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Vertical Flight Society Technical Papers - Coming Soon to Mobilus

Vertical Flight Society papers coming soon to SAE Mobilus. In partnership with the Vertical Flight Society (VFS), SAE Mobilus will be hosting more than 17,000 technical papers and proceedings from VFS. Click here to see a sample of the content covering decades of rotorcraft and vertical flight technologies.

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

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

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

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

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

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

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

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

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

Materials and Manufacturing

Passenger Cars - Mechanical Systems

Recent Books

Browse All 722

Metallic Materials Properties Development and Standardization (MMPDS) Handbook - 2026 - Volume II

B-994_VOLUME27/1/2026

Volume II publishes the framework for generating and analyzing the data so that material sponsors can generate the right data, knowing how it will be analyzed by the Battelle Memorial Institute. MMPDS-2026 Volume II Process Intensive Materials and Joining Technologies does not currently have any material properties, focusing on additive manufacturing of metallic materials. MMPDS-2026 Volume II focuses on non-conventional processes and will be published each year. Volume I: Conventional Materials and Joint Allowables.

Metallic Materials Properties Development and Standardization (MMPDS) Handbook - 2026 - Volume I

B-994_VOLUME17/1/2026

The Metallic Materials Properties Development and Standardization MMPDS-2026 supersedes MMPDS-25 and prior editions of the MMPDS Handbook as well as all editions of MIL-HDBK-5, Metallic Materials and Elements for Aerospace Vehicle Structures Handbook that were maintained by the U.S. Air Force. The last edition, MIL-HDBK-5J was cancelled by the U.S. Air Force in March 2006. This document contains design information on the mechanical and physical properties of metallic materials and joints commonly used in aircraft and aerospace vehicle structures. All information contained in this Handbook has been reviewed and approved using a standardized process. The development and ongoing maintenance process involves certifying agencies, including the FAA, DoD, and NASA, and major material suppliers and material users worldwide. The information and procedures in this Handbook are continuously reviewed and modified or removed as determined to be appropriate. With advances in materials and fastener

1D and MultiD Modeling Techniques for IC Engine Simulation Second Edition

R-5805/29/2026

The internal combustion (IC) engine remains the most widely used thermal machine in the world and will continue to play a central role in global mobility for decades to come. Even as alternative powertrains expand, optimized IC engines—often integrated within hybrid and electrified architectures—are essential to achieving low fuel consumption, near-zero pollutant emissions, and reduced carbon dioxide output. Advances in combustion strategies, synthetic fuels, turbocharging, and aftertreatment systems are driving this evolution. This fully revised and expanded second edition reflects the rapid progress made in engine modeling and simulation over the past two decades. One-dimensional (1D), three-dimensional (3D), and coupled 1D–3D modeling techniques have become indispensable tools in modern engine design, enabling engineers to evaluate performance, efficiency, and emissions through advanced virtual engine environments. Bringing together contributions from leading international

Variable Compression Systems for Future Engines and Fuels

R-5534/30/2026

Variable Compression Engines: Enabling Net Zero explores variable compression ratio (VCR): one of the most promising—and historically elusive—advancements in internal combustion engine (ICE) technology. Long recognized for its thermodynamic benefits, VCR has challenged engineers for decades due to its mechanical complexity. Today, as the global mobility landscape demands ever higher efficiency, lower emissions, and greater fuel flexibility, VCR has emerged as a viable and transformative solution. This book delivers a comprehensive and authoritative examination of VCR technology, quantifying its efficiency and CO2-reduction potential while surveying the wide range of mechanisms conceived, developed, and tested over more than a century of engine innovation. By combining historical insight with modern analysis, the authors reveal the remarkable ingenuity of past and present engine designers—and demonstrate that VCR is not only feasible, but increasingly essential. Positioned squarely

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

Safety, ADAS, and Cybersecurity: Vol. 4

EPRCOMPV01202512/29/2025

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A Review of UAV Support Technologies for Low-Altitude Airspace Operation and Management

2026-99-0597

7/10/2026

In recent years, with the low-altitude economy developing rapidly, the operation and management of low-altitude airspace has gradually become a hot topic. Unmanned aerial vehicles (UAVs) constitute a fundamental component of the low-altitude airspace ecosystem, significantly influencing its structure and functionality. The technological advancement of UAVs has fundamentally transformed the operational paradigm for low-altitude airspace management. This paper presents a comprehensive review of UAV-supported technologies in the context of low-altitude airspace operations and management. It systematically analyzes key technologies and applications of UAVs in areas such as airspace capacity and safety assessment, trajectory planning, and standardized flight management. Drawing from kinematic analysis and traffic flow theory, UAV density control and collision risk prediction offer quantitative insights into airspace capacity evaluation. Additionally, probabilistic analysis and simulation

Gong, Lei, Ma, Zhenxiao, Luo, Qin

Research on Age-Friendly Design Strategies for Autonomous Buses Based on Service Design Concepts

2026-99-0536

7/10/2026

In the context of the accelerating development of an aging society, the inconvenient mobility of the elderly conflicts with the design of existing vehicles. The promotion and development of autonomous vehicles can provide solutions to this conflict to a certain extent. But existing autonomous vehicles lack a systematic age-friendly design. This study is based on a service design idea and employs the KJKANO hybrid model. The KJ method is used to construct a three-tier demand framework of “safety-function-emotion.” The KANO method is applied to identify the priority classification of each demand within the tiered framework. The study derives an aging-friendly design strategy for autonomous buses that prioritizes safety demands as the foundation, with functionality and emotional demands balanced accordingly. These strategies are then implemented in design practice. This study provides a user-centered systematic solution for the age-friendly design of autonomous buses, offering insights

Li, Wangyan, Ji, Yuanyuan

An Exploration of the Potential of Urban Linear Space under the Background of Fully Autonomous Vehicle System in Beijing

2026-99-0551

7/10/2026

The technology of autonomous vehicles has become the bellwether for the next transportation evolution. Based on the system of level 5 autonomous vehicles (fully autonomous vehicles), there will be space released from the existing urban context, including linear space, nodular space, and intersected space because of the enhancement of transportation efficiency and organization. The study took Beijing as an example to explore the linear space releasing potential under fully Autonomous Vehicles system to provide a reference for future urban planning. Considering saturation flow rate, speed, parallel throughput, vehicle occupancy, and safe headway, we quantitatively analyzed the potential release from various types of urban roads. The results shows that the expressways, arterial roads, secondary arterial roads, and branch roads could release up to 50%, 66% 50%, and 75% of the road space, respectively. The study verified that fully AV system can release great amount of public space, and

Ding, Yufei, Hou, Shuyu

Simulation Analysis of Pure Electric Vehicle Equipped with Continuously Variable Transmission

2026-99-0522

7/10/2026

This study looks into the performance traits of a pure electric car that has a continuously variable transmission (CVT) system by doing careful simulations. The research is mostly about checking how well it performs dynamically and how much better its energy efficiency is compared to regular designs. With the help of AVL Cruise software, a detailed drivetrain model was made to test things like how fast it can accelerate, its top speed, how well it climbs hills, and how much energy it uses when driven in standard ways. The simulation results show some big improvements: the CVT car can go from 0 to 100 km/h in 12.92 seconds, which is 14% quicker than expected; it can reach a top speed of 179 km/h, 15% higher than planned; and it can climb really steep hills at a 41.33% gradient. The energy efficiency analysis also found that it uses less power, consuming just 15.88 kWh per 100km under NEDC conditions and 13.72 kWh per 100km in UDC cycles, which are 21% and 24% less than before. These

Chen, Haishan, Gong, Naifa, Pan, Yulong, Cai, Zhicheng, Gao, Yujie, Shen, Xiaobing, Fu, Xianlan, Chen, Keren

Traffic Flow Prediction System Based on Deep Learning

2026-99-0549

7/10/2026

Traffic flow prediction is of great significance for improving the operation efficiency of the transportation system, optimizing travel experience and reducing traffic congestion. Traditional traffic flow prediction methods are difficult to capture the spatio-temporal nonlinear characteristics of traffic flow due to its simple model and insufficient feature extraction ability. Therefore, an intelligent traffic flow prediction system based on deep learning is proposed, constructs a deep learning model based on graph convolution and fusion of attention mechanism LSTM. Based on this, a traffic flow prediction system is implemented. Experiments show that, on the PeMSD4 and PeMSD4 datasets, the error of the model in RMSE and Mae indicators is significantly reduced compared with the traditional methods, which provides an efficient solution for traffic flow prediction and congestion analysis, and has both theoretical innovation and engineering practical value.

Tang, Zhan, Lu, Xiaoyu, Yang, Nian, Xiang, Xiaohong, Hou, Xiang, Peng, Xiaoli

Human-Machine Ergonomics Analysis of Civil Aircraft Electric Pilot Seats

2026-99-0570

7/10/2026

This paper uses a structured evaluation framework to study the ergonomics of electric pilot seats in modern civil aircraft. We have established a multi-level indicator system to examine the adjustability, pressure distribution, dynamic response and, fatigue relief effect of the seat. All experimental data were obtained from a full-scale cockpit simulator environment, where a ground-based mock-up and motion-free simulated cockpit were used to replicate real operational posture, control-reach conditions, and long-duration mission loads. This framework combines experimental measurement and fuzzy evaluation techniques to quantify the quality of human-computer interaction. Test results show that compared with ordinary seats, the prototype seat has a wider adjustment range, a more uniform pressure distribution, and a smoother dynamic response. It is particularly worth mentioning that it can delay the emergence of fatigue during long-term operation, which proves the advantages of the electric

Tian, Yanan, Pi, Zhengyang

2025 International Conference on Intelligent Transportation and Low Altitude Transportation (ITLAT)

2026-99-0500

7/10/2026

TOC

Tobolski, Sue

Temperature Influence Analysis and Compensation Method of Hemisphere Resonator Gyroscope

2026-99-0514

7/10/2026

Hemisphere resonant gyroscope (HRG) is a new type of vibration gyroscope with high precision, high reliability, and long lifespan. Improving the temperature stability of a hemispherical resonant gyroscope (HRG) has profound implications for navigation and guidance systems as well as airborne sensor technology. By optimizing temperature compensation algorithms or improving material thermal properties, the angular velocity measurement error caused by temperature drift can be significantly reduced, thereby improving the long-term positioning reliability of navigation systems in extreme temperature fluctuation scenarios. This article starts with the structure of the hemispherical resonant gyroscope, studies the temperature characteristics of the hemispherical resonator through formula theory, verifies and analyzes the temperature characteristics of the hemispherical resonant gyroscope through experiments, and designs a temperature compensation scheme. Through experimental data analysis

Wang, Jiachen, Chen, Pu, Yao, Zhiqiang, Zhang, Yi, Bai, Fan

Design and Testing of a Quasi-Zero-Stiffness Vehicle-Mounted Isolation System with Additional Inerter

2026-99-0520

7/10/2026

Vehicle vibrations during precision instrument transport can cause damage and failure. Existing vibration isolators often lack reliability, mass production feasibility, and easy maintenance. In this paper, we design and analyze a quasi-zero-stiffness vehicle-mounted isolator with an inerter, decreasing dynamic stiffness while raising the effective mass. Theoretical, simulation, and experimental results show improved isolation performance, lower isolation frequency, and a broader isolation bandwidth.

Li, Kai, Lv, Sibo, Sun, Ning, Dai, Shijie

Voltage Regulation and Limits

J3226_202607 (Current)

7/10/2026

This document defines the test procedures and performance limits of steady state and transient voltage characteristics for 12 V, 24 V, or 48 V electrical power generating systems used in commercial ground vehicles.

Truck and Bus Electrical Systems Committee

Study on Diesel-Methanol Non-Premixed Combustion Characteristics of a Marine Dual-Fuel Engine at Different Methanol Substitution Rate

2026-99-0517

7/10/2026

Methanol use in marine engines has the potential to reduce nitrogen oxide emissions, particulates, and greenhouse gas emissions. A turbocharged four-stroke marine diesel powerplant was converted to run as a double-DI (direct injection) diesel-methanol hybrid engine. Experimental studies using a non-premixed combustion scheme showed that higher methanol substitution ratios (MSR) led to increased peak heat release rates. The combustion process displayed distinctive two-phase behaviors. Increasing MSR caused retarded ignition timing, shortened combustion duration, and improved thermal efficiency. Combustion stability was significantly improved at higher MSR. Emissions results showed NOX and HC were increased in proportion to MSR, whilst particulate emissions and CO concentrations were inversely reduced. Methanol enrichment was found to enhance NOX and HC formation processes but also accelerate soot particulate decomposition and CO oxidation mechanisms.

Li, Xiao, Jiang, Yuqi, Yan, Ping, Zheng, Liang, Li, Hongmei, Zhang, Wenzheng, Chen, Chao, Man, Zhongguo

Design and Analysis of Orthogonal Excitation Eddy Current Brake for High-Speed Trains

2026-99-0513

7/10/2026

As high-speed train technology advances, the demands on braking system performance have intensified. Known for their efficiency, reliability, and eco-friendliness, Linear Eddy Current Brakes (LECB) have become a focal point in the research and development of high-speed train braking systems. This paper presents an innovative Orthogonal Excitation Eddy Current Brake (OEECB), which enhances the braking force without modifying the overall dimensions of the conventional LECB. By adding a set of longitudinal excitation coils parallel to the rail surface, the OEECB creates an orthogonal excitation structure that augments the braking force. Initially, this paper outlines the design concept of the OEECB and then analyzes its working principle based on electromagnetic field theory. Subsequently, a finite element solver is employed to numerically model the electromagnetic characteristics of the OEECB. Finally, by comparing the performance differences between the conventional LECB and OEECB, the

Huang, Liuwen, Zuo, Jianyong, Zhang, Yu

Researchon Key Technology Optimizationof Automotive Magnetic Continuously Variable Transmission

2026-99-0509

7/10/2026

Traditional mechanical continuously variable transmission (CVT) has a complicated structure. During the transmission process, the master and slave wheels rub against each other to produce chattering and heat loss, and the master and slave wheels are seriously worn. In order to improve the transmission efficiency and reliability of continuously variable transmission, Automotive magnetic CVTs (Manetti Continus, Livaria, Breitlans, Mack) were used as research objects. By establishing the efficiency model of key parts, the relationship between the efficiency of each component and different parameters is transformed and calculated, and then it is optimized using Matlab. The finite element analysis of a permanent magnet eddy current speed regulating device is carried out by using finite element Ansys Maxwell, and the relationship curve between the average meshing area and each parameter is analyzed. The results show that the volume of the optimized gear train is reduced by about 51.7

Zhou, Dan, Zhang, Bolin

Distributed Control Method and System of Formation Train Based on Multi-Objective Operation Curve Optimization

2026-99-0555

7/10/2026

In order to improve the transportation efficiency of high-speed trains, reduce the operational energy consumption and ensure the on-time arrival of trains, the operation curve optimization is regarded as a key way to achieve the above objectives. In this paper, a distributed control method and system for grouped trains based on multi-objective running curve optimization is introduced. Firstly, the train dynamics equations are established by considering the combined forces during train operation and the train driving maneuvering strategy, combining with the line conditions, and dividing the train operating conditions; secondly, combining with the virtual grouping technology, the train units are kept in a high safety and smooth tracking operation with small intervals between the train units; and then the constraints, such as setting up safety protection distance and Then, the constraints of safety protection distance and space-time safety protection are set, and with energy-saving and

Jiang, Qiqi, Chen, Guangwu, Shi, Jianqiang, Wang, Dong, Si, Yongbo, Li, Peng, Zhang, Wentao, Yang, Yang

Nonconvex Quadratic Programming Problem for Ship Magnetic Dipole Array Model

2026-99-0587

7/10/2026

The magnetic field modeling methodology for ships based on magnetic dipole arrays demonstrates heightened sensitivity to input data. When addressing overdetermined systems characterized by numerous variables and constrained measurement points, the coefficient matrix frequently develops pathological ill-conditioning, leading to solution divergence and compromised result accuracy. This research reformulates the ship magnetic field inversion challenge as a non-convex quadratic programming problem, employing the Successive Convex Approximation (SCA) algorithm as the computational solver. Rigorous comparative validation was performed against conventional stepwise regression algorithms and experimental datasets acquired from scaled ship model measurements. Results substantiate that while the modeling precision of the SCA algorithm remains comparable to that achieved by stepwise regression methods, SCA exhibits demonstrably superior solution stability. This enhanced robustness positions SCA

Chen, Hao, Pan, Xun

Optimizing Autonomous Obstacle Avoidance with PON Architecture and SDN-Based Dynamic Scheduling

2026-99-0592

7/10/2026

This study addresses the challenges of communication delays and system stability in autonomous obstacle avoidance (AOA) systems under next-generation vehicular electronic/electrical architectures. A centralized PON-based architecture is proposed, leveraging XGSPON technology to enhance bandwidth capacity and reduce electromagnetic interference, while rigorously analyzing worst-case in-vehicle communication (IVOC) delays. To mitigate latency impacts, a Software-Defined Networking (SDN)-driven dynamic scheduling strategy prioritizes safety-critical data streams (e.g., environmental perception, motion control) through adaptive resource allocation. Further integrated with a robust H-infinity LQR controller, the co-design framework ensures precise trajectory tracking and suppresses steering oscillations under communication uncertainties. Simulation tests validate the framework's efficacy, demonstrating significant reductions in loop delays and improved dynamic stability in complex scenarios

Wang, Wenwei, Han, Muchen, Cao, Wanke

Optimization of Preheating Energy Distribution for Low-Temperature Cold Starts in Diesel-Electric Hybrid Vehicles

2026-99-0516

7/10/2026

To minimize energy input and preheating time, this study first analyzed the energy consumption of intake air, lubricating oil, and coolant preheating through simulations. Temperature rise data were collected under various heating parameters. Next, simulations evaluated the hybrid power system’s resistance characteristics immediately after startup and the combustion parameters during the first cycle post-ignition under different temperatures. The temperature thresholds for successful start-up were identified, defining the feasible domain for optimization. Optimization calculations aimed to minimize preheating time and energy input, constrained by maximum preheating power. Results show that intake air heating has the greatest impact on start-up success, followed by lubricating oil heating. It is recommended to increase energy allocation to intake air and lubricating oil heating. This optimized strategy reduces preheating time and energy input by approximately 26% without changing the

Wei, Shengchen, Zhao, Zhenfeng

Multi-Objective Optimization Research and Design of Seat Structure in Vehicle Collision

2026-99-0518

7/10/2026

The vehicles often accompanied by a huge impact in the collision process, high-quality and high-strength car-seats can better protect the safety of passengers. However, in the call for vehicle energy saving and emission reduction, the lightweight design of car-seats is imminent. Therefore, it is necessary to achieve lightweight seat weight while ensuring vehicle safety. Based on the dynamic condition of vehicle collision, this paper takes the rear seat of a certain model as the research object, takes multiple responses of the seat skeleton system as the target, establishes a multi-objective optimization model of the seat skeleton, determines the optimization result with the greatest comprehensive satisfaction, verifies the optimization result of the seat skeleton. The correctness and feasibility of the design method are proved.

Shao, Youlin, Ni, Weiyu, Chen, Daojiong, Cheng, Zhiqing

Aircraft Noise Event Identification Technology Based on Single Acoustic Vector Sensor

2026-99-0591

7/10/2026

With the rapid development of China’s civil aviation industry, the problem of airport noise has attracted widespread social attention. The requirement for the real-time monitoring and evaluation of acoustic environment around airports is becoming more and more intense. The identification of aircraft noise events in the complex acoustic environment surrounding the airport is the most critical technical problem in airport noise monitoring. However, the traditional noise source identification technology is difficult to be widely used in real-time monitoring system due to its large errors and complex deployment conditions. This paper presented an aircraft noise source identification technique based on a single acoustic vector sensor. The azimuth parameters of the noise source were estimated by the three-dimensional spatial positioning algorithm of sound pressure and particle vibration velocity combined with information processing, and the three-dimensional footprint of the noise event in

Hou, Jiayu, He, Tianlun, Zhu, Lin, Chen, Ying, Liu, Yinhui, Lv, Lei, Wang, Yuhao, Chen, Da

Multi-sensor Data Fusion Based on Big Data Modelling

2026-99-0568

7/10/2026

The collection of road high-frequency data often involves inputs from multiple sensors, such as stress and strain, and sampling of these data features a high sampling rate of up to 2,000 Hz. High-frequency sampling enables capturing of the internal stress and strain of the pavements when vehicles are passing and facilitates the analysis of the pavement structure and prediction of its long-term service performance. However, while the sensors are continuously collecting data, the time the vehicles pass is discrete and unpredictable, resulting in a large number of low information density or irrelevant data. Even when the massive high-frequency data are collected, challenges remain in data transmission, storage, and analysis—the challenges are attributable not only to the massive quantity and complexity of data from multiple sensors, but also to the inconsistent data formats, misaligned timestamps, and multi-sensor data fusion difficulties. In response to the challenges specified above, a

Gang, Jian, Zhang, Yue, Chen, Yinghao, Zheng, Xiaoyan, Wang, Taojie, Liu, Yilin, Guan, Wei, Wu, Jiangfeng

Research on Battery Environment Heat Dissipation Control System

2026-99-0535

7/10/2026

Batteries generate a large amount of heat during operation, and if it cannot be dissipated in a timely and effective manner, it will seriously affect the performance, lifespan, and even safety of the battery. Therefore, battery heat dissipation has become a key challenge in the development of new energy vehicles. The traditional liquid cooling system has problems such as complex design and control, and the need to improve heat dissipation efficiency. To address these issues, this study proposes an optimized design scheme for battery environment heat dissipation control system based on liquid cooling heat dissipation system. This study first conducted an in-depth analysis of the thermal generation mechanism of lithium-ion batteries and studied existing examples of thermal management schemes. On this basis, an innovative forward and reverse circulation device was designed, combined with a liquid cooling heat dissipation structure. The Keil uVision4 programming software was used to write

Ding, Xvqiang, Ni, Yiwei, Gu, Chen, Zhang, Jin, Chen, Mingyang, Jiao, Yunxiao

Research on the Design of Lane Line Recognition and Deviation Warning System Based on Machine Vision

2026-99-0566

7/10/2026

In order to reduce traffic accidents caused by cars straying from lanes, a lane line recognition and deviation warning system based on machine vision is designed. It mainly includes image preprocessing, lane line detection, and the design of a deviation warning model. “In this study, an ROS-based intelligent vehicle-mounted camera is adopted for road image collection. To reduce the computational load of data processing while guaranteeing the algorithm’s accuracy and reliability, grayscale conversion and region of interest (ROI) extraction are implemented to finish the image preprocessing stage. Additionally, a fusion strategy of global and local thresholds is introduced to enhance both the operational speed and detection accuracy of the algorithm” use the Canny operator for the edge feature extraction; and complete the fitted lane lines with the improved Hough transform. Finally, based on the Kalman filter and camera viewpoint conversion coefficient algorithm, the lane line offset is

Wang, Xufeng, Zhang, Chunshu, Wang, Yan, Chen, Yihui, Ji, Rui

Advances in Research on Emergency Lane Activation Model for Highways

2026-99-0542

7/10/2026

Qin, Fengcai, Chen, Jianqiu, Che, Guoyan, Lou, Benxiao, Wang, Xiang, Ning, Longtang, Zhou, Shixuan, Zhang, Xiyuan, Bao, Chun, Gu, Guobin

Missile Pose Measurement Based on ArUco Markers

2026-99-0576

7/10/2026

This paper presents a monocular vision-based system for high-precision missile pose measurement using ArUco markers and Perspective-n-Point (PnP) algorithms. By deploying 6 × 6 ArUco markers on a cylindrical missile mock-up, the system establishes 3D-2D correspondences between structured-light-scanned models and camera images to solve the PnP problem. The proposed approach integrates optimized ArUco marker recognition — leveraging adaptive thresholding, contour simplification, and grid-based validation — with the Efficient PnP (EPnP) algorithm to achieve real-time pose estimation. Experimental validation demonstrates angular accuracy of ± 0.3° in roll/pitch/yaw and positional accuracy of ± 2 mm within a 2 m range under controlled conditions. The system exhibits robustness against partial occlusions and motion blur, with degraded performance (± 1.2°, ± 5 mm) in extreme scenarios. Key innovations include a streamlined marker detection pipeline and adaptive pose refinement using Levenberg

Wang, Ruiyang, Zhang, Chaofan

Privacy-Preserving UAV-Based Traffic Data Acquisition Platform

2026-99-0595

7/10/2026

This paper puts forward a Privacy-Preserving UAV-Based Traffic Data Acquisition Platform to address 1) privacy leakage, 2) limited scenario coverage, and 3) low traffic data utilization efficiency in urban traffic monitoring environments. Our system integrates three innovations: 1) Dynamic Privacy Masking (DPM) and Dual-Track acquisition (DTC), which hides sensitive information (e.g., faces, license plates or LPL) in real-time while preserving critical traffic data (e.g., vehicle density, speed), 2) traffic data Localization (DL) and Privacy-Enhanced Federated Learning (FEFL), enabling cross-regional collaboration without raw traffic data sharing by perturbing neural network updates with differential privacy (DP), and 3) Ground-Air Collaboration (GAC) and VPF (VPF), combining UAVs with ground sensors and digital twins (DTs) to cover blind spots (e.g., tunnels, extreme weather). Experimented on UA-DETRAC and CitySim traffic data-sets, the platform achieves 92% privacy compliance (GDPR

Zhang, Shilin, Yan, Ming

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