platform, please log into your subscription and your personal My Library (sign up is free) located in the top right corner of the screen. Key Features Intuitive User Interface: We've listened to our customers and tied this to the best practices in the industry to offer an improved, intuitive, and desirable website experience for our users. Improved In-app Discoverability: Enhanced search and expanded menu featuring search suggestions that allow for quick discovery of content. Announcements: Stay up to date on new features through a dedicated announcements page. Most recent announcements also get featured on the homepage. Enhanced Browse capabilities: Browse through over 200,000 publications that are now classified into categories commonly used across the industry. Deep-dive further into any topic or sub-topic of interest to make the most for your corporate projects or research. Smart Automation: "Meta Tags" on each result will help you find content related to your search. My Library: My dashboard is rebranded as My Library with powerful features to help you make the most out of the platform Mobile Friendly: Upgraded navigation on mobile devices Training Available SAE’s Customer Success team is dedicated to delivering the best platform experience possible. Through monthly trainings and short, on-demand video tutorials, find answers to your questions here: SAE Mobilus Spotlight training - Available monthly, hosted live by SAE’s Customer Success team Mobilus Minute – 2-minute videos, available on-demand Need some troubleshooting help? Access our FAQs by visiting our Help section: https://saemobilus.sae.org/help/home Resources to help you navigate the new platform are available here, where you can find links to quick start guides and video tutorials on features like My Library, Announcements, Saved Search, Login and new features. Have feedback that you'd like to share with us? Please submit your feedback to the Mobilus team through the blue Knowledge bot in the bottom right hand corner of the new platform.

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Recent SAE Edge™ Research Reports

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Wing-in-Ground Effect Vehicles: From Modern Military and Commercial Development to Global Disaster Response

EPR202501711/24/2025

The wing-in-ground effect (WIG) vehicle represents a significant advancement in aerodynamics and vehicle design, leveraging the ground effect phenomenon to enhance lift and reduce drag when flying close to the surface. This unique capability allows WIG vehicles to achieve higher payloads, longer range, and greater fuel efficiency compared to traditional aircraft, making them an attractive option for modern military and global disaster response applications. Wing-in-Ground Effect Vehicles: From Modern Military and Commercial Development to Global Disaster Response discusses future disaster response, logistics, and military applications for WIG vehicles, including the ongoing development of aerospace and transportation technology. Relavant advancements in materials and propulsion systems holds promise for further enhancing WIG performance and operational range. Additionally, cost-effective and powerful flight computers with various types of mission-enabling sensor suites from the

Sustainable Circular Future Mobility: Environmental Impact of Next-gen Vehicles

EPR20250159/22/2025

The next generation of mobility, driven by shared, driverless, connected, and electrified vehicles, holds strong potential to advance sustainability through lower emissions and improved resource efficiency. However, critical questions remain regarding their true environmental impact, including battery lifecycle management, material consumption, and circular manufacturing practices. Sustainable Circular Future Mobility: Environmental Impact of Next-gen Vehicles explores these unresolved issues, focusing on the shift from internal combustion to electric vehicles, supply chain challenges, regulatory gaps, and the operational realities of sustainable productization. It also critically examines the risks of greenwashing, the need for consistent standards, and the role of intersectoral collaboration—with energy, urban planning, information and communications technologies, and waste management sectors—in building resilient, scalable solutions. The report provides strategic recommendations and

Next-gen AI for Aerospace Engineering

EPR20250169/22/2025

Despite growing investments, the widespread adoption and scalable deployment of generative artificial intelligence (AI) remains a challenge due to data trustworthiness, regulatory uncertainty, interpretability, and ethical governance. The need to accelerate automation and maintain the human-in-the-loop demonstrates broader questions of responsibility and transparency. Next-gen AI for Aerospace Engineering investigates the transformative role of GenAI within aerospace engineering, examining its shift from conventional workflows toward more AI-driven solutions in design, manufacturing, and maintenance. It emphasizes GenAI’s emerging ability to automate repetitive mundane tasks, reduce design complexity, and optimize engineering pipelines. The report underscores the need for validation methods that must align AI-generated outputs with physics-informed models, integration with legacy engineering tools (e.g., computational fluid dynamics, finite element analysis, digital twins), and

Small, Mobile, and Autonomous Agricultural Robots

EPR20250128/13/2025

The automation of labor-intensive picking and planting operations is having an immediate impact in the agricultural indutry. In its simplest form, robotic automation can reduce the labor and soil disturbance while enabling organic soil cover and increasing species diversification through precision approaches to planting, weeding, and spraying. With this, pesticides and fertilizers can be applied in a more targeted way, and with machinery visiting fields more frequently, earlier and more targeted intervention can occur before pests become established. Small, Mobile, and Autonomous Agricultural Robots identifies issues that need to be resolved fo for this technology to thrive, including improving methods of acquiring and labeling training data to facilitate more accurate models for specific applications. It also discusses concepts such as general-purpose mechanical platforms for use as carriers of agricultural automation systems with high stability, positional accuracy, and variable

Safety Impacts of Active Safety and Driving Automation Features

EPR20250138/13/2025

Advanced technologies that assist the human driver or reduce (or even eliminate) the human driver’s role are becoming increasingly prevalent in new light-duty vehicles used by the general public. These technologies are divided between Active Safety features that monitor the human driver and vehicle motion and act intermittently to mitigate and avoid crashes, and Driving Automation features that assume some or all of the dynamic driving task from the human driver. Both types of technologies have the potential to reduce injuries and save lives by reducing the frequency and/or severity of crashes. Safety Impacts of Active Safety and Driving Automation Features addresses the current capabilities and future potential for Active Safety and Driving Automation features to reduce crash frequency and severity and provides an overview of the state of the industry for both types of features, including current deployments, trends, and anticipated rollouts. Gaps in knowledge, unsettled issues, and

Hybrid Data- and Physical Model-driven Safe and Intelligent Motion Planning and Control for Autonomous Vehicles

EPR20250147/18/2025

Autonomous vehicle motion planning and control are vital components of next-generation intelligent transportation systems. Recent advances in both data- and physical model-driven methods have improved driving performance, yet current technologies still fall short of achieving human-level driving in complex, dynamic traffic scenarios. Key challenges include developing safe, efficient, and human-like motion planning strategies that can adapt to unpredictable environments. Data-driven approaches leverage deep neural networks to learn from extensive datasets, offering promising avenues for intelligent decision-making. However, these methods face issues such as covariate shift in imitation learning and difficulties in designing robust reward functions. In contrast, conventional physical model-driven techniques use rigorous mathematical formulations to generate optimal trajectories and handle dynamic constraints. Hybrid Data- and Physical Model-Driven Safe and Intelligent Motion Planning and

Product Assurance in the Age of Artificial Intelligence

EPR20250115/21/2025

Driven by the vast consumer marketplace, the electronics megatrend has reshaped nearly every sector of society. The advancements in semiconductors and software, originally built to serve consumer demand, are now delivering significant value to non-consumer industries. Today, electronics are making inroads into traditionally conservative, safety-critical sectors such as automotive and aerospace. In doing so, electronics—now further propelled by artificial intelligence—are disrupting the functional safety architectures of these cyber-physical systems. Electronics have created the world of cyber-physical systems, raising broader concerns about the broader category of product assurance. Product Assurance in the Age of Artificial Intelligence continues the work of previous SAE Edge Research Reports in examining open research challenges arising from this shift, particularly in automotive systems, as core electronic technologies (e.g., the combination of software and communications) have even

Leveraging Advanced Data Technologies for Smart Traffic Management

EPR20250085/20/2025

The transportation industry is transforming with the integration of advanced data technologies, edge devices, and artificial intelligence (AI). Intelligent transportation systems (ITS) are pivotal in optimizing traffic flow and safety. Central to this are transportation management centers, which manage transportation systems, traffic flow, and incident responses. Leveraging Advanced Data Technologies for Smart Traffic Management explores emerging trends in transportation data, focusing on data collection, aggregation, and sharing. Effective data management, AI application, and secure data sharing are crucial for optimizing operations. Integrating edge devices with existing systems presents challenges impacting security, cost, and efficiency. Ultimately, AI in transportation offers significant opportunities to predict and manage traffic conditions. AI-driven tools analyze historical data and current conditions to forecast future events. The importance of multidisciplinary approaches and

Edge Artificial Intelligence in Connected, Cooperative and Automated Mobility

EPR20250095/20/2025

With many stakeholders involved, and major investments supporting it, the advancements in automated driving (AD) are undoubtedly there. Generally speaking, the motivation for advancing AD is driver convenience and road safety. Regarding the development of AD, original equipment manufacturers, technology start-ups, and AD systems developers have taken different approaches for automated vehicles (AVs). Some manufacturers are on the path toward stand-alone vehicles, mostly relying on onboard sensors and intelligence. On the other hand, the connected, cooperative, and automated mobility (CCAM) approach relies on additional communication and information exchange to ensure safe and secure operation. CCAM holds great potential to improve traffic management, road safety, equity, and convenience. In both approaches, there are increasingly large amounts of data generated and used for AD functions in perception, situational awareness, path prediction, and decision-making. The use of artificial

Automated Vehicles and Infrastructure Enablers: Dedicated Lanes

EPR20250074/24/2025

Dedicated lanes provide a simpler operating environment for ADS-equipped vehicles than those shared with other roadway users including human drivers, pedestrians, and bicycles. This final report in the Automation and Infrastructure series discusses how and when various types of lanes whether general purpose, managed, or specialty lanes might be temporarily or permanently reserved for ADS-equipped vehicles. Though simulations and economic analysis suggest that widespread use of dedicated lanes will not be warranted until market penetration is much higher, some US states and cities are developing such dedicated lanes now for limited use cases and other countries are planning more extensive deployment of dedicated lanes. Automated Vehicles and Infrastructure: Dedicated Lanes includes a review of practices across the US as well as case studies from the EU and UK, the Near East, Japan, Singapore, and Canada. Click here to access the full SAE EDGETM Research Report portfolio.

Latest Journal Issues

Browse All 16

Passenger Vehicle Systems

Electrified Vehicles

Advances and Current Practices in Mobility

Sustainable Transportation, Energy, Environment, & Policy

Connected and Automated Vehicles

Transportation Cybersecurity and Privacy

Vehicle Dynamics, Stability, and NVH

Transportation Safety

Alternative Powertrains

Commercial Vehicles

Engines

Materials and Manufacturing

Fuels and Lubricants

Aerospace

Passenger Cars - Mechanical Systems

Recent Books

Browse All 720

Aerospace Standards Index - 2026

ASIN20262/25/2026

This valuable resource lists all Aerospace Standards (AS), Aerospace Recommended Practices (ARP), Aerospace Information Reports (AIR), and Aerospace Resource Documents (ARD) published by SAE. Each listing includes title, subject, document number, key words, new and revised documents, and DODISS-adopted documents. AMS Index - Now Available!

Business Reliability Growth for Automotive Engineering, Volume 4

R-5522/17/2026

In a world where every business process is under pressure to perform faster, safer, and more reliably, this book delivers a powerful roadmap for sustained operational excellence. Centered on the proven methodology of Design of Experiments (DOE), it shows how organizations can move beyond reactive problem-solving to systematic reliability growth. From well-defined standard operating practices to management-level decision-making, the book connects strategy, data, and execution to create repeatable, measurable results across the enterprise. Readers are guided through practical, real-world applications of DOE, from selecting the right factors and levels to executing robust experiments, analyzing outcomes, validating solutions, and continuously monitoring performance. Each chapter translates complex statistical and engineering concepts into actionable business value, helping teams improve quality, reduce waste, and increase return on investment. Key capabilities explored in this book

January 2026 AMS Index

AMSJAN-20261/24/2026

Fundamentals of Sustainable Aviation Fuels

R-5471/22/2026

As global energy demands rise and environmental challenges intensify, the aviation industry faces a critical need to redefine how it powers the skies. Fundamentals of Sustainable Aviation Fuels presents a comprehensive, research-driven exploration of the transition from fossil-based fuels to renewable alternatives that promise to reshape the future of air transportation. This book bridges the gap between academic knowledge and industrial application, offering a detailed overview of the science, technology, and policy driving the adoption of Sustainable Aviation Fuels (SAFs). From understanding feedstocks and conversion pathways to evaluating production technologies, emissions performance, and life-cycle impacts, the text equips readers with a holistic understanding of SAFs within today’s global energy landscape. Across five insightful chapters, readers will find a clear roadmap: the evolution and importance of SAFs; production methods and technological foundations; environmental

SAE International’s Dictionary of ADAS and Connected Vehicles

R-5591/20/2026

The convergence of Advanced Driver Assistance Systems (ADAS) and connected vehicle technologies is ushering in a transformative era of automotive innovation—one that is fundamentally enhancing vehicle safety, efficiency, reliability, and the overall driving experience. SAE International’s Dictionary of ADAS and Connected Vehicles stands as the definitive reference for this rapidly evolving domain, meticulously compiled to clarify and standardize the language shaping modern mobility. Inside, readers will find clear, authoritative definitions encompassing the full spectrum of technologies that enable connected and automated driving—including vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-everything (V2X) communication systems. This comprehensive resource translates complex engineering terminology into accessible language, enabling engineers, researchers, policymakers, educators, and enthusiasts to share a common technical foundation. Reflecting the latest

Electrification: Vol. 3

EPRCOMPV04202512/29/2025

Safety, ADAS, and Cybersecurity: Vol. 4

EPRCOMPV01202512/29/2025

Infrastructure Enablers for Automation: Vol. 4

EPRCOMPV02202512/29/2025

Automated Vehicles: Development, Testing, and Validation: Vol. 4

EPRCOMPV03202512/29/2025

Commercial Vehicles: Vol. 2

EPRCOMPV05202512/29/2025

Recently Published

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STUD, LOCKED-IN RING, SERRATED, HIGH STRENGTH

AS51992D (Historical)

4/8/2026

E-25 General Standards for Aerospace and Propulsion Systems

Integration and Certification Considerations for Electrified Propulsion Aircraft

AIR7128 (Current)

4/8/2026

This document provides a comprehensive compilation of currently available practices, standards, regulations, and guidance material that have been considered relevant for developing an electrified propulsion system (independently or as part of an aircraft) and that may also help the applicants in the process of building their own certification approach with their Authority. It also covers unique considerations for electrified propulsion development and aircraft integration. It focuses on the particularities introduced by the new technology. This document is not intended to represent a proposed Means of Compliance (MoC) with any particular certification regulation.

E-40 Electrified Propulsion Committee

Copper Alloy (Brass), Sheet, Strip, and Plate, 70Cu - 30Zn, Half Hard (H02)

AMS4507K (Current)

4/8/2026

This specification covers a copper-zinc alloy (brass) in the form of sheet, strip, and plate (see 8.6).

AMS D Nonferrous Alloys Committee

Test Method for Measuring Wet Color Transfer Characteristics

J1326_202604 (Current)

4/8/2026

This procedure describes a method of measuring the resistance to wet color transfer of materials such as textiles, leather, and composites.

Textile and Flexible Plastics Committee

Sampling, Conformance Strategies, and Recommended Practices for Closed Loop Processing of Powder for Additive Manufacturing

ARP7302 (Historical)

4/8/2026

This SAE Aerospace Recommended Practice (ARP) establishes methods and identifies opportunities to sample used powder feedstock circulating within closed loop equipment of an additive manufacturing (AM) process for the purpose of showing conformance to a powder specification. Powder within the entirety of closed loop equipment cannot be represented by sampling and testing of discrete, in-process lots. Because powder processing (i.e., reconditioning, conveyance, and storage) is asynchronous with a build cycle, individual samples and their associated tests do not represent the totality of powder committed to a machine. Powder consumed as part of an individual build cycle may only represent a subset of feedstock in circulation within such equipment. Therefore, regular testing to substantiate conformance to a powder specification is required to assert conforming feedstock was consumed during individual build cycles of the AM workflow to fabricate parts or preforms. Operation of some

AMS AM Additive Manufacturing Metals

Steel, Sheet, Strip, and Plate, 0.75Si - 0.62Cr - 0.20Mo - 0.10Zr (0.10 - 0.17C) (NAX 9115-AC)

AMS6354H (Current)

4/8/2026

This specification covers a low-alloy steel in the form of sheet, strip, and plate 4.00 inches (101.6 mm) and under in thickness.

AMS E Carbon and Low Alloy Steels Committee

Aluminum Alloy, Sheet, 3.2Cu - 0.52Mg - 0.30Ag - 0.95 Li - 0.12Zr (2198-T8), Solution Heat Treated, Cold Worked, and Artificially Aged

AMS4412C (Current)

4/8/2026

This specification covers an aluminum alloy in the form of sheet from 0.063 to 0.249 inch (1.60 to 6.30 mm) in nominal thickness (see 8.6).

AMS D Nonferrous Alloys Committee

Magnesium Alloy, Investment Castings, 9.0Al - 2.0Zn (AZ92A-T6), Solution and Precipitation Heat Treated

AMS4453H (Current)

4/8/2026

This specification covers a magnesium alloy in the form of investment castings (see 8.6).

AMS D Nonferrous Alloys Committee

Model-Based Development of the “Big 5” in Fuel Cell Systems

2026-01-0072

4/7/2026

Fuel cell systems are gaining traction across heavy-duty applications, driven by global decarbonization targets. Managing their inherent complexity and diverse architectural requirements, commonly organized into the “Big 5” fuel cell subsystems (stack, thermal, electric, anode, and cathode), necessitates advanced Model-Based Development (MBD) approaches. This paper presents and validates a constraint-graph-based, equation-oriented, acausal MBD methodology for fuel cell system (FCS) development, implemented in an industrial modeling environment. This methodology supports scalable functional and software development from 75 kW single-stack systems to twin-stack configurations exceeding 250 kW. It facilitates robust parameterization and reuse of consistently formulated, subsystem-level physical models across Model-in-the-Loop (MiL) to Hardware-in-the-Loop (HiL) environments, ensuring numerically robust software architectures and improved embedded control quality. Industrial application

Bandi, Rajendra Prasad, Bleile, Thomas

Forensic Acquisition and Analysis of Unsupported Lexus Infotainment Modules via CMD42 Bypass and Data Carving

2026-01-0540

4/7/2026

Crashes involving passenger vehicles increasingly include vehicles equipped with infotainment systems that are unsupported by commercial vehicle system forensics hardware and software. Examiners facing these systems must overcome challenges in acquiring and analyzing user data, requiring an understanding of both digital forensics principles and the proprietary characteristics of the modules. This paper presents a methodology for acquiring data from previously unsupported Lexus infotainment modules, including techniques to bypass CMD42 security locks on SD cards and extract data. Once acquired, the paper outlines methods for analyzing user data through data carving techniques, enabling recovery of information from binary images even when the full file system cannot be reconstructed. Emphasis is placed on maintaining the integrity of the evidence and validating findings through controlled testing. These validation procedures ensure that the recovered information is both accurate and

Burgess, Shanon

From Algorithm to Engineering Judgment: Navigating Topology Optimization’s Limits in Crash Applications

2026-01-0189

4/7/2026

The non-linear nature of crash scenarios has led to many designs being developed through extensive trial and error based on the intuitions of the design engineer. As such, effectively utilizing topology optimization for crash applications offers opportunities to provide major improvements in cost, weight, and passenger safety. Topology optimization is known for creating stiff, lightweight structures, however its application to crash scenarios must be handled carefully. Compliance minimization, the most common optimization objective, can yield misleading designs that prioritize undesirable qualities when developing structures for crash applications. In this paper, the design process of a passenger seat assembly subject to sequentially applied enforced displacement, and crash deceleration loads is discussed. Due to the conflicting nature of compliance minimization and enforced displacement, the design was split into two types of regions; sacrificial, which are regions manually designed

Orr, Mathew, Shi, Yifan, Lee, Jake, Gray, Savannah, Park, Taeil, Wotten, Erik, LeFrancois, Richard, Huang, Yuhao, Patel, Anuj, Kim, Hansu, Burns, Nicholas, Jalayer, Shayan, Grant, Robert, Kok, Leo, Hansen, Eric, Kim, Il Yong

Accelerating Electrification through Modular Propulsion: GM’S Strategy for BEV and BET Platforms

2026-01-0410

4/7/2026

General Motors (GM) continues to advance its electrification strategy through the development of scalable Battery Electric Vehicle (BEV) and Battery Electric Truck (BET) platforms. This paper highlights GM’s latest BEV and BET products that leverage shared Drive Unit (DU), Rechargeable Energy Storage System (RESS), and integrated power electronic (IPE) components across multiple vehicle programs. By adopting a modular and commonized propulsion architecture, GM achieves significant benefits in manufacturing efficiency, cost optimization, speed to market, and product flexibility. The shared DU, RESS, and IPE components are engineered to meet diverse performance requirements while maintaining high standards of energy efficiency, thermal management, and durability. This approach enables rapid deployment of electrified solutions across various segments, from passenger vehicles to full-size trucks, without compromising on capability or customer experience. The paper outlines the technical

Liu, Jinming, Sevel, Kris, Anwar, Mohammad, Oury, Andrew, Welchko, Brian, Gagas, Brent

Machine Learning-Based Prediction of Wind-Induced Interior Noise in Ground Vehicles

2026-01-0599

4/7/2026

In response to increasing customer demand for enhanced passenger comfort and perceived vehicle quality, OEMs in automotive and commercial vehicles are placing significant emphasis on reducing the interior cabin noise. At highway speeds, wind noise is a primary contributor to the overall noise within the vehicle cabin. Conventional approaches to predict vehicle wind noise rely on physical testing, which can only be conducted in the later stages of the design process once a physical prototype is available. Increased adoption of established computational fluid dynamics (CFD) methods has enabled earlier assessment. However, such simulations require several hours to complete, posing a challenge in the context of rapid design iteration cycles. With the growing adoption of artificial intelligence in engineering, machine learning (ML) approaches have been proposed to predict a vehicle’s aerodynamics performance. Nevertheless, development of ML techniques in the context of aeroacoustics

Higgins, John, Fougere, Nicolas, Sondak, David, Senthooran, Sivapalan, Moron, Philippe, Jantzen, Andreas, Bi, Jing, Oancea, Victor

Speed Determination Using Audio Analysis of Dash Camera Video from Commercial Vehicle Tires Frequencies for Vehicle Accident Reconstruction

2026-01-0536

4/7/2026

Prior research has validated a reliable method for determining vehicle speed using audio recorded by cameras mounted in vehicles, specifically for rolling passenger vehicle tires. Passenger vehicle tires produce a frequency component directly correlated to vehicle speed when traveling on concrete roadways. However, prior research has not been conducted on audio for rolling commercial vehicle tires, which differ in construction from passenger vehicle tires. The stiffer Commercial tires produce audio signals on roadway surfaces that passenger vehicles tires did not when tested in the prior study. The current research concluded that commercial vehicle tires rolling on various roadway surfaces also generated a frequency that varied with vehicle speed. The purpose of this study was to outline, test, and confirm the source of the speed-dependent frequency and to develop a validated method for use in forensic applications. A modified version of the passenger vehicle tire equation from prior

Vega, Henry V., Cornetto, Anthony, Ngo, Long Justin, Hatab, Ziad, Hunter, Eric

Inertial Pedal Displacement and Brake Switch Activation in Frontal Crash Events

2026-01-0541

4/7/2026

This paper presents research into the inertial displacement of brake pedals and the subsequent activation of brake light switches during crash events. In certain scenarios, such as multiple-impact crashes or crashes with pre-impact interactions such as curb strikes or sideswipes, inertial forces alone may generate sufficient brake pedal movement to trigger the brake switch, activating the brake lights. Such signals may be recorded by an Event Data Recorder (EDR) or observed by witnesses and incorrectly interpreted as an indication of intentional driver braking. To investigate this phenomenon, HYGE sled tests were performed using brake pedal assemblies and associated components from a Toyota Tacoma pickup truck and a Cadillac DeVille passenger sedan. The assemblies were subjected to acceleration pulses simulating a frontal impact, with high-speed video used to capture brake pedal displacement and brake light activation. The tests demonstrated that inertial loading from a pulse with a

Walker, James, Duran, Amanda, Barnes, Daniel, Osterhout, Aaron, Clayton, Aidan

Modification and Validation of a Finite Element Model of a Pedestrian Dummy

09-14-01-0012

4/7/2026

Aims of the research This study aims to modify the lower body (the pelvis, thigh, and leg) of the mid-sized male pedestrian dummy FE model by considering the latest version of the physical dummy and to evaluate both the accuracy by comparing test results of the past studies and the biofidelity specified in SAE J2782 in both component and full-scale validations. Methods 1 Component validation The validation of the modified pelvis model was performed in dynamic lateral compression simulations. The sacrum and the pubis force-deflection responses of the iliac or the acetabulum impact were measured. The modified thigh and leg models were evaluated in a dynamic 3-point lateral bending simulation, measuring the force-deflection responses. The results from the simulations were compared with test results and the biofidelity requirements. 2 Full-scale validation The whole-body model was updated by incorporating these modified component models. The model of the generic buck developed for the

Asanuma, Hiroyuki, Gunji, Yasuaki, Mori, Fumie, Nagashima, Akiko

Energy Efficiency Analysis of U-Haul Truck and Trailer Systems: Impact of Tongue Weight and Load Variations

2026-01-0466

4/7/2026

The demand for improved energy efficiency in real-world vehicle operations continues to grow with technology enhancement. When transporting large cargo loads with passenger pickup trucks and rental trailers, the interaction between vehicle payload, towing configuration, and fuel consumption becomes a key factor in overall system efficiency. Understanding how towing configurations and trailer loading influence fuel consumption and vehicle performance is critical for both consumer guidance and vehicle system design. This study investigates the energy efficiency of U-Haul truck and trailer systems, with a particular focus on the influence of trailer tongue weight. U-Haul truck and trailer simulation models were developed using AVL Vehicle Simulation Model (VSM) software, with an F-350 engine brake-specific fuel consumption (BSFC) map integrated to represent realistic engine performance. Two configurations with equal payload were evaluated: (1) a U-Haul truck alone, and (2) a U-Haul truck

Wang, Gang, Kathadi, Mohammad, Yang, William, Chen, Yan

Use Inertial Sliding of Reclined Seat to Enhance Occupant Retention under Rear-End Crash

2026-01-0563

4/7/2026

Autonomous vehicles may attract more passengers to recline their seat for comfort. However, under severe rear-end crashes and large reclining angle, the backward inertia could completely throw occupant out of seat. Even if the occupant body can be restrained by seatbelt, the occupant’s head could slide out of the head restraint area. Any of these situations may cause severe injuries. To address this safety concern, we developed a sliding seat system designed to enhance occupant retention. Activated by impact inertia of rear-end collision, the system allows the seat sliding backward along its track in a controlled manner, and the sliding stroke is accompanied by a restraint force and absorbs some amount of kinetic energy during the sliding. Thus, occupant retention can be enhanced, and injury risks of head and neck can be reduced. To demonstrate this concept, we built a MADYMO model and conducted a parametric analysis. The model includes a 50th percentile human model, a vehicle seat

Dai, Rui, Zhou, Qing, Puyuan, Tan, Shen, Wenxuan

Development of Automotive Hood Using Multi-Material Double Injection Molding – An Overview

2026-01-0476

4/7/2026

This paper presents the multidisciplinary development of a hybrid automotive hood manufactured using double-shot injection molding with overmolded brackets. Conventional steel and aluminum hoods, while structurally reliable, pose challenges in terms of weight reduction, pedestrian head protection, and manufacturing cost. Composite and thermoplastic alternatives supported by computational analysis and advanced molding processes provide opportunities to address these challenges. Finite element analysis (FEA) was employed to evaluate torsional and bending stiffness, locking load, and crashworthiness, while pedestrian headform simulations following ECE R127 and EEVC WG17 guidelines were conducted to assess compliance with safety regulations. Adhesion and bonding strength of overmolded polymer–polymer interfaces were studied to validate manufacturing feasibility. Results confirm that hybrid hoods fabricated using multi-material double-shot molding can achieve weight reductions of up to 30

Ganesan, Karthikeyan, Seok, Sang Ho, Jo, Hyoung Han

Sideswipe Impact Severity Testing and Analysis with an Instrumented Hybrid III Anthropomorphic Test Device (ATD)

2026-01-0532

4/7/2026

Vehicle-to-vehicle sideswipe collisions are unique in their impact characteristics because the vehicles typically do not reach a common velocity at impact. To better understand the characteristics and dynamics of sideswipe collisions, vehicle-to-vehicle crash testing was performed to find the relationships between variables related to the impact, such as closing speed, relative angle, and overlap depth. This paper discusses data collected for three sideswipe (oblique) impact tests conducted at a testing facility in Buffalo, New York. The tests were conducted using a passenger vehicle as the sideswiping vehicle, which impacted a stationary cargo van. The passenger vehicle was towed into the van at relative angles ranging from 8 to 15 degrees and at velocities of 5 to 20 mph. Two different (but identical) passenger cars and two cargo vans were used during the testing series. Test results were then utilized to investigate a methodology of analyzing sideswipe collisions as a combination of

Danaher, David, McDonough, Sean, Donaldson, Andrew, Neale, William, Cochran, Reece

CAE Acceleration with Machine Learning for Results Prediction

2026-01-0488

4/7/2026

Industries are following a tedious product development cycle for developing their product. In product development major steps includes design ideas, Drawings, CAD, CAE, Testing and design improvement cycle. This is a monotonous process and takes time which impacts on its time to deliver product and cost on development. Now a days industries are fast growing and targeting to reduce development cycle time and cost. AI&ML is impacting almost all areas in the industry and significantly reducing efforts time and cost. To make use of AI&ML in CAE, Altair Physics AI is an effective tool. To ensure the design of product traditional way is to develop a CAD of the product, develop, perform CAE and analyze performance. If we consider CAE procedure it is time consuming process which includes FEA model build, applying boundary conditions, running simulation and analyzing results which could take minutes to hours. By using ML with Physics AI we can make predictions on new design of the product in

Dangare, Anand Manohar, Kulkarni, Mandar

Application of DFSS for Optimizing Thermal Protection in Electric Vehicles during Battery Thermal Runaway Events

2026-01-0142

4/7/2026

Battery thermal runaway is a major safety concern in electric vehicles because of the extreme heat and hazardous gases released during cell failure. These venting events can quickly raise the temperature of the battery enclosure and cabin floor, threatening occupant safety. To address this challenge, this study employs the Design for Six Sigma (DFSS) methodology to design and optimize a thermal protection system that delays and limits heat transfer to the cabin. A physics-based transient heat-transfer model was combined with DFSS principles to systematically evaluate insulation materials, shield layouts, surface emissivity, and layer geometry. An L-18 orthogonal array was used to identify key parameters and quantify their influence on thermal robustness. The optimized architecture reduced cabin-floor temperature rise under severe runaway conditions (600–900 °C vent gas), meeting occupant-egress safety requirements. Findings confirm DFSS as an effective framework for developing high

El-Sharkawy, Alaa, Asar, Mona, Taha, Nahla, Sheta, Mai

The Impact of Various Renewable Hydrocarbons on Performance and Emissions in a Super Lean Burn Engine

2026-01-0306

4/7/2026

Compared to regular fuels, biofuels can play a key role as low-carbon transitional energy sources for ICE vehicles as the fleet moves towards increasing electrification. Blending of ethanol plays a key role in enhancing the anti-knock properties of the fuel and also allows renewable hydrocarbons (such as bio-naphtha) to be incorporated into the blend whilst maintaining an acceptable overall fuel quality. Super lean burn ICE technology with λ between 2 and 3 can lead to enhanced fuel economy and reduced NOx emissions. The Toyota prototype engine used to generate data for this project injects most of the fuel in PFI mode to generate a homogeneous super-lean charge in the cylinder, but just before spark ignition the DI injector sprays a small amount of fuel towards the spark plug to create a richer charge near the spark plug to promote flame kernel development. Various fuel formulations with high biofuel content were tested in both conventional and super lean burn engines. Certain fuel

Aradi, Allen, Krueger-Venus, Jens, Jain, Sandeep Kumar, Cracknell, Roger, Kolbeck, Andreas, Shibuya, Masahiko, Yamada, Ryota, Matsubara, Naoyoshi, Kitano, Koji

Application of Topology Optimization to Production-Ready Passenger Seat Components Design

2026-01-0498

4/7/2026

Lightweighting of components has become a key challenge in the development of modern transportation systems. In the automotive and aerospace industries, the overall mass of a vehicle has a significant impact on its fuel efficiency and manufacturing cost. Therefore, the lightweight design of vehicle components is crucial in the industrial field. Topology optimization (TO) is a computational design approach aimed at achieving lightweight designs. However, most existing studies focus on simplified academic models, with limited demonstration in real-world applications. This paper presents a revised TO workflow to obtain production-ready design and a practical implementation of TO in the design of three structural components in the aerospace industry: seatback frame, seat fuselage mount, and seat spreader. The revised TO workflow incorporates the practical demands of industry, including enhanced manufacturability and cost efficiency through TO design. The resulting designs are evaluated to

Lee, Hanbok Jake, Shi, Yifan, Gray, Savannah, Orr, Mathew, Park, Taeil, Wotten, Erik, LeFrancois, Richard, Huang, Yuhao, Patel, Anuj, Kim, Hansu, Jalayer, Shayan, Burns, Nicholas, Hansen, Eric, Grant, Robert, Kok, Leo, Kim, Il Yong

Pre-Impact Seat Rotation for Mitigating Lumbar Injury in Flying Car Crash

2026-01-0558

4/7/2026

Flying cars have already been used in tourism, firefighting, and logistics, and might be soon used for short-distance commute. However, the lumbar spine injury risks in flying car crash accidents have raised safety concerns. This is because the crash load of a flying car is largely aligned with the orientation of the occupant’s spine. This study introduces a countermeasure of actively adjusting seat posture for mitigating lumbar injury in crash events. A flying car crash usually has a few seconds of warning time before collision to ground. The pre-impact warning time is enough to rotate the seat and occupant together using seat motors. Posteriorly rotating seat can alter the angle between the crash load and the spinal axis, thereby reducing lumbar injury risk. Using numerical simulations, the 30g deceleration pulse defined in SAE-AS-8049 was applied to seat of flying car. The THUMS (Total Human Model for Safety) human body model was used to model occupant, sitting in a typical vehicle

Zhuang, Ziao, Puyuan, Tan, Shen, Wenxuan, Zhou, Qing, Gu, Gongyao

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