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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

Browse All 177

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

EPR202501711/24/2025

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

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

EPR20250159/22/2025

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

Next-gen AI for Aerospace Engineering

EPR20250169/22/2025

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

Small, Mobile, and Autonomous Agricultural Robots

EPR20250128/13/2025

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

Safety Impacts of Active Safety and Driving Automation Features

EPR20250138/13/2025

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

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

EPR20250147/18/2025

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

Product Assurance in the Age of Artificial Intelligence

EPR20250115/21/2025

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

Leveraging Advanced Data Technologies for Smart Traffic Management

EPR20250085/20/2025

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

Edge Artificial Intelligence in Connected, Cooperative and Automated Mobility

EPR20250095/20/2025

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

Space-based Solar Power for Instantaneously Dispatchable Renewable Power on Earth

EPR20250054/24/2025

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

Browse All 16

Passenger Vehicle Systems

Electrified Vehicles

Advances and Current Practices in Mobility

Sustainable Transportation, Energy, Environment, & Policy

Connected and Automated Vehicles

Transportation Cybersecurity and Privacy

Vehicle Dynamics, Stability, and NVH

Transportation Safety

Alternative Powertrains

Materials and Manufacturing

Passenger Cars - Mechanical Systems

Recent Books

Browse All 722

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

B-994_VOLUME17/1/2026

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

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

B-994_VOLUME27/1/2026

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

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

R-5805/29/2026

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

Variable Compression Systems for Future Engines and Fuels

R-5534/30/2026

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

Aerospace Standards Index - 2026

ASIN20262/25/2026

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

Business Reliability Growth for Automotive Engineering, Volume 4

R-5522/17/2026

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

January 2026 AMS Index

AMSJAN-20261/24/2026

Fundamentals of Sustainable Aviation Fuels

R-5471/22/2026

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

SAE International’s Dictionary of ADAS and Connected Vehicles

R-5591/20/2026

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

Safety, ADAS, and Cybersecurity: Vol. 4

EPRCOMPV01202512/29/2025

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SAE TOMORROW TODAY UNPLUGGED - Regulation, Risk, and the Rise of L2++

135757/2/2026

What exactly is L2+? And what about L2++? As the industry embraces these increasingly common terms, is liability slowing the path to Level 3 automation? In this Unplugged episode of SAE Tomorrow Today, join host Grayson Brulte to explore the automation liability concerns keeping OEMs awake at night and why companies like NVIDIA, Mobileye, Qualcomm, Stellantis, and Mercedes-Benz are using terminology that isn't formally defined. As adoption accelerates and regulation struggles to keep pace, one thing is clear: that extra "plus" may just be the industry's way of navigating a self-driving future that's arriving faster than the rules can keep up. Have your own thoughts on this topic? We'd love to hear from you! Share your comments, questions or ideas for future topics with Grayson on Twitter or send them to podcast@sae.org. Follow SAE on LinkedIn, Instagram, Facebook, Twitter, and YouTube.

Patterson, Lori

Helicopter Engine-Rotor System Compatibility

ARP704A (Current)

7/2/2026

This SAE Aerospace Recommended Practice (ARP) recommends a methodology to be used for the design, analysis and test evaluation of modern helicopter gas turbine propulsion system stability and transient response characteristics. This methodology utilizes the computational power of modern digital computers to more thoroughly analyze, simulate and bench-test the helicopter engine/rotor system speed control loop over the flight envelope. This up-front work results in significantly less effort expended during flight test and delivers a more effective system into service. The methodology presented herein is recommended for modern digital electronic propulsion control systems and also for traditional analog and hydromechanical systems.

S-12 Powered Lift Propulsion Committee

ARINC 834A-1 Internet Protocol Based Aircraft Data Interface Function (ADIF)

ARINC834A-1 (Current)7/2/2026

This standard defines the services, the transport layers, and the suggested security mechanisms to enable communication between aircraft systems and an Electronic Flight Bag (EFB). Herein is the definition of a set of protocols and services for the exchange of aircraft avionics data across aircraft networks. The purpose is to define a common set of services to be used to access specific avionics data that will enhance EFB applications. Supplement 1 introduces bi-directional communication between the EFB and FMS. It also enables mutual Transport Layer Security, incorporating client authentication.

Airlines Electronic Engineering Committee

A Transition Curve-Based Design Method for the Recirculation Channel in Internal Recirculating Ball Screws

15-19-03-0011

7/1/2026

Internal recirculating ball screws are widely used as linear motion components in automotive active safety systems, owing to their simple structure and compact size. The recirculation (or deflection) channel is a key feature that distinguishes this type from other ball screw designs. The objective of this article is to investigate this key feature that has been rarely addressed in existing research on internal ball screw. The conventional design method for the recirculation channel involves sweeping the cross-section along the center curve. The center curve is typically defined by various classical equations. These equations are applied in different application scenarios. In automotive braking systems, high loads and strict size constraints place critical demands on both the recirculation channel and its center curve. As a representative best-practice example, the machined channel in the screw is typically employed in this application. This article compares several classical center

Xia, Xinan, Xia, Yanzhe, Zhao, Tina

Optimization of a Halbach array as NVH Mitigation Technique in a Yokeless and Segmented Armature Axial Flux Machine

2026-01-0754

7/1/2026

This paper presents the optimization of a Halbach magnet array applied to an axial flux machine (AFM) in a 12-pole, 18-slots yokeless and segmented armature (YASA) topology, evaluated in the torque–speed characteristics diagram. AFMs offer significant advantages in terms of compact design and high torque density compared to other permanent magnet machine topologies. However, noise, vibration, and harshness (NVH) performance is strongly influenced by cogging torque, electromagnetic torque ripple, and tooth forces. While Halbach magnet arrays are well established in high-performance radial flux machines, only limited research has investigated their influence in AFMs. A Halbach array concentrates magnetic flux on one side of the magnet arrangement, leading to increased air gap flux density and a strongly reduced need of a back iron yoke under the magnets. By using a Halbach array, the magnetic field distribution in the air gap becomes more sinusoidal, thereby reducing harmonic components

Müller, Karsten, Schulz, Fabian, Bremer, Martin, Burkhardt, Yves, De Gersem, Herbert

Experimental Investigation into Port Water Injection on the Transient Behavior of a Heavy-Duty Hydrogen Engine

2026-01-0743

7/1/2026

Hydrogen-fuelled internal combustion engines are a potential carbon-free propulsion solution for high-power applications such as construction machinery and heavy-duty commercial vehicles. However, compared to conventional diesel engines, hydrogen engines exhibit limitations in transient operation and at full load, primarily due to the high reactivity of hydrogen. In spark-ignited hydrogen engines, combustion anomalies represent the main constraint during performance-oriented operation, particularly during transient phases that require mixture enrichment to meet dynamic torque demands. Water injection is investigated in this study as a means to mitigate these limitations. The paper describes the implementation of a port water injection system on a heavy-duty commercial hydrogen engine and evaluates its influence on engine performance with a focus on transient operating conditions. A combustion anomaly evaluation method developed in-house is applied to quantify the effect of water

Schneider, David, Christoforetti, Paul, Kappacher, Peter, Kapeller, David, Schutting, Eberhard, Eichlseder, Helmut, Trapp, Christian

An Application-Oriented Process Model for Selecting Uncertainty Quantification Methods in Machine Learning

2026-01-0773

7/1/2026

Uncertainty quantification (UQ) is increasingly recognized as essential when machine learning (ML) is employed in domains that are safety-relevant, cost-intensive, or legally binding, such as the product engineering of battery electric vehicle (BEV) energy systems. UQ methods aim to estimate the aleatoric, epistemic or both uncertainties associated with the predictions of a machine learning model. However, the landscape of UQ methods is diverse and rapidly evolving, with no single approach proving optimal across all tasks. Consequently, the selection of methods in practice is often driven by experience, constrained by limited comprehensive knowledge, time, and implementation capacity. This paper introduces an application-oriented process model supporting data scientists in selecting UQ methods in ML by adapting the SPALTEN [1] problem-solving methodology and the Algorithm Selection Process Model (ASPM) into an Algorithm Selection Process Model for Uncertainty Quantification (UQ-ASPM

Holderied, Niklas, Hörtling, Stefan, Bause, Katharina, Düser, Tobias

Multiphysical Modeling of a Direct-Cooled Litz Wire Winding for a PMSM Using Surrogate Models

2026-01-0731

7/1/2026

In permanent magnet synchronous machines (PMSMs) ohmic losses occur in the stator windings. Reducing these losses contributes to a higher efficiency and increases the vehicles range. An effective approach to reduce frequency-dependent AC conduction loss is the use of litz wires. In addition, direct cooling helps to reduce DC conduction loss and winding temperatures. Therefore, this work presents a multiphysical modeling approach of a direct-cooled litz wire winding in a PMSM. It combines loss modeling of the winding with novel thermal and hydraulic calculation methods. AC conduction loss due to skin and proximity effect and DC conduction loss are modeled temperature dependent. Scaled-down conjugate heat transfer simulations are used to determine the heat transfer coefficient (HTC) between wires and coolant. Additionally, the pressure drop is derived and converted into parameters for use in a porous media model. The derived parameters are used to generate surrogate models to enable

Blaschke, Wolfgang Maximilian, Mengoni, Leonard, List, Adrian, Kulzer, André Casal

Efficient Powertrain Control Using Signal Decomposition: Utilizing Signal Decomposition Constituents for Knock Detection in Internal Combustion Engines

2026-01-0737

7/1/2026

Knocking combustions in an Internal Combustion Engine (ICE) are engine damaging combustions, and reliable detection of each knocking event is very critical. Engines usually rely on piezo-electric knock sensors to monitor structure-borne noise, which outputs a complex, continuous time series signal. Typically, knock combustions have an additional noise component along with the regular combustion signal, but differentiation of knocking vs non knocking signal (signal to noise ratio) based on visual inspection of this signal alone is challenging and requires computationally intense signal processing such as Fast Fourier Transforms (FFT) or Wavelet transforms followed by manual calibration [1]. In this paper, we propose an alternative to replace traditional knock detection with more reliable time-domain alternative signal decomposition technique. Here we decompose the raw sensor signal into seasonality, trend, and residual, and use the residual component as it is seen to retain

Parulekar, Tushar A., Chilukuri, Sandeep, Mahmood, Haneefa

Experimental Study of Warm-Up And Startability Operations in a Spark Ignition Engine Fueled with Ethanol Gasoline Blends

2026-01-0738

7/1/2026

The mitigation of Greenhouse Gas (GHG) emissions poses a major challenge for the transportation sector, driving the need for renewable fuels. Bioethanol represents a promising fuel for Spark-Ignition (SI) engines, combining a reduced life-cycle CO₂ impact with advantageous combustion properties. However, despite its proven performance under steady-state conditions, the widespread of fuels with high ethanol content is still constrained by significant difficulties during engine cold-start operation. This study aims to experimentally assess the effect of ethanol concentration on cold-start performance and warm-up transient behavior of a Naturally Aspirated (NA), Port Fuel Injected (PFI) SI engine. Warm-up tests were conducted at an operating condition of 2000 rpm engine speed and 20 Nm torque using three fuels with increasing ethanol content: commercial gasoline (E5), E30 and E60. In addition, dedicated startability tests were carried out for E60 and neat ethanol (E100) at different

Falbo, Luigi, Falbo, Biagio, Perrone, Diego, Castiglione, Teresa

Trajectory Tracking Control and State Estimation for Highly Automated Vehicles: A System Framework Implemented on U-Shift II

2026-01-0779

7/1/2026

Trajectory tracking control and vehicle state estimation are core functionalities of highly automated vehicles and must operate reliably under strict real-time constraints as well as in the presence of model uncertainties and limited sensor availability. This paper presents an integrated, real-time capable framework for trajectory tracking control and vehicle state estimation, developed within the UShift II research project and implemented on the highly automated vehicle platform. The framework combines nonlinear model predictive control (NMPC) for trajectory tracking with an extended Kalman filter (EKF) for multi-sensor state estimation within a modular system architecture. The NMPC is based on a vehicle model designed for low-speed automated driving maneuvers and explicitly accounts for actuator constraints. Trajectories are tracked based on local planned reference trajectories while ensuring smooth and physically feasible control inputs for underlying control. The EKF fuses

Fuchs, Sören, Neubeck, Jens, Wagner, Andreas

Representative Driving Cycles for Light Commercial Vehicles Based on Their Usage Profiles

2026-01-0751

7/1/2026

This study describes a methodology for synthesizing representative driving cycles for light commercial vehicles. The focus is on taking the usage profiles of these vehicles into account in the driving cycle synthesis. In this methodology, representative routes are simulated using the example of light commercial vehicles in the craft sector. The results of these simulations are representative speed distributions and representative altitude variations. These results are then used as target values for the actual driving cycle synthesis. Furthermore, measurement runs are carried out with a light commercial vehicle to create a database of real-world driving data. The measurement runs include different urban, rural, and motorway sections and cover a total distance of approximately 510 km. Routes with flatter and more challenging altitude profiles are driven. During the measurement runs, the speed signal and the altitude signal are measured. These signals are then processed and cut into short

Heilmann, Oliver, Grabow, Andreas, Cortès, Sven, Schlick, Michael, Stoll, Tobias, Kulzer, André Casal

Quantifying the Impact of Software Updates through First Time Quality in Automotive Production

2026-01-0786

7/1/2026

Vehicle software updates are released more frequently and in increasingly shorter cycles, which places growing pressure on vehicle quality and final assembly line stability. In production environments, software related issues do not remain limited to the digital domain, since errors introduced by software updates can interrupt flashing and commissioning processes, slow down assembly, and increase rework, thereby directly affecting production throughput. Electronic control units are particularly sensitive to software updates because they are flashed and commissioned during vehicle production under strict timing constraints, and changes to flashing sequences, memory structures, configuration parameters, or function definitions can negatively influence commissioning behavior. This paper presents a novel approach where an established quality measure – First Time Quality (FTQ) – is used to quantify the impact of software updates in the final assembly. By comparing FTQ values from production

El Asad, Aiman, Köhler, Katja, Hahn, Michael, Reuss, Hans-Christian

Production-Ready Automated ECU Calibration Using Residual Reinforcement Learning

2026-01-0780

7/1/2026

Electronic Control Units (ECUs) have played a pivotal role in transforming motorcars of yore into the modern vehicles we see on our roads today. They actively regulate the actuation of individual components and thus determine the characteristics of the whole system. In this, the behavior of the control functions heavily depends on their calibration parameters which engineers traditionally design by hand. This is taking place in an environment of rising customer expectations and steadily shorter product development cycles. At the same time, legislative requirements are increasing while emission standards are getting stricter. Considering the number of vehicle variants on top of all that, the conventional method is losing its practical and financial viability. Prior work has already demonstrated that optimal control functions can be automatically developed with reinforcement learning (RL); since the resulting functions are represented by artificial neural networks, they lack

Kampmeier, Andreas, Badalian, Kevin, Koch, Lucas, Lee, Sung-Yong, Andert, Jakob

Methodology for Developing a Learning-Based Energy Management Strategy for Hybrid Electric Vehicles via Soft Actor-Critic (SAC) Deep Reinforcement Learning Algorithm

2026-01-0774

7/1/2026

The optimization of energy management strategies for hybrid electric vehicles is crucial for minimizing fuel and electrical energy consumption while maintaining the energetic stability of the electrical system. Conventional heuristic, rule-based approaches typically rely on classical optimization techniques and manual calibration by experienced engineers. These methods often suffer from simplified assumptions, sub-optimality, and are increasingly time-consuming given the growing complexity of modern hybrid powertrain architectures. This research proposes a novel methodology for the development of a learning-based energy management strategy (EMS) via deep reinforcement learning (DRL) to transition toward highly automated, data-based, and optimization-based development approaches. The methodology utilizes the Soft Actor-Critic (SAC) algorithm, an off-policy actor-critic method, to train an agent through experiences by interacting with an environment. The environment consists of a

Metzler, Sebastian, Winke, Florian, Jungen, Mario, Schmiedler, Stefan, Hofmann, Peter, Geringer, Bernhard

Methodological Framework for the Derivation of Objective Criteria for Ride Comfort Assessment

2026-01-0765

7/1/2026

In recent years, the automotive industry has faced increasing pressure to accelerate development cycles and reduce costs. Simultaneously, ride comfort standards have risen due to the ongoing integration of autonomous driving functionalities. Consequently, it has become essential to ensure that ride comfort attains a high degree of maturity at the very early stages of the automotive development process. This necessitates the establishment of objective criteria that enable the reliable estimation of subjective ride comfort, utilizing simulation-based assessment methods. This study introduces a methodological framework designed to systematically translate the manufacturer specific subjective perception and assessment of ride comfort into objective descriptions using a dynamic driving simulator. The framework is conceived as a generic approach, enabling the comprehensive application to a wide spectrum of subjective ride comfort phenomena, while being specifically optimized for the

Stroesser, Simon, Zwosta, Tobias, Angrick, Christian, Neubeck, Jens, Wagner, Andreas

Context-Dependent Assessment of Driving Dynamics and User Perception in Automated Driving

2026-01-0757

7/1/2026

As automation advances and occupants transition from active drivers to passive passengers, understanding how automated driving behavior is evaluated becomes increasingly important. While longitudinal and lateral vehicle dynamics are known to influence perceived comfort and safety, it remains unclear to what extent motion–perception relationships remain stable across urban traffic contexts. This study compares two real-world investigations of automated driving: a left-turn maneuver at a signalized intersection on a test track and a roundabout maneuver with a shuttle in public traffic. Both datasets include high-resolution vehicle dynamics and structured subjective ratings. A consistent objectification approach was applied to examine the transferability of motion–perception relationships across contexts. However, differences in vehicle platform, automation level, trajectory characteristics, and study design limit direct comparability and require cautious interpretation. Despite partially

Panzer, Anna, Strenge, Emma, Iatropoulos, Jannes, Henze, Roman

Stakeholder-Oriented Explainability Requirements for Advanced Driver Assistance Systems and Automated Driving Systems: A Structured Analysis

2026-01-0788

7/1/2026

The development and validation of advanced driver-assistance systems (ADAS) and automated driving systems (ADS) are shifting from traditional linear V-model processes toward more iterative engineering cycles. Despite faster iteration, these safety-critical systems remain subject to stringent regulations. Standards and guidance, including UNECE UN Regulation No. 157 and ISO/TS 5083, emphasize traceability, transparency, and explainability throughout development and validation. Nevertheless, as ADAS/ADS are developed and validated in faster, more iterative release cycles, additional stakeholders become involved and new explainability requirements emerge. These requirements vary between stakeholders and across development, validation, and post-market deployment phases, yet they are not systematically captured in the current state of research and practice. Therefore, to ensure that explainability supports rapid iteration, it is essential to identify relevant stakeholders and specify their

Liu, Xuanheng, Bairy, Akhila, Paudel, Bijay, Adolph, Laurenz, Heck, Melanie, Hettich, Lennard, Nägele, Ann-Therese, Rudolf, Korbinian, Bause, Katharina, Düser, Tobias, Schwammberger, Maike

Enhancing Efficiency in Megawatt-Scale EV Charging via Adaptive Multi-Agent Control of DC/DC Converters

2026-01-0769

7/1/2026

The rapid adoption of electric vehicles (EVs) with longer driving range demands high-power charging solutions that are efficient, scalable, and reliable. This work introduces a comprehensive simulation framework for megawatt-scale charging systems, focusing on the integration and control of multiple DC/DC converters. With the primary objective of maximizing overall system efficiency during megawatt-scale charging operations. A multi-agent adaptive control strategy is implemented to dynamically optimize operating points and allocate charging currents across converters in real time so that each participating converter operates at its optimal operating point where the maximum possible efficiency is delivered. This multi-agent adaptive control strategy allocates not only the individual optimal operating points of the multiple DC/DC converters but rather determines the optimal number of participating DC/DC converters at each time instance during the charging session. In addition to that

Salah, Alia, Abu Mohareb, Omar

From Wind Tunnels to an AI-Supported Data-Driven Development Ecosystem

2026-01-0767

7/1/2026

Despite advances in CFD, wind tunnel testing remains indispensable for aerodynamic validation, correlation, and homologation. Increasing configuration complexity, shortened development cycles, and stringent result robustness and documentation requirements demand a shift from isolated facilities to integrated, data-driven ecosystems within the overall development and company-wide test processes. We present a software-centric approach integrating wind tunnel operations into a strategic element of the Digital Thread. By orchestrating test planning, execution, data acquisition, and documentation within a unified framework, experimental data becomes reusable across projects and traceable for compliance and homologation. The interaction between CFD and physical testing is important. Such approach systematically improves simulation models with wind tunnel tests. And CFD results guide efficient test matrix definition. Extended measurement methodologies include automated actuation of active

Jacob, Jan D.

Integrated DC Boost Charger in Post-800V Architecture with Open-End Winding Machine – Magnetic-Domain Modelling and Torque Analysis

2026-01-0739

7/1/2026

Next-generation powertrain architectures proposed within EU Horizon projects adopt operating voltages above 800 V, providing improvements in efficiency as well as reductions in copper usage and system weight. However, post-800 V vehicles must remain backward compatible with existing 400 V and 800 V charging infrastructure, which requires the installation of an additional onboard DC boost charging unit on the vehicle. This paper proposes an integrated DC boost charging solution that reutilizes the open-end winding electric machine and the traction inverter of the electric powertrain, enabling backward compatibility while further reducing system cost and weight. In charging mode, the electric machine is repurposed as a passive inductive component, imposing a strict requirement of stationary operation with zero torque generation, which fundamentally differs from the driving mode characterized by rotor rotation and electromagnetic torque production. Consequently, conventional electric

Wang, Haoran, Kallur-Krishnamoorthy, Rajesh, Neuhaus, Christoph, Andert, Jakob

Numerical Analysis of Directly Injected Hydrogen into a High-Pressure Chamber

2026-01-0745

7/1/2026

Hydrogen Internal Combustion Engines have emerged as an option for decarbonizing heavy-duty transportation. However, injecting high-pressure hydrogen gas into pressurized combustion chambers induces complex compressible flow phenomena, including choked flow and under-expanded supersonic jet structures, which challenge conventional modeling approaches for optimizing engine performance and emissions. This study conducts a numerical investigation of transient hydrogen injection into a high-pressure argon environment, benchmarking a 2D axisymmetric Computational Fluid Dynamics (CFD) model against high-fidelity experimental optical measurements. Utilizing Ansys Fluent with a density-based solver, coupled with the k-ω SST turbulence model and species transport equations, simulations were performed at injection pressures of 6 MPa and 10 MPa into a 1 MPa ambient chamber. The simulation successfully captured fundamental compressible physics, including Mach disk formation and significant

Castilla Batun, Uriel Isaac, Alzahrani, Fahad

Improved Thermal Management for Operating a Battery Electric City Bus under Real Driving Conditions

2026-01-0758

7/1/2026

The goal of reducing global CO2 emissions requires actions especially for the transportation sector. To achieve the goal, electric traction motors are frequently implemented in passenger vehicles, as well as in commercial vehicles like heavy-duty trucks or buses. Particularly electric city buses have the potential to reduce the local emissions in urban areas and provide local exhaust-emission-free mobility. While their number of registrations rises, research focusses on the improvement of the overall system in order to increase energy efficiency. High importance is gained by the thermal management of the whole system. This research investigates a simulative approach to improve the thermal management and therefore the energy efficiency of an electric city bus. The different thermal components of an electric city bus like drive system, battery system and heating, ventilation and air conditioning system (HVAC system) are modelled. Their thermal behavior has been validated in previous

Schäfer, Henrik, Hellberg, Tobias, Meywerk, Martin

Development of a Digital Twin of an Electrical Powertrain in a Testbench Environment for Efficiency Estimations

2026-01-0744

7/1/2026

The aim of this work is to develop a modular, real-time-capable digital twin of an electric powertrain based on machine learning (ML)-based model structures and a systematic, component-oriented architecture with a focus on efficiency estimation in test bench environments. The further goal here is to enable virtual testing, which can be used for frontloading and thus both prevent errors and increase the speed of product development. Based on a comprehensive set of measured and derived test bench data, a multi-stage procedure is implemented that integrates data acquisition, physically informed feature selection, modeling at the component and subsystem level, and hybrid coupling strategies. The digital twin captures inverter, electric machine, and mechanical transmission stages and generates consistent predictions of key variables such as torque, speed, power factors, and subsystem as well as overall drivetrain efficiency. The methodology enables a systematic comparison of black box, dark

Kopp, Lennart, Proksch, Daniel, Ockert, Niels, Karthaus, Carsten, Kley, Markus

Cybersecurity Risk Assessment and Experimental Validation of Automotive Ultrasonic Sensors

2026-01-0782

7/1/2026

Ultrasonic sensors are widely deployed in automotive driver assistance systems for near-range environment perception and provide safety-relevant inputs for functions such as parking assistance and automated parking. With increasing vehicle automation, the integrity and availability of ultrasonic sensor data become more critical, as compromised measurements may lead to incorrect vehicle decisions and hazardous behavior. While prior research has extensively studied physical attacks on ultrasonic sensors, a structured cybersecurity risk analysis in accordance with automotive cybersecurity standards, combined with experimental validation, is largely missing. In particular, the communication interface between ultrasonic sensors and control units has received limited attention despite its relevance as a potential attack surface. This paper presents a systematic security analysis of an automotive ultrasonic sensing system based on a demonstrator setup. The work applies a Threat Analysis and

Gahm, Sebastian, Haller, Jonathan, Kriesten, Reiner

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