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Announcements for SAE Mobilus

Vertical Flight Society Technical Papers - Coming Soon to Mobilus

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

Important Update – Accessibility Enhancements on SAE Mobilus

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

SAE AI Chat — Update and What's Next

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

SAE International Digitization and AI Policy

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

Welcome to the new SAE Mobilus®

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

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Recent SAE Edge™ Research Reports

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

EPR202501711/24/2025

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

Next-gen AI for Aerospace Engineering

EPR20250169/22/2025

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

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

EPR20250159/22/2025

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

Small, Mobile, and Autonomous Agricultural Robots

EPR20250128/13/2025

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

Safety Impacts of Active Safety and Driving Automation Features

EPR20250138/13/2025

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

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

EPR20250147/18/2025

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

Product Assurance in the Age of Artificial Intelligence

EPR20250115/21/2025

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

Edge Artificial Intelligence in Connected, Cooperative and Automated Mobility

EPR20250095/20/2025

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

Leveraging Advanced Data Technologies for Smart Traffic Management

EPR20250085/20/2025

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

Automated Vehicles and Infrastructure Enablers: Dedicated Lanes

EPR20250074/24/2025

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

Latest Journal Issues

Browse All 16

Passenger Vehicle Systems

Electrified Vehicles

Advances and Current Practices in Mobility

Sustainable Transportation, Energy, Environment, & Policy

Connected and Automated Vehicles

Transportation Cybersecurity and Privacy

Vehicle Dynamics, Stability, and NVH

Transportation Safety

Alternative Powertrains

Commercial Vehicles

Aerospace

Engines

Materials and Manufacturing

Fuels and Lubricants

Passenger Cars - Mechanical Systems

Recent Books

Browse All 720

Variable Compression Systems for Future Engines and Fuels

R-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 - 2026

ASIN20262/25/2026

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

Business Reliability Growth for Automotive Engineering, Volume 4

R-5522/17/2026

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

January 2026 AMS Index

AMSJAN-20261/24/2026

Fundamentals of Sustainable Aviation Fuels

R-5471/22/2026

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

SAE International’s Dictionary of ADAS and Connected Vehicles

R-5591/20/2026

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

Safety, ADAS, and Cybersecurity: Vol. 4

EPRCOMPV01202512/29/2025

Manufacturing and Industry 4.0 : Vol. 2

EPRCOMPV06202512/29/2025

Electrification: Vol. 3

EPRCOMPV04202512/29/2025

Infrastructure Enablers for Automation: Vol. 4

EPRCOMPV02202512/29/2025

Recently Published

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BOLT, MACHINE - DOUBLE HEXAGON EXTENDED WASHER HEAD, DRILLED, PD SHANK, SILVER PLATED, NICKEL ALLOY, UNS N07718, 185 KSI MIN, .2500-28 UNJF-3A

AS3251E (Current)

5/20/2026

E-25 General Standards for Aerospace and Propulsion Systems

Remover, Temporary Coating Alkaline Type, Water Base

AMS1388B (Historical)

5/20/2026

This specification covers two types of thickened, water base temporary coating remover in the form of an alkaline liquid.

AMS J Aircraft Maintenance Chemicals and Materials Committee

INSPECTION GAGE, FOR AS81790/1 CONNECTORS AIRCRAFT EXTERNAL ELECTRIC POWER

AS81790/3A (Current)5/20/2026

AE-8C1 Connectors Committee

SAE TOMORROW TODAY - Can Airports Become Innovation Labs?

135685/20/2026

What if your airport was a living laboratory for innovation? Listen in as we sit down with Brian Cobb, Chief Innovation Officer at Cincinnati/Northern Kentucky International (CVG) Airport, to explore how CVG operates as a "city within a city," deploying emerging technologies to improve passenger experience, strengthen operational resilience, and reimagine the modern airport. Discover how CVG is advancing innovation through real-time TSA wait times, robotics testing, and the growing role of AI, autonomy, and cybersecurity. Get even more insight as Brian takes the stage as keynote speaker at the 25th anniversary of AeroTech(R) this June. He'll explore what's next for aviation innovation, from connected robotics and autonomous workflows to the standards and cross-industry collaboration needed to make it all work safely. To learn more and register, visit sae.org/events/aerotech. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast

Patterson, Lori

FITTING, ADAPTER, EXTERNAL THREAD, SPHERICAL, 37° FLARED TO INTEGRAL WELD RING

AS6231B (Current)

5/20/2026

SCOPE IS NOT AVAILABLE.

G-3, Aerospace Couplings, Fittings, Hose, Tubing Assemblies

Remover, Temporary Coating Alkaline Type, Water Base

AMS1388A (Current)

5/20/2026

This specification covers two types of thickened, water base temporary coating remover in the form of an alkaline liquid.

AMS J Aircraft Maintenance Chemicals and Materials Committee

Rapid Modeling of Transient Thermal Systems through Ensemble Parameter Estimation Applied to the Lumped Parameter Linear Superposition Method

2026-01-5034

5/19/2026

Efficient thermal modeling is essential for the design and reliability of power electronics systems, particularly under fast transient operating conditions. Building upon prior formulations of the Lumped Parameter Linear Superposition (LPLSP) method, this work introduces an ensemble parameter estimation framework that enables reduced-order thermal model generation from a single transient dataset. Unlike the earlier implementation that relied on multiple parametric simulations to excite each heat source independently, the proposed approach simultaneously identifies all model coefficients using fully transient excitations. Two estimation strategies namely two-stage decomposition and rank reduction are developed to further reduce computational cost and improve scalability for larger systems. The proposed strategies yield models with temperature-prediction errors within 5% of CFD simulations while reducing model development times from O(103 s) to O(100 s)–O(101 s). Once constructed, the

Padmanabhan, Neelakantan

J1798/1_202605 (Current)

5/19/2026

This SAE Recommended Practice provides for common test and verification methods to determine lead acid and nickel metal hydride electric vehicle battery module performance. The document creates the necessary performance tests to determine (a) what the basic performance of EV battery modules is, and (b) if battery modules meet minimum performance specification established by vehicle manufacturers or other purchasers. Specific values for these minimum performance specifications are not a part of this document.

Battery Standards Testing Committee

A Novel Stiffness Prediction Model of Rolling Lobe Air Springs Considering Irregular Piston Contour Geometry: Development and Experimental Validation

15-19-02-0006

5/18/2026

An accurate air spring model is essential for the design and optimization of air suspension systems to achieve superior performance. This article presents a novel stiffness model for a rolling lobe air spring (RLAS), formulated using stiffness characteristic parameters. Prediction models for these parameters, including effective area and its change rate, as well as effective volume and its change rate, are derived through geometric analysis, based on polynomial fitting of the irregular piston contour. The local contour cone angle of the piston is determined by differentiating the polynomial function, capturing the geometry-dependent variation across the profile. Additionally, a nonlinear hysteresis model for the rubber bellows is integrated, combining a Berg friction component and a Kelvin-Voigt fractional derivative viscoelastic model to represent the amplitude- and frequency-dependent behavior of the RLAS. The proposed model is parameterized through quasi-static and dynamic bench

Xia, Xiaojun, Zhang, Hong, Zou, Yi, Ye, Lei, Lu, Yi, Chen, Rui, Zou, Hantong, Wang, Yang

Limit Stability Control for Corner Module Vehicles Based on Hierarchical Hybrid Game

10-10-04-0032

5/18/2026

Corner module vehicles (CMVs) achieve the decoupling of driving, braking, steering, and suspension, significantly enhancing vehicle handling potential, but under extreme operating conditions, the interactions between actuators severely constrain the improvement of vehicle handling performance. In order to mitigate conflicts between subsystems and enhance vehicle handling stability, a hierarchical hybrid game–based limit stability control method for CMVs is proposed in this article. Taking into account the handling potential of subsystems under limit conditions, a Stackelberg leader–follower game is designed by first designating Direct Yaw moment Control (DYC) as the leader and Active Rear Steering (ARS) as the follower. Subsequently, the DYC–ARS and Active Suspension System (ASS) were constructed into a non-cooperative game system, and the Nash equilibrium solution was solved through iteration. The lower-level controllers, respectively, established a tire force distribution model that

Peng, Jinxin, Xiao, Feng, Ke, Yuan, Jin, Liqiang

The Aerodynamic Performance of Lotus EMEYA

15-19-02-0007

5/18/2026

In this article, the aerodynamic features of two configurations of Lotus EMEYA are introduced. The first configuration includes a fixed air dam and an active rear spoiler (ARS) assembly, which has two active blades in order to obtain the aerodynamic drag and lift performance required. The second configuration includes an Active Air Dam (AAD) assembly and a gurney flap mounted on the ARS in order to achieve more aggressive aerodynamic performance. The aerodynamic bandwidths and the lift balances of both configurations are demonstrated, and the strategies of active aero components of the two configurations are also introduced. Through active aerodynamics and control strategies, the two configurations of Lotus EMEYA can meet the performance requirements of users in different scenarios.

Yuan, Qingpeng, Yang, Lei, Li, Bo, Ni, Li, To, Chi Hin, Xiong, Zhenfeng

Advanced Composites Prepreg - Nominal 250 °F (121 °C) Cure - 12K Tow Carbon Fiber and Epoxy Resin, Plain Weave Fabric

AMS3914B (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

An Anthropomorphic Trajectory Optimization Research for Autonomous Vehicles Considering Omnidirectional Dynamics

2026-99-0733

5/15/2026

The rapid development of autonomous driving technology has brought emerging opportunities to optimize the omnidirectional vehicle driving performance. However, its compliance with driving habits directly determines its social acceptance. Therefore, how to balance consistency between performance improvement and driving habits has become an important bottleneck restricting the rapid promotion of autonomous driving technology. Manual driving vehicles mostly focus on the safety of both longitudinal and lateral movements, and cannot cope with the vertical movement, let alone the performance of economy, comfort, and efficiency. In this context, this paper proposes an anthropomorphic trajectory optimization method incorporating vehicle omnidirectional dynamic characteristics and corresponding driving habits. Firstly, this paper explores vehicle dynamic characteristics in longitudinal, lateral, and vertical directions, and reveals the coupling effect of motion states during driving

Liao, Peng, Zhang, Defeng, Ning, Donghong, Li, Sijia, Wang, Tao

Research on Performance Prediction Methods for Centrifugal Refrigeration Compressors in Data Centers

2026-99-0725

5/15/2026

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

Local LLM Based Knowledge Graph in Power Domain Using Graph-Schema Reasoning and Retrieval-Augmented Generation

2026-99-0756

5/15/2026

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 Feedback

2026-99-0753

5/15/2026

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

Secondary Control Method for Parallel DC-DC Converters under FDI Attacks Based on Sliding Mode Observer

2026-99-0708

5/15/2026

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

Design of a Novel Intelligent Monitoring Platform for Low and Medium Altitudes

2026-99-0739

5/15/2026

This paper presents the design of a novel intelligent monitoring platform for low and medium altitudes, aiming to offer a new solution for the development of intelligent equipment operating in this airspace. Current monitoring tasks are primarily performed by fixed-wing and multi-rotor UAVs, but these platforms face significant technical bottlenecks in flight endurance and monitoring precision. This research aims to address these deficiencies. The platform is based on a small-scale unmanned airship featuring a semi-rigid, hybrid lift-body structure. Improvements were made upon the traditional ellipsoidal hull; the hull profile was optimized using a geometric superposition method, introducing an aerodynamic camber line with a maximum camber (m) of 4% to enhance aerodynamic performance at small angles of attack. In terms of its energy system, the platform is powered by a purely electric energy system composed of solar panels and batteries; solar energy is used during the day, while

Song, Ziang, Gao, Wenxuan, Cao, Xiaochuan, Zheng, Xing, Zhao, Chong

Cabbage Cleaning Device Based on Fischertechnik Model

2026-99-0734

5/15/2026

This article focuses on the problem of high labor cost, low processing efficiency and poor automation of the existing equipment in the postharvest processing of Chinese cabbage. It will design and produce an automated Chinese cabbage processing method called Smart Fresh Pack. Root removal, leaf removal, washing, loading, weighing, packaging and labeling functions were integrated, and smart dexterous intelligence was applied to core concepts and this can be used in the bulk production scenario of supermarkets in the city and countryside Compared with traditional assembly line equipment, obvious advantages in terms of structure, function and processing capacity: Key innovations include: Low-pressure air jet cleaning replaces water washing, which prevents a second contamination and weighing error due to surface moisture; pneumatic gripper and multi-DOF robotic arms combine to package and dynamically weigh simultaneously, streamlining these tasks; machine vision relies on an SSD

Chen, Yuhui, Zhang, Yixuan, Ruan, Jia, Zhu, Huayun, He, Lianzheng, Zhao, Ping

Design of a Modular High-Power High-Repetition-Rate Semiconductor Pulsed Laser Power Supply

2026-99-0716

5/15/2026

μsμs

Huang, De, Lu, Jiawei, Yang, Zhiqing, Xv, Ziyi, Xing, Hui

International Conference on the New Energy and Intelligent Vehicles

2026-99-0700

5/15/2026

TOC

Tobolski, Sue

Research on Waste Heat Recovery Characteristics of Electric Drive System in Hybrid Electric Light-Duty Trucks

2026-99-0722

5/15/2026

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

Optimal Power Sharing and Voltage Restoration in DC Microgrids Based on Adaptive Droop Control

2026-99-0707

5/15/2026

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 Validation

2026-99-0703

5/15/2026

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

Research on a Lightweight Assistive Manipulator for Insulated Short-Stick Live-Line Operations in Distribution Networks

2026-99-0732

5/15/2026

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

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