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Announcements for SAE Mobilus

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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 ResponseEPR202501711/24/2025
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 advanced air mobility and drone industry further enable the development of modern, safe, and practical WIG platforms. Click here to access the full SAE EDGETM Research Report portfolio.
Next-gen AI for Aerospace EngineeringEPR20250169/22/2025
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 mitigation of algorithmic biases. Click here to access the full SAE EDGETM Research Report portfolio.
Sustainable Circular Future Mobility: Environmental Impact of Next-gen VehiclesEPR20250159/22/2025
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 actionable solutions to help stakeholders better navigate the transition toward a circular future for mobility. It further highlights the overlooked complexities in the Global South, emphasizing the importance of ethical market expansion and localized mobility strategies. Click here to access the full SAE EDGETM Research Report portfolio.
Safety Impacts of Active Safety and Driving Automation FeaturesEPR20250138/13/2025
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 suggestions for future research will also be discussed. Click here to access the full SAE EDGETM Research Report portfolio.
Small, Mobile, and Autonomous Agricultural RobotsEPR20250128/13/2025
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 track, as well as the economics of moving capital intensive automation systems toward a service-provision business model. Click here to access the full SAE EDGETM Research Report portfolio.
Hybrid Data- and Physical Model-driven Safe and Intelligent Motion Planning and Control for Autonomous VehiclesEPR20250147/18/2025
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 Control for Autonomous Vehicles presents a hybrid framework that combines data-driven insights with the robustness of physical models. It identifies key challenges in fusing these disparate methods and outlines potential solutions in developing robust fusion strategies, establishing generalized mixed dynamics models, and designing multi-objective robust control systems. In addition, the report explores future research directions to enhance learning efficiency, improve adaptability to rare but critical scenarios, and ultimately pave the way for secure, efficient, and human-like autonomous driving systems. Click here to access the full SAE EDGETM Research Report portfolio.
Product Assurance in the Age of Artificial IntelligenceEPR20250115/21/2025
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 redefined what it means to be a "product." Click here to access the full SAE EDGETM Research Report portfolio.
Edge Artificial Intelligence in Connected, Cooperative and Automated MobilityEPR20250095/20/2025
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 intelligence (AI) is instrumental in processing such data, and in that context, “edge AI” is a more recent type of implementation. Edge AI involves AI algorithms in edge computing devices, which requires hardware operating close to where data is generated. This report explores the potential of edge AI in CCAM. Different perspectives on edge AI for CCAM are explored and definitions drafted. Primary applications are explored, and an outlook on further advancements in applications is presented. The report includes a discussion on the benefits, risks, and challenges related to the use of edge AI in this domain. Major issues such as privacy and cybersecurity are considered, as are misconceptions. Furthermore, potential learning benefits, using experiences gained in other sectors, are introduced. NOTE: SAE Edge Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. These reports are not intended to resolve the challenges they identify or close any topic to further scrutiny.
Leveraging Advanced Data Technologies for Smart Traffic ManagementEPR20250085/20/2025
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 educational programs in leveraging AI for transportation applications are emphasized in this report. Click here to access the full SAE EDGETM Research Report portfolio.
Space-based Solar Power for Instantaneously Dispatchable Renewable Power on EarthEPR20250054/24/2025
Recent advances are reducing the cost of space launch, high specific power solar cells, and the production of satellite systems. Modular architectures with no moving parts and distributed power systems would minimize assembly and maintenance costs. Together, this may enable space-based solar power to provide decarbonized dispatchable power at a lower cost than equivalent technologies such as nuclear power stations. Space-based Solar Power for Instantaneously Dispatchable Renewable Power on Earth discusses the advances in emerging technologies, like thin film solar cells, reusable launch vehicles, and mass-produced modular satellite systems that would make economic space power feasible. Click here to access the full SAE EDGETM Research Report portfolio.

Latest Journal Issues

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Passenger Vehicle Systems
SAE International Journal of Passenger Vehicle Systems
Electrified Vehicles
SAE International Journal of Electrified Vehicles
Advances and Current Practices in Mobility
SAE International Journal of Advances and Current Practices in Mobility
Sustainable Transportation, Energy, Environment, & Policy
SAE International Journal of Sustainable Transportation, Energy, Environment, & Policy
Transportation Cybersecurity and Privacy
SAE International Journal of Transportation Cybersecurity and Privacy
Connected and Automated Vehicles
SAE International Journal of Connected and Automated Vehicles
Vehicle Dynamics, Stability, and NVH
SAE International Journal of Vehicle Dynamics, Stability, and NVH
Transportation Safety
SAE International Journal of Transportation Safety
Alternative Powertrains
SAE International Journal of Alternative Powertrains
Commercial Vehicles
SAE International Journal of Commercial Vehicles
Passenger Cars - Mechanical Systems
SAE International Journal of Passenger Cars - Mechanical Systems
Passenger Cars - Electronic and Electrical Systems
SAE International Journal of Passenger Cars - Electronic and Electrical Systems
Engines
SAE International Journal of Engines
Aerospace
SAE International Journal of Aerospace
Materials and Manufacturing
SAE International Journal of Materials and Manufacturing

Recent Books

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Composite Materials Handbook Volume 5 - Revision BR-4608/27/2026
The fifth volume of this compendium publishes technical guidelines and properties of ceramic matrix composite material systems. The content includes information on material selection, processing, characterization, testing, data reduction, design, analysis, quality control, application, case histories, and lessons learned of typical ceramic matrix composite materials. Initial Release of Volume 5 superseded Mil-HDBK-17-5 dated June 17, 2002. The Composite Materials Handbook, referred to as CMH-17, is an engineering reference tool that provides comprehensive, practical engineering guidelines that have proven reliable for the design, fabrication, characterization, test, and maintenance of polymer matrix, metal matrix, ceramic matrix, structural sandwich, and non-metallic AM materials. CMH-17 provides information and guidelines necessary to design and fabricate end items from composite materials. The compendium includes reliable data, linked to control of processes and raw materials, to provide material property basis values and design information that promotes the safe use of ceramic matrix composites in aerospace applications. CMH-17 provides information and guidelines necessary to design, fabricate, and maintain components from composite and non-metallic additively manufactured (AM) materials. In support of this purpose, the handbook constitutes an overview of the field of advanced materials technology and engineering. It is used by engineers worldwide in designing and fabricating products made from composite materials.
July 2026 AMS IndexAMSJULY-20267/22/2026
Metallic Materials Properties Development and Standardization (MMPDS) Handbook - 2026 - Volume IB-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 systems, and with the review process of existing information, periodic updates of the MMPDS should be expected. As such, it is recommended that the latest version of the MMPDS be used. Volume II: Process Intensive Materials and Joining Technologies.
Metallic Materials Properties Development and Standardization (MMPDS) Handbook - 2026 - Volume IIB-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.
1D and MultiD Modeling Techniques for IC Engine Simulation Second EditionR-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 researchers and industry experts, this book presents the most significant and recent developments in IC engine simulation. Topics include 0D, 1D, quasi-3D, and full 3D modeling approaches; turbocharging and aftertreatment systems; co-simulation and real-time applications; hydrogen and two-stroke engines; and advanced thermal modeling techniques. Designed for engineers, researchers, and graduate students, this second edition serves as a comprehensive reference for understanding, comparing, and applying state-of-the-art IC engine modeling methodologies in an evolving mobility landscape. Chapter topics include: • state of the art of 1D thermo-fluid dynamic simulation models • virtual engine development: 1D- and 3D-CFD up to full engine simulation • advanced 0D and quasiD thermodynamic combustion models for SI and CI engines • compressor and turbine (turbocharger, supercharger, or turbocompounding device) as boundary conditions for 1D simulations • 3D-CFD combustion models for SI and CI engines • model order reduction for real-time simulation and control applications • modeling of EGR systems •1D engine model in XiL application-a simulation environment for the entire powertrain development process • coupling of 1D and 3D fluid dynamic models for hybrid simulations • extending the 1D approach to the simulation of 3D components: the quasi-3D approach • 1D simulation models for aftertreatment components• 3D simulation models for after-treatment systems • modeling of IC engine silencers and tailpipe noise: 1D and 3D approaches • hydrogen-fueled internal combustion engines • optimization of the gas exchange process in advanced 2-stroke engines • IC engine 0D/1D thermal modeling
Variable Compression Systems for Future Engines and FuelsR-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 within the context of global decarbonization, the book argues for a realistic, inclusive pathway to net-zero emissions—one in which ICEs continue to play a critical role. VCR technology enables higher efficiency across almost all operating conditions, supports advanced combustion strategies, and allows engines to operate effectively on a broad spectrum of low- and zero-carbon fuels, from biofuels to synthetic e-fuels. With VCR now in high-volume production and poised for broader adoption across automotive, heavy-duty, and marine applications, this timely volume is an essential resource for OEMs, suppliers, policymakers, researchers, and students seeking practical, scalable solutions for a sustainable energy future. Chapter topics include: • compression ratios and fuels • compression ratio limits • cylinder head VCR • cylinder block VCR • connecting rod variable compression • piston VCR • cranktrain and linkages VCR • modulated crankshaft eccentricity VCR • axial or barrel engine VCRs • high power and downsized engines • impact of VCR systems on engines • VCR applications for the future • variable compression for future engines and fuels • VCR cost–benefit analysis
Aerospace Standards Index - 2026ASIN20262/25/2026
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 4R-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 include: • Holistic reliability across design, manufacturing, supply chain, and marketing. • Advanced experimental designs, including split-plot and fractional factorial methods. • Fault tree analysis (FTA) and FMEA for failure prediction and prevention. • Supply chain optimization through multivariate process control. • Production and field reliability using design for testability and diagnostics. • Electric vehicle system and battery reliability analysis. • Marketing reliability driven by voice of customer and data-based value analysis. This book is an essential resource for engineers, operations leaders, and technical managers who want to build resilient systems, unlock innovation, and achieve long-term competitive advantage through disciplined, data-driven reliability.
Fundamentals of Sustainable Aviation FuelsR-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 performance and emissions reduction potential; safety, certification, and market integration; and future projections supported by international initiatives and regulatory frameworks. By combining technical depth with practical relevance, Fundamentals of Sustainable Aviation Fuels serves as both a foundational reference and a forward-looking guide for researchers, policymakers, industry professionals, and students. It underscores that achieving sustainability in aviation depends not only on innovation but also on global collaboration, paving the way toward cleaner skies and a resilient, low-carbon future for air travel.
SAE International’s Dictionary of ADAS and Connected VehiclesR-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 global standards, research, and innovations, this dictionary bridges the gap between theory and application. It fosters interdisciplinary collaboration, supports safer system design, and provides clarity for those engaged in regulatory development or technology deployment. As the pace of mobility innovation accelerates, precise and accessible communication becomes indispensable. SAE International remains committed to advancing global transportation knowledge—empowering professionals to navigate, contribute to, and shape the future of intelligent, connected, and sustainable mobility with confidence and clarity.

Recently Published

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Design and Analysis of a Continuous Drying Process and Equipment for 3D Hollow Polyester Fiber Production2026-99-190311/6/2026
In the production of polyester fibers from recycled polyethylene terephthalate (rPET), the drying and crystallization of plastic bottle flakes are crucial for ensuring the consistency and strength of the finished fibers. Traditionally, rPET production lines still rely on vacuum drum dryers, which have been suffering from issues including agglomeration, uneven heating, and high energy demand. In this work, we developed a novel continuous system that is capable of achieving a total throughput of 1300 kilograms per hour. The design consists of a pulsating fluidized-bed crystallizer and two cylindrical drying towers operating in parallel. Structural performance of the main systems was analyzed using finite element analysis under material load, thermal expansion, and internal air pressure. Airflow behavior and temperature distribution inside the units were studied using Computational Fluid Dynamics (CFD) models, where the flake bed was treated as a porous medium based on experimental bulk density and pressure drop. Results showed that the drying tower maintained a minimum safety factor above 3 under full-load conditions, while the crystallizer also remained well within allowable stress limits. Additionally, flow-field analysis results indicated stable countercurrent airflow, adequate mixing near the inlet region, as well as acceptable axial temperature gradients for moisture removal below 50 ppm. Compared with conventional drum drying, we believe the continuous configuration simplifies operation and reduces heat loss. Our design approach has been combined with analytical calculations on structural and flow simulation, and can be beneficial when applied to similar rPET drying applications.
Wu, Ye, Wu, Tianqi, Ge, Yuchen, Ni, Hongjun, Tan, Linwei, Lv, Shuaishuai
Optimization of Vehicle Windshield Cleaning: A Novel Horizontal Wiper System Based on Ball Screw Drive2026-99-190911/6/2026
Conventional types of wipers are characterized by some consistent disadvantages, such as huge uncleared blind spots (up to 40 percent of the target area), limited wiping functionality, and great dynamic visual interference. Due to the intensive full-field visibility demands of autonomous driving, this paper will introduce a new linear reciprocating wiper that will be driven by a ball screw. In particular, one of the prototypes of such a system is designed based on a Dongfeng heavy-duty truck, according to which the traditional oscillatory movement is converted into a horizontal directional movement by a ball screw. This is powered by a motor of 24 V drive with a worm gear reducer to give the force needed to achieve the horizontal reciprocating motion of the wiper blade assembly over the windshield. For the intelligent control module of the proposed lateral linear wiper system, a special intelligent control system is developed based on the principle of CAN bus communication and multi-sensor fusion. Both a rain sensor and a proportional-integral-derivative (PID) algorithm allow the system to achieve adaptive control of wiper speed and apply to various modes, including intermittent wiping, low-speed wiping, and high-speed wiping.
Dong, Xingzhuang, Hu, Yanxingyu, Li, Jincheng, Xu, Tongqiang, Wu, Liying
Regenerative Braking Control Strategy for Electric Vehicle Based on Improved Ant Colony Algorithm2026-99-191911/6/2026
To address low energy recovery efficiency and inaccurate torque distribution of regenerative braking in electric vehicles, this paper proposes an optimized fuzzy control strategy for regenerative braking based on an improved ant colony algorithm. The design focuses on using the battery state of charge, real-time vehicle speed, and braking intensity as fuzzy control inputs, with the regenerative braking ratio as the output. By employing the improved ant colony algorithm to dynamically optimize the parameters of the fuzzy controller, the accuracy of electric motor braking force distribution is effectively improved; Building on this foundation, the introduction of the Elite Ant Guidance Algorithm enhances the speed of adaptive pheromone updates and dynamic path selection, thereby improving regenerative braking energy recovery efficiency. A MATLAB/Simulink simulation model was developed, and comparisons under the NEDC and UDDS test cycles demonstrated that, compared to traditional fuzzy control strategies, the optimized algorithm increases energy recovery efficiency by 12.8% and 8.1%, respectively, confirming the effectiveness and validity of the improved control strategy.
Yang, Zijiang, Zhang, Wei, Zhang, Jihong, Qi, Ye, Zhang, Zilei
Research on Load Distribution Methods for Planetary Gearboxes Based on Three-Dimensional Tolerance Analysis2026-99-190211/6/2026
Based on the Jacobian tensor and small displacement tensor theories, this paper establishes a three-dimensional tolerance chain analytical model for manufacturing and assembly errors in planetary gearboxes and proposes three methods for managing tolerance accumulation paths. Through tolerance analysis, the cumulative pitch error is quantified and incorporated into the nonlinear dynamic model of the planetary gearbox to determine the time-varying meshing force between the ring gear and planetary gear. This enables calculation of the theoretical load distribution coefficient while accounting for three-dimensional tolerance effects. To validate the model’s accuracy, a dedicated test bench was constructed, and dynamic stresses were measured using a root strain gauge array; the experimental load distribution coefficient was then derived. Comparison of simulation and experimental results shows that the deviation in the load distribution coefficient is only 7.4%, strongly confirming the reliability of the three-dimensional tolerance-dynamics coupled model. This study represents the first closed-loop verification from tolerance propagation to system-level load distribution, providing a theoretical foundation for tolerance design optimization and load distribution performance enhancement in high-precision planetary gearboxes.
Yu, He, Duan, Jiandong, Zhang, Jing, Shi, Wankai
Research on the Influence Pattern on the Coal Rock Cutting Efficiency of Cutting Teeth of the Roadheading Machine2026-99-192011/6/2026
In order to improve the quality of the tunnel cross-section formation and the cutting efficiency of the drilling machine, this paper established a horizontal swing cutting model for the cutting head and conducted a simulation analysis of the spatial movement trajectory of the cutting teeth. A finite element simulation model of the cutting teeth cutting coal and rock was established using the Abaqus/Explicit software. The simulation data were processed and statistically analyzed using MATLAB software. The influence patterns of variable cutting parameters and coal and rock properties on the quality of the tunnel cross-section formation and the cutting efficiency of the drilling machine were studied. Thus, the dual-objective optimal cutting parameters for the automatic cutting control of the drilling machine were determined, guiding the cutting head to perform coal and rock cutting operations. The research on the influence patterns on the coal and rock cutting efficiency of the cutting teeth of the tunneling machine can also provide references for solving problems in the swinging state control of the cutting arm and the correction of the cutting head trajectory.
Qin, Lei, Sun, Changyuan, Li, Xiangshuai, Sun, Xiaolin, Li, Longjie, Lyu, Wenjun
Study on Corrosion of the Vehicle Body Sheet Metal and Exterior Chrome-Plated Parts in Typical Climatic Environments2026-99-190711/6/2026
22
Liu, Peng, Zhuang, Mengmeng, Chen, Junjie, Wang, Jiayu, Wu, Weixing, Ren, Kaixu, Wang, Wentao, Li, Yan
XGBoost–Bayesian Optimization Method for Multi-Blade Centrifugal Fan2026-99-192111/6/2026
To overcome the trade-off between airflow rate and efficiency in a multi-blade centrifugal fan for automotive air-conditioning systems, as well as the low optimization efficiency of conventional simulation- or experiment-based approaches resulting from the large number of impeller design parameters, a surrogate-model-based optimization framework coupled with an intelligent optimization algorithm is proposed for impeller design. Latin hypercube sampling was employed to generate 120 samples within the design space, and an XGBoost model was integrated with a Bayesian optimization strategy to perform the optimization process. Validation results indicate that the prediction error of the surrogate model is less than 3%. Under the final optimized impeller configuration, the airflow rate is increased by 22% at the design operating condition, while the total pressure efficiency is improved by approximately 20%, satisfying the prescribed design requirements.
Yan, Yaqin, Yue, Chen
Failure Mechanism Analysis of Traction Battery Caused By Bottom Collision2026-99-191411/6/2026
As green development has become a global unified strategy, major developed countries in the world have successively announced their ambition to achieve carbon neutrality in this century. The new energy vehicle and traction battery industry has ushered in a high-quality development moment, and the safety of traction batteries has also been widely valued worldwide. As the traction battery is mainly arranged at the bottom of the vehicle, enhancing the operational safety of new energy vehicles necessitates a breakthrough in performance testing for bottom-impact protection. It is essential to develop a robust evaluation methodology that can accurately and efficiently evaluate the extent of damage inflicted on the battery system following a bottom impact or collision. Based on the bottom impact experiment of a typical traction battery pack, this paper studies the damage morphology and damage mechanism of the bottom impact. By integrating finite element mechanical simulations, it provides a detailed analysis of the evolving mechanical states across different zones of the battery pack during the impact event. The findings contribute to enhancing safety protection strategies for traction batteries in bottom impact scenarios and offer crucial support for evaluating the post-impact safety performance of new energy vehicles.
Yan, Pengfei, Han, Liqiong, Chen, Liduo, Wang, Fang, Ma, Tianyi, He, Gaiyun, Liu, Lei
Structural Optimization Design of a Compact Electric Tightening Tool for Narrow-Space Assembly Operations2026-99-190611/6/2026
This paper proposes an electric tightening tool for screw tightening in confined spaces during aero-engine assembly. By combining a gear with a curved rack, the tool converts the motor’s rotary motion into the swing motion of the tool head, thereby addressing torque transmission problems in narrow radial spaces. The tool head features an openable clamping mechanism to facilitate operation. Finite element analysis is used to evaluate the stress distribution and strain characteristics of key components under representative loading conditions. The results show that, under the specified working conditions, the stresses and deformations of the key components remain within reasonable ranges, and the structural strength meets the requirements for use.
Bu, Xin, Feng, Junping, Peng, Shuhao, Yang, Yinfei
Research on Quantification Methods for Nonlinear Forming Length of Ultra-Thin Flat Wires in Flat Wire Motors2026-99-191311/6/2026
Because of the imprecision of length quantification in the manufacturing of flat wire windings for flat wire motors, empirical allowances have long been a common practice in production, which in turn leads to considerable material waste and elevated production costs. This paper presents an integrated solution that fuses material experiments, reverse engineering, simulation iteration and parametric design, realizing accurate prediction and quantitative calculation of winding forming length. First, high-precision elastic-plastic constitutive relationships of flat wires are acquired through room-temperature uniaxial tensile tests. On this basis, reverse engineering is applied to derive the initial geometric characteristics and process motion paths of flat wire windings from the 3D model of finished products. Next, an innovative closed-loop iterative compensation algorithm is constructed, with the forming height of the innermost flat wire layer serving as an absolute reference; finite element simulation is then utilized to dynamically optimize the forming length of each flat wire layer. Finally, a parametric design system with a visual interactive interface is developed, which enables an intelligent workflow where precise cutting lengths and equipment motion curves are automatically generated upon input of key design parameters. Production validation results show that this method drastically reduces the length allowances of flat wires, markedly lowers the production scrap rate, and shortens the process debugging cycle of new motor models by more than 80%.
Li, Wenbin, Zhu, Ye
Research on Lightweighting Wheel Hub for New Energy SUVs Based on ANSYS Workbench2026-99-190411/6/2026
In recent years, the sales volume of new energy vehicles (NEVs) in China has maintained a steady growth trend, and consumers have paid increasing attention to vehicle range. Against this backdrop, the demand for lightweighting of various core components of NEVs has significantly increased. As a key component of automobiles, the wheel hub accounts for a relatively large proportion of the unsprung mass, and its lightweighting is of great significance for improving the driving range and enhancing vehicle performance. In this paper, sunflower and bridge truss are integrated as design elements, and a small-sized new energy sports utility vehicle (SUV) is selected as the reference vehicle model to design a lightweight wheel hub. Creo is used for 3D modeling of the wheel hub, and static stress, radial fatigue, bending fatigue, and modal simulations are performed in ANSYS Workbench. The results show that all wheel hub performance indicators meet the service requirements. Meanwhile, the quality evaluation indicates that the weight of the designed wheel hub is 10.95 kg, which is 3.90 kg lighter than the original wheel hub, representing a weight reduction of 26.3% compared with the original one, thus meeting the lightweighting standards.
Li, Chang
Category-Aware Transformer for Automotive Spare Parts Demand Forecasting2026-99-191711/6/2026
In the modeling process, existing auto parts demand forecasting methods often fail to clearly distinguish structural differences at the demand-frequency level, which results in limited adaptability in real scenarios characterized by sparse demand and a complex category structure. In response to the above problems, this paper proposes a category-aware Transformer framework for auto parts demand forecasting. To explicitly represent demand differences across frequency-based accessory groups and to reduce training bias caused by long-tail sample imbalance, the framework first constructs frequency categories based on statistical demand characteristics and incorporates them into the model as embedding-based structural priors. It then designs a category-perception attention mechanism within the Transformer to guide differentiated modeling of category-related temporal dependencies. At the same time, in order to improve the expression ability of sparse and nonlinear disturbances, this paper introduces a nonlinear mapping module at the prediction end and uses a weighted loss function based on sample distribution to constrain the training target. Experimental results on three real auto-parts demand datasets from Dongfeng Automobile Co., Ltd. show that the proposed method outperforms five benchmark models in terms of RMSE and MAE, with especially strong performance in predicting intermediate-frequency and long-tail parts.
Yi, Yuxuan, Wang, Xiaodong, Yang, Wei, Cai, Yonghua
2026 International Conference on Intelligent Vehicles and Mechanical Engineering (IVME 2026)2026-99-190011/6/2026
TOC
Tobolski, Sue
Anchoring Mechanics Analysis and Structural Optimization of Slip for Pipeline Plugging Robot2026-99-191511/6/2026
Reliable anchoring of slip is essential for preventing axial slippage of pipeline plugging robots under high-pressure plugging conditions. However, excessive tooth penetration may induce furrow formation, local plastic deformation, and hard-contact damage on the inner wall of the pipeline. To balance anchoring capacity and pipe-wall protection, this study establishes a mechanical model for the slip–pipe interaction and analyzes the effects of key structural parameters on slip anchoring performance. The self-locking condition between the slip and slip bowl is first derived, and the minimum equivalent friction coefficient required for stable anchoring is determined. Subsequently, an explicit finite element model of the slip anchoring process is developed to evaluate the influence of bevel angle, tooth profile angle, and curvature radius on the von Mises stress and equivalent plastic strain of both the slip and the pipe wall. Based on the simulation results, an orthogonal parameter optimization scheme is conducted to identify the optimal structural combination. The results show that the optimized slip structure, consisting of a 20° bevel angle, a 90° tooth profile angle, and a 150 mm curvature radius, can effectively reduce pipe-wall damage while maintaining reliable anchoring performance. This study provides a theoretical and numerical basis for the structural design and optimization of anchoring slip in pipeline plugging robots.
Wang, Mingkuan, Zhang, Enchao, Gao, Ang, Shao, Hongyuan, Zhang, Shimin, Zhu, Xiaoxiao
Determination Method of Engagement Position of SSS Clutch in NCB Steam Turbine and Analysis of Its Impact on Shaft System Vibration2026-99-190111/6/2026
An SSS clutch is incorporated into the shaft system of the NCB steam turbine in the gas-steam combined cycle unit. The benefit of this specific design is that the shaft system of the NCB steam turbine can disengage from and engage with the LP rotor during operation, enabling rapid and flexible adjustment between power generation output and heat supply. However, this mode of operation presents some special vibration issues in the shaft system. Analysis of the shaft vibration fluctuations that occur in NCB steam turbines before and after operating mode transitions indicates that this issue arises because the random engagement position of the SSS clutch induces changes in the shaft train’s balance and alignment conditions. Based on the measurement principle of shaft vibration phase and the dual keyphasor measurement system of NCB steam turbines, this paper proposes a novel methodology for determining the optimal engagement position of SSS clutches. This approach establishes quantitative correlations between shaft vibration characteristics and clutch engagement positioning, thereby enabling precise identification of the optimal engagement configuration. The research conclusions provide operational guidance for power plants to optimize shaft vibration in NCB steam turbines.
Song, Tongtong, Song, Yajun, Zhang, Wei, Si, Paiyou, Gao, Yibo
The Dynamic Analysis of the Passenger Car Steering and Braking Stability2026-99-191211/6/2026
During cornering-braking maneuvers, an excessively high braking torque can consume a substantial portion of the available tire-road friction and cause insufficient frictional capacity to satisfy the lateral force demand generated by cornering. As a result, the vehicle may experience stability degradation and, in severe cases, lose control, potentially causing accidents. In this study, an AMESim-based vehicle dynamics model is developed, and yaw rate and sideslip angle are adopted as the primary evaluation indices to characterize steering-braking behavior. Under conditions of a fixed turning radius and initial braking speed, the critical braking force was simulated and analyzed. Additionally, the critical steering wheel angle was examined under conditions of a fixed braking torque and steering speed. The results indicate that if either the braking force or the steering wheel angle exceeds its critical value, the vehicle will lose stability during combined steering and braking.
Ma, Lianglin, Yi, Bingjun, Hu, Yang
Lightweight Design of Car Doors Based on Six Sigma Reliability Optimization2026-99-191011/6/2026
Considering the impact of machining errors in the mass production of car doors, uncertainty factor analysis is introduced to achieve the three-in-one optimization goal of “lightweight-performance-reliability”. This paper takes a car door as the research object. First, its finite element model is established, and analyses of upper torsion, lower torsion, vertical, and belt line stiffness working conditions, as well as modal analysis, are carried out to obtain the door’s stiffness and modal performance data. Taking the thickness of the door sheet metal parts as the design variable, an RBF surrogate model is established. The NSGA-II algorithm is used to carry out reliability optimization with the stiffness under four working conditions, the first-order torsional mode, and the Six Sigma reliability level as constraints, and with the minimization of door mass and maximization of the first-order bending mode as objectives. The research results show that while meeting the reliability requirements and achieving weight reduction of the door, the performance of the door is also improved.
Wei, Yansai, Shen, Yongfeng, Wan, Huawei, Li, Dan
Design of the Loss-Reducing and Dust-Suppressing Device for Cigarette Tumblers2026-99-191111/6/2026
2 mmkg/mg·m−3
Zhang, Lei, Zong, Ze, Liu, Jinlong, Sun, Yanzhao, Zhang, Hanqi, Chong, Chen, Wang, Yuanhui, Yang, Minghao
Impact of ESG Performance on Corporate Value in Low-Altitude Economy Enterprises2026-99-220911/6/2026
Low-altitude economy has already become an important strategic engine for high-quality development as a symbol of new productive forces. The impact of ESG performance on corporate value within the low-altitude economy (a strategic emerging industry), as well as its dual effects and situational specificities, is systematically and empirically examined in this paper using panel data from Chinese A-share listed companies from 2018 to 2023. The results show that the ESG performance of “low-altitude economy” enterprises has a significant impact on company value through two channels: investment in R&D and obtaining more government subsidies. Analyst coverage might be contradictory; too much analyst coverage may even counteract the advantage of ESG performance. Our results also reveal significant heterogeneity patterns. Value-enhancing effects of ESG are greater in low-pollution sectors, technology-based enterprises, non-State-owned companies, and companies located in central and western China. To foster sustainable, high-quality company business, this paper provides suggestions for implementing ESG and conceptually elaborates on how the low-altitude economy influences company ESG performance.
Lv, Xiaonuo, Chu, Yanchang
Adaptive Multi-Agent Path Planning for UAV Formation Missions Based on MAPPO with Curriculum Learning and Graph Attention Networks2026-99-061511/6/2026
In high-end aerospace mission scenarios such as distributed sensing and tactical reconnaissance, path planning for multi-UAV cooperative formation flight has become an indispensable core component of mission systems. However, a key unresolved technical bottleneck remains: how to achieve an optimal balance between strictly maintaining the UAV formation’s preset geometric configuration and realizing collision-free, flexible flight in dynamically changing complex environments. Multi-Agent Reinforcement Learning (MARL) can theoretically solve this coupled optimization problem, but the control instructions generated by the existing mainstream MARL methods often have high-frequency fluctuation issues. Direct deployment of these fluctuating commands on physical UAV hardware will increase alternating stress on mechanical structures, raise the risk of motor overheating, and significantly boost battery energy consumption. These problems directly restrict the engineering application of such methods. To address the above challenges, this paper proposes a robust control framework that accounts for UAV physical characteristics to solve the model mismatch between simulation environments and real flight scenarios during carrier-based UAV deployment. Firstly, to improve the learning efficiency of the algorithm and avoid the cold start problem in the initial training stage, this paper introduces the Adaptive Curriculum Learning (ACL) method. Unlike the fixed-difficulty training mode, ACL can dynamically adjust the environmental complexity based on the real-time task performance of the UAVs. It first allows agents to master basic formation maintenance skills, before training is gradually transitioned to more complex tasks such as navigation in intricate environments. Additionally, considering the computational limitations of the onboard embedded processors of UAVs, this paper only integrates the Graph Attention Network (GAT) into the centralized Critic network of the centralized training and decentralized execution (CTDE) framework. The core advantage of this design is that the system no longer solely relies on distance as the judgment basis but assesses the influence of adjacent UAVs based on the collision risk level. This not only improves the accuracy of value estimation, but also does not compromise the response speed of local control instructions- a feature that is crucial for the real-time requirements of UAV flight control. The proposed method was tested and validated in a high-fidelity simulation environment built in strict compliance with UAV kinematic constraints. The experimental results fully demonstrate its superiority: in dense obstacle areas, the success rate of the task reached 80.4%; compared with the aggressive baseline method, the jerk was reduced by 10.9%. Most importantly, the flight trajectories generated by this framework are smooth and adaptable to actual flight conditions, and the corresponding control commands can be directly deployed on real flight controllers without additional parameter adjustments. This result demonstrates that the proposed framework achieves substantial technical progress in enhancing the autonomous response capabilities of UAV clusters to complex scenarios.
Huang, Xingyu, Zhang, Jiyu, Jiang, Yanshu, Fan, Yuhang
Measuring Industrial Linkages Based on Market Signals: A Study on the Synergy, Leading Role, and Policy Resonance between the New Energy Vehicle and Low-Altitude Economy Industry2026-99-220411/6/2026
This paper aims to empirically examine the dynamic correlation mechanism based on market signals between the two strategic emerging industries, namely the new energy vehicles (NEVs) and the low-altitude economy (LAE), from the perspective of the capital market. In response to the challenges of lagging and missing statistical data of emerging industrial entities, this study innovatively views the stock market indices as a “forward-looking signal” of industry dynamics, and constructs a four-step analytical framework of “long-term trend synergy, short-term fluctuation correlation, long-term equilibrium and causal leadership, and key event resonance”. Based on monthly data from January 2017 to December 2025, the study comprehensively uses methods such as cointegration tests, vector error correction models, and the Granger causality tests for analysis. The results show three main findings. Firstly, the long-term trends of the two industry indices are highly synchronous. Secondly, their short-term market returns show a significant positive correlation (r = 0.637). The cointegration test indicates that there is a long-term equilibrium relationship between the two. The Granger causality test further reveals a bidirectional prediction relationship: the impact of the LAE industry on the NEV industry is more significant (p < 0.05), and the NEV industry also has a predictive effect on the LAE industry (p < 0.1). Finally, these two industries show significant market resonance when facing common industrial policies. This study provides high-frequency evidence from the capital market for understanding the statistical co-movement between these two industries and provides methodological references for the study of the correlation of emerging industry linkages in the period of data scarcity.
Li, Yifan
Aeroseek: Exploring LLM-Enhanced Monte-Carlo Path Planning for UAV Navigation2026-99-061311/6/2026
While Unmanned Aerial Vehicles (UAVs) hold immense potential for transforming the low-altitude economy, developing an agent that combines both intelligence and flexibility remains a significant challenge. To this end, we propose a novel aerial navigation system, Aeroseek, to search for executable paths that coherently transition from cognitive understanding to physical movement, enabling more autonomous and flexible navigation with instruction guidance. Specifically, given a navigation instruction, we follow a fast-andslow thinking procedure inspired by human pilots by breaking down complex decisions into manageable sub-tasks and initiating motion planning immediately upon the completion of each sub-task for realtime movement. By integrating a multi-branch Chain-of-Thought, Aeroseek is capable of combining reasoning with spatial recognition and self-verification to search for robust sub-goals under expected constraints. For sub-goal navigation, we introduce Online Kinodynamic Monte-Carlo Path Planning (OnKi-MCPP), a novel motion planning approach handling both kinodynamic constraints and path search, while ensuring obstacle avoidance for UAVs. Benefiting from the proposed two-tier searching protocol, Aeroseek demonstrates comprehensive capabilities in processing complicated instructions and adapts to dynamic aerial conditions. Extensive experiments demonstrate the advantages of Aeroseek across tasks of varying complexity.
Luo, Guoan, Xu, Tian, Zhou, Jiacong, Wang, Xianyun
Intelligent Unmanned Aerial Vehicle System for Automated Red Pine Cone Harvesting in Dense Forests2026-99-063011/6/2026
This paper describes an intelligent unmanned aerial vehicle (UAV) system that automates red pine cone harvesting in dense forests to mitigate the safety and inefficiency of traditional manual harvesting. The suggested system combines multi-sensor fusion perception, variable-stiffness rigid-flexible composite manipulator, and smart path planning into a single aerial harvesting system. To create a three-dimensional model of the environment and robust cone detection under complicated lighting conditions and extreme canopy occlusion, a heterogeneous sensor suite such as LiDAR, depth cameras, and inertial sensors is used. According to the results of fused perception, collision-free approach paths are created to lead the UAV safely to target cones in limited three-dimensional spaces. One of the significant contributions of this work is the iterative design and optimization of a dedicated harvesting manipulator to be used in aerial forestry operations. A comparative analysis of various structural designs leads to the creation of a rigid flexible composite manipulator with an effective workspace diameter of 1.8 m and adequate stiffness to reduce the effects of the downwash of the UAV rotor. The disturbance-assisted harvesting strategy is adopted by the system, which enables efficient dislodgement of cones without requiring accurate grasping. The proposed technical route is proven to be feasible based on laboratory experiments and initial field tests carried out in real forest settings. It has been experimentally proven that the combined system can effectively perform autonomous harvesting cycles, including target recognition, navigation, and cone dislodgement, thus offering a practical technical paradigm of intelligent and safe forestry harvesting applications.
Shi, Shuaiqi, Du, Yisheng, Li, Xiang, Wang, Weidong
Study on the Severity of Aircraft Ice Protection System Performance in the Icing Envelope2026-99-061111/6/2026
In the process of design and verification of the aircraft ice protection system, a prediction model of ice protection system performance based on Severity Index(IPSI) is proposed, which quantifies the relationship between input and output energy of the ice protection system. In this research, a theoretical calculation method is developed, and the water total collection coefficient and convective heat transfer coefficient on the skin surface were obtained using CFD calculations and rapid neural network prediction methods. The consistency between IPSI and ice protection system performance is verified through an aircraft wing ice protection wind tunnel test. The results show that the lower the slat skin temperature in the ice protection area, the higher the IPSI value, which means the more severe the ice protection system performance. The ice protection performance severity analysis method is carried out for the cases in the CCAR/FAR/CS-25 continuous maximum(CM) envelope of an aircraft, and the IPSI values of each case at some altitudes are calculated, as well as the distribution of the ice protection system performance severity cases in the CM altitude-temperature envelope. The ice protection system performance severity cases are not the highest or lowest atmospheric static temperature in the CM envelope, in which atmospheric static temperature ranges from -8°C to -23°C from low altitude (1500 ft) to high altitude (22000 ft). When the flight speed is constant, and the atmospheric static temperature is gradually reduced, the IPSI value decreases. When the atmospheric static temperature is constant, and the flight speed increases gradually, the IPSI value increases. The influence of water evaporation heat transfer on ice protection performance severity is greater than that of convection heat transfer. The total air temperature for the most severe condition is always 0°C at every altitude. The IPSI calculation model can be used to quickly predict the severity of ice protection system performance in other ice protection areas of aircraft, even wind blades.
Hu, Weixue
Research on Intelligent Switching and Control Strategy of Air-Sea Amphibious WIG Craft Based on Multi-Sensor Fusion2026-99-061911/6/2026
Aiming at the core problems of abrupt changes in dynamic characteristics and poor smoothness in mode switching during the cross-medium operation of amphibious wing-in-ground (WIG) craft, this paper develops an intelligent switching and control system based on multi-sensor fusion. The system integrates measurement data from the Global Navigation Satellite System (GNSS), Inertial Measurement Unit (IMU), and Light Detection and Ranging (LiDAR) to construct a state observation module for mode switching decision-making. On this basis, a fuzzy switching logic centered on flight altitude and sea state characteristics is proposed, and a hybrid control strategy combining Linear Quadratic Regulator (LQR) and Proportional-Integral-Derivative (PID) is designed to realize the smooth transition between water surface and flight modes. Numerical simulations conducted in Python demonstrate that the proposed control scheme can accurately determine the mode switching timing, stabilize the pitch angle fluctuation within ±3° during the transition process, and effectively enhance the ability of WIG craft to operate autonomously and stably of the WIG craft in complex sea conditions.
Zhang, Qihao, Yan, Yifei, Cao, Fengshuo, Xiong, Yueling, Liu, Qing, Deng, Yanpeng, Wu, Peng