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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
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
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
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
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
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
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
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
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
Automated Vehicles and Infrastructure Enablers: Dedicated LanesEPR20250074/24/2025
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
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
Connected and Automated Vehicles
SAE International Journal of Connected and Automated Vehicles
Transportation Cybersecurity and Privacy
SAE International Journal of Transportation Cybersecurity and Privacy
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
Aerospace
SAE International Journal of Aerospace
Engines
SAE International Journal of Engines
Materials and Manufacturing
SAE International Journal of Materials and Manufacturing
Fuels and Lubricants
SAE International Journal of Fuels and Lubricants
Passenger Cars - Mechanical Systems
SAE International Journal of Passenger Cars - Mechanical Systems

Recent Books

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Variable Compression Systems for Future Engines and FuelsR-5534/30/2026
Variable Compression Systems for Future Engines and Fuels 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
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
January 2026 AMS IndexAMSJAN-20261/24/2026
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
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
Safety, ADAS, and Cybersecurity: Vol. 4EPRCOMPV01202512/29/2025
Electrification: Vol. 3EPRCOMPV04202512/29/2025
Infrastructure Enablers for Automation: Vol. 4EPRCOMPV02202512/29/2025
Automated Vehicles: Development, Testing, and Validation: Vol. 4EPRCOMPV03202512/29/2025

Recently Published

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Advanced Composites Prepreg - Nominal 250 °F (121 °C) Cure - 12K Tow Carbon Fiber and Epoxy Resin, Plain Weave FabricAMS3914B (Current)5/15/2026
The intent of this specification is for the procurement of plain weave fabric epoxy prepreg product with 250 °F (121 °C) cure for aerospace applications; therefore, no qualification or equivalency threshold values are provided. Users that intend to conduct a new material qualification or equivalency program must refer to the production quality assurance section (see 4.3).
AMS P17 Polymer Matrix Composites Committee
Rating Air-Conditioner Evaporator Air Delivery and Cooling CapacitiesJ1487_202605 (Current)5/15/2026
The purpose of this SAE Recommended Practice is to establish uniform test procedures for measuring and rating air delivery and cooling capacity of truck and off-road self-propelled work machines used in earth moving, agriculture, and forestry air-conditioner evaporator assemblies. It is the intent to measure only the actual cooling capacity of the evaporator. It is not the intent of this document to rate and compare the performance of the total vehicle air-conditioning system.
Truck and Bus Windshield Wipers and Climate Control Comm
Standard Practice for Force Protection and SurvivabilitySAE1008A (Current)5/15/2026
According to SAE6906, Force Protection and Survivability (FPS) is the Human Systems Integration (HSI) domain that facilitates system operation and personnel safety during and after exposure to hostile situations or environments. Force protection refers to all preventive measures taken to mitigate hostile actions against Department of Defense (DoD) and Department of Homeland Security (DHS) (e.g., U.S. Coast Guard, Customs and Border Patrol, Immigration and Customs Enforcement, etc.) personnel. Survivability denotes the capability of the system and/or personnel manning the system to avoid or withstand man-made hostile environments without suffering an abortive impairment of his/her ability to accomplish its designated mission. Damage due to enemy or fratricidal action, or even equipment failure, will endanger the warfighters' well-being and place them into a life-threatening situation.
G-45 Human Systems Integration
Rolling Element Bearing Hardness TestARP5483/2B (Current)5/15/2026
This method outlines the standard procedure for testing the hardness of bearing components. Bearings covered by this test method shall be any rolling element bearing used in airframe control.
ACBG Rolling Element Bearing Committee
Permanent or Fixed Place Flight Deck Head-Up DisplaysARP4102/8B (Current)5/15/2026
This SAE Aerospace Recommended Practice (ARP) provides criteria for the design, installation, operation, and training aspects of head-up display (HUD) systems in transport category aircraft, with emphasis on pilot interface and operational requirements. The recommendations apply to permanently installed (including stowable) HUDs that display primary flight information, including those integrating enhanced flight vision system (EFVS) imagery. The intent is to ensure HUDs are designed and used in a manner that improves pilot situational awareness and flight technical performance across all phases of flight, up to and including low-visibility operations. While technical design standards (optical performance, hardware specs, etc.) are defined in documents like ARP5288 and AS8055, this document focuses on pilot usage considerations and human factors. HUD systems addressed here are typically designed to support a fail-passive operational concept applicable to Category III instrument approach
S-7 Flight Deck Handling Qualities Stds for Trans Aircraft
FITTING, BULKHEAD END - THREADED COUPLING, RIGID, SELF-BONDING, DESIGN STANDARDAS5948A (Current)5/15/2026
G-3, Aerospace Couplings, Fittings, Hose, Tubing Assemblies
Advanced Composites Prepreg - Nominal 250 °F (121 °C) Cure - Carbon Fiber and Epoxy Resin, Unidirectional TapeAMS3960B (Current)5/15/2026
The intent of this specification is for the procurement of carbon fiber epoxy prepreg product with 250 °F (121 °C) cure for aerospace applications; therefore, no qualification or equivalency threshold values are provided. Users that intend to conduct a new material qualification or equivalency program must refer to the production quality assurance section (see 4.3).
AMS P17 Polymer Matrix Composites Committee
Constructing a Development Assurance Plan for Integrated SystemsAIR6218A (Current)5/15/2026
This SAE Aerospace Information Report (AIR) supplements ARP4754B/ED-79B by identifying the crucial elements to be considered when constructing the development assurance plans described in Section 3 (Development Assurance Planning) of ARP4754B/ED-79B for integrated systems. Section 4.6.4 of ARP4754B/ED-79B expands the aircraft/system integration and verification activities by emphasizing testing during integration to investigate for unintended behaviors. However, guidelines are needed for planning that are specifically aimed at the aircraft level and at integrating across system functions and boundaries. Until such guidelines are more comprehensively provided, this AIR presents a collection of lessons learned from past certification programs involving integrated systems, and as such it may be considered in conjunction with Sections 3 and 4 of ARP4754B/ED-79B. ARP4761A/ED-135 elaborates the safety activities by adding processes and methods such as the Aircraft or System Functional Hazard
S-18 Aircraft and Sys Dev and Safety Assessment Committee
FITTING END, 24° CONE, FLARELESS, FLUID CONNECTION, DESIGN STANDARDAS5863A (Current)5/15/2026
G-3, Aerospace Couplings, Fittings, Hose, Tubing Assemblies
Research on Performance Prediction Methods for Centrifugal Refrigeration Compressors in Data Centers2026-99-07255/15/2026
As the “digital brain” and core foundational support for the development of intelligent transportation and connected vehicles, the performance of data centers directly determines the operational capability of intelligent transportation systems. In the process of advancing the vehicle-road-cloud collaborative architecture, the demand for high-performance computing power in data centers has experienced explosive growth. The substantial increase in computing tasks has posed severe challenges to thermal management, making efficient and reliable cooling systems an indispensable core component. Centrifugal compressor water-cooling units are the mainstream cooling solution for large-capacity scenarios, and their design optimization is crucial for improving the energy efficiency and performance of the entire cooling system. This paper proposes a one-dimensional performance prediction method for centrifugal compressors based on an empirical loss model, and realizes the iterative calculation of
Zhu, Minhao, Jiang, Bin, Li, Min, Zeng, Zihui, Gu, Yunhui
International Conference on the New Energy and Intelligent Vehicles2026-99-07005/15/2026
TOC
Tobolski, Sue
Crowd Counting Network for Risk Early Warning in Exhibition Scenarios2026-99-07055/15/2026
As a densely populated public place, exhibitions feature spatial layouts with multi-area linkage and instantaneous crowd flow mutations. Thus, developing a crowd flow early warning system adapted to exhibition dynamics is a key focus at the public safety and smart exhibitions to avoid risks like local congestion-induced stampedes. In general, two core challenges in exhibition crowd counting: 1) Key dynamic gathering information is hidden in high frequency components, but no correlation mechanism between frequency components and scene has been established; 2) Instant crowd gatherings cause high-frequency local density mutations, leading to time delays and spatial ambiguity of dynamic signals. To solve these, we propose a novel Crowd Counting Network for Risk Early Warning in Exhibition Scenarios with two core modules: 1) A bidirectional feature filtering module optimizes frequency information through low-frequency suppression to reduce redundancy and high-frequency activation to
Zhang, Jin, Zhang, Wanyue, Yuan, Jingjing, Chen, Zhen, Gu, Dazhi
Linear Trajectory Planning of Hydrogen Storage Tank with Unequal Polar Holes2026-99-07185/15/2026
In this paper, the design and process research of uniform filling linear trajectory for filament wound hydrogen storage tank with unequal polar holes are carried out. Firstly, by optimizing the slip coefficient, the winding angles of the left and right heads are smoothly and continuously transitioned to the cylindrical section. We study the necessary conditions for achieving the central angle of uniform filling, and calculate the tangent points of the trajectory line based on the continuous fraction principle. Meanwhile, the slip coefficients at the left and right ends that satisfy stable winding and uniform covering are determined. Based on the equal contour constraint conditions, we analyze the motion trajectory equation of the four-axis winding machine and convert it into the corresponding machine code for actual winding operations. Experimental results show that stable winding of fibers on the surface of the unequal-polar-hole mandrel is achieved, and uniform filling and winding
Chen, Baosen, Fu, Jianhui, Cao, Xuewen, Yu, Libin
Research on a Lightweight Assistive Manipulator for Insulated Short-Stick Live-Line Operations in Distribution Networks2026-99-07325/15/2026
With the continuous economic development and the rapid advancement of urbanization, the stable operation of distribution networks has become a key factor in ensuring the reliability of power systems. In response to the problems of high risk, high labor intensity, and low efficiency in distribution network operations, this paper designs an auxiliary operation mechanical arm for distribution networks. This auxiliary operation mechanical arm is fixed on the working bucket of an insulated boom truck. The main body is a two-degree- of-freedom SCARA mechanical arm that moves in a plane, and the end is connected to a three-degree-of-freedom end effector through a flange to cooperate in completing the pitch, deflection, axial feed, and clamping of insulated rods, achieving coarse positioning in the plane and precise positioning of the target. The auxiliary mechanical arm operation platform adopts a fully insulated design. The platform is made of glass nylon material, and the edges are rounded
Wang, Jingjie, Chen, Zhenning, Feng, Yu, Wu, Shaolei, Zhang, Yuxi, Dou, Hang, Wang, Wei
Driving Behavior Heterogeneity Identification with Action Patterns Relationship2026-99-07525/15/2026
Identifying driving heterogeneity is critical for enhancing the strategy learning capabilities of autonomous driving systems, as well as improving their safety and efficiency. This research proposes a novel driving heterogeneity identification framework. The framework consists of three core processes: action phase extraction, action relationship modeling, and behavior heterogeneity identification. First, a rule-based segmentation method is employed to systematically decode and interpret the inherent variations in human driving behavior. Subsequently, an action relationship modeling method is introduced to characterize the temporal relations between the acquired action phases. Finally, to mitigate the inaccurate identification caused by the sparse distribution of critical driving events in long-sequence data, a semantic encoding method is applied to remap the driving behavior space. Experimental results on the Lyft level-5 dataset validate the effectiveness of the proposed framework
Yin, Hui, Zhang, Qinyao, Li, Xiaojian, Mo, Hangjie
Adaptive Speed-Regulated Impedance Control for Robotic Ultrasound Scanning: Reducing Constant-Force Tracking Errors2026-99-07515/15/2026
Robotic ultrasound scanning technology is a research hotspot in the field of medical imaging, and can achieve standardized and high-precision data acquisition. However, large force tracking errors occur during scanning, especially in complex human tissues, which can severely degrade image quality and diagnostic accuracy. Therefore, we propose an adaptive speed-regulated impedance control strategy to address this challenge, which innovatively combines the spline real-time interpolation and impedance control for constant force tracking. Firstly, the discrete ultrasound scanning paths are fitted to generate a smooth and synchronized interpolation trajectory. Then, the speed of the reference trajectory is adjusted in real time based on the Taylor formula to reduce the force tracking error. Experimental verification was conducted, and the results showed that the force tracking error increases with the increase of trajectory speed. In addition, at high speeds (e.g., 10 mm/s), the mean
Min, Kang, Zhang, Le, Shi, Yudong, Fang, Jin, Mo, Hangjie, Li, Xiaojian
Diffusion Framework with Cross-Modality Fusion Perception for Autonomous Driving in Urban Traffic2026-99-07495/15/2026
End-to-end autonomous driving in urban environments faces three core challenges. First, camera and LiDAR sensor heterogeneity causes cross-modal perception inconsistencies and sensor fusion instability. Second, diffusion models suffer from training instability due to scale variance and distribution changes, which limits generalization. Third, traditional trajectory decoders lack structured interaction with semantic elements, thereby undermining planning rationality. To address these issues, CMFPNet introduces an integrated framework with three key modules. The HGCF-Backbone integrates LiDAR and camera features using channel focus, deformable cross-focus, and state space modeling to enhance semantic alignment. The NST module maps physical trajectories to normalized space, employing truncated diffusion sampling for stable generation in just 2–4 steps. The NDA models trajectory generation as a semantic narrative, utilizing a six-stage semantic attention flow incorporating BEV context
Qu, Yanwei, Mo, Hangjie
Design of a Modular High-Power High-Repetition-Rate Semiconductor Pulsed Laser Power Supply2026-99-07165/15/2026
μsμs
Huang, De, Lu, Jiawei, Yang, Zhiqing, Xv, Ziyi, Xing, Hui
Research on Waste Heat Recovery Characteristics of Electric Drive System in Hybrid Electric Light-Duty Trucks2026-99-07225/15/2026
Aimed at the high energy consumption for battery heating of a light hybrid truck in low-temperature winter, this paper proposes an optimized battery thermal management scheme based on motor waste heat and PTC cooperation. Then it verifies its energy-saving performance based on multi-condition simulation and testing. Taking the constant-speed condition at -5°C as an example, firstly, the accuracy of the battery thermal management model is verified by comparative simulation and test. Then, based on the verified model, the battery thermal management model is simulated under typical winter conditions at 0°C and 5°C. The analysis results show that, when the battery temperature is raised from the initial state to a certain target, the energy consumption of the motor waste heat-assisted PTC heating scheme is obviously less than that of PTC heating. The energy saving rates are 33.137% at -5°C, 32.45% at 0°C, and 32.56% at 5°C, respectively. The research results have proved that the effective
Meng, Shun, Zhang, Dong, Zhang, Yu, Zhang, Chunyu, Yao, Mingyao, Qiu, Liang, Qian, Yejian
Semantic-Driven Mathematical Modeling and Adaptive Refactoring for Logistics Optimization: A Language-Model Orchestrated Optimization Pipeline2026-99-07505/15/2026
While large language models (LLMs) offer a convenient natural language interface for logistics optimization problems, it remains challenging to directly generate reliable mathematical models and executable code from unstructured text requirements. LLMs tend to produce invalid constraints or syntactically incorrect code. In addition, traditional logistics optimization methods lack the flexibility to adjust warehouse rules or operational goals without manual expert intervention. To address these issues, we propose LOOP (a Language-Model Orchestrated Optimization Pipeline), which automatically translates natural-language requirements into optimization algorithm code while retaining the rigor of classical models and solvers. LOOP leverages task-specific agents to construct accurate mathematical models and adopts a difference-driven code generation approach. First, it synchronizes model changes into executable code via semantic mapping and ensemble difference analysis. Second, it
Ding, Ruiqing, Li, Qianying, Li, Xiaojian
Local LLM Based Knowledge Graph in Power Domain Using Graph-Schema Reasoning and Retrieval-Augmented Generation2026-99-07565/15/2026
In recent years, large language models (LLMs) have shown great potential in many domains. However, their application in professional domains is often limited by problems like erroneous outputs and hallucinatory responses. Therefore, we present a framework that combines knowledge graphs (KGs) with local LLMs. The framework utilizes the factual information in KGs to improve the initial output of the LLMs, thereby reducing the factual errors in inference. In this paper, a domain knowledge graph is automatically constructed using textual data from the power industry. The KG contains 149,732 entities and 139,280 relationships. The proposed method is tested on EleQA, a public Q&A dataset of electricity regulations. Compared with the LLM-only baseline, the knowledge-graph-enhanced model achieves an improvement of 32.42%. Moreover, the framework shows strong adaptability and performs well on various LLMs. Our framework improves the accuracy and utility of large language models in the power
Chen, Ruiduan, Lin, Shizhong, Shao, Zhan, Cui, Shicheng, Li, Xingyu, Luo, He
Pattern-Guided Implicit Sentiment Analysis: Knowledge-Augmented Prompting with Aspect-Sentiment Joint Extraction for Automotive User Feedback2026-99-07535/15/2026
Implicit sentiment analysis of automotive user feedback is crucial for understanding user opinions. Automotive user feedback often express opinions in an indirect way and are accompanied by a dense array of industry terms. Therefore, without costly fine-tuning, both aspect identification and sentiment analysis are rather difficult. We propose a Pattern-Guided pipeline for implicit sentiment analysis to achieve the joint extraction of aspect and sentiment. This pipeline first performs Pattern Anchoring, mapping colloquial expressions and slang to the standardized vehicle component knowledge system. Then, using Knowledge-Augmented Prompting, these domain rules are injected into well-designed prompt templates. In this pipeline, the large language model (LLM) is applied to output JSON records suitable for comprehending, including aspects, sentiments, confidence levels, and brief reasons. To enhance stability, we employ an improved prompt and consistency-driven confidence fusion to generate
Chang, Gengjia, Deng, Zuxing, Ma, Aonan, Yao, Jiangqi, Li, Xiaojian, Li, Ling
Optimal Power Sharing and Voltage Restoration in DC Microgrids Based on Adaptive Droop Control2026-99-07075/15/2026
The stable operation of islanded DC microgrids is conditioned by two essential objectives. One is to maintain the bus voltage at its nominal value, and this can ensure system stability. The other is to achieve cost-effective power allocation among distributed generation units, which guarantees economic efficiency. These two objectives are often conflicting. Adding droop control to the voltage and current dual closed-loop control can achieve primary current sharing. However, it inevitably introduces steady-state voltage deviations on the DC bus and results in inflexible or not optimal power sharing. To resolve these inherent limitations, this paper proposes a innovative distributed secondary control strategy. The method is designed to meet both requirements within a unified framework. In the primary control layer, it uses adaptive droop gains to optimize power distribution in real time based on changing load requirements which enables distributed generation units to achieve cost
Sun, Wei, She, Dunjun, Yu, Jinzhu, Yuan, Weibo, Peng, Bo, Zheng, Yingchun
Time Series Causal Discovery Based on Data Augmentation and Causal Validation2026-99-07035/15/2026
Causal discovery within time series is crucial for revealing the actual causal mechanisms in dynamic systems, and it has major impacts in various fields like economics, healthcare, and climate science. Even though it’s important, accurately figuring out causal relationships from observational temporal data is still quite a difficult task. Traditional Granger causality based methods are often limited by noise sensitivity, large amount of data, and the inability to distinguish between real causality and false correlation caused by hidden factors. In order to solve these problems, this paper presents CausalAugVeri, which is a new algorithm that cleverly mixes data augmentation with causal verification to make causal discovery more solid and precise. This work has three main points: First, we carefully check that using convolutional data augmentation techniques can greatly improve how well time series predictions work, giving a steadier base for detecting Granger causality. Second, the
Yang, Jing, Chen, Xiaotao, Qin, Xuanli, Xu, Xianjun, Hu, Zhangxiang
Secondary Control Method for Parallel DC-DC Converters under FDI Attacks Based on Sliding Mode Observer2026-99-07085/15/2026
Currently, with the continuous development of electric vehicles, DC microgrids have attracted widespread attention due to their flexible access methods and high energy transmission efficiency. However, since the distributed secondary control of DC microgrids relies on information exchange through communication networks, false data injection (FDI) attacks on these networks may cause control algorithms to fail, leading to voltage deviations, output current imbalance, and in severe cases, system instability. This study focuses on DC microgrids based on parallel DC–DC buck converters and proposes a distributed secondary control strategy based on a sliding mode observer to address FDI attacks. By treating the system's FDI attack signals as an extended state, an extended sliding mode observer is designed to track the attack signals. Based on the observed attacks, a control algorithm is proposed that compensates the control inputs through the observer, ensuring proportional sharing of bus
Sun, Wei, Chen, Jing, Yu, Jinzhu, Yuan, Weibo, Peng, Bo, Lin, Fei