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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

Safety Impacts of Active Safety and Driving Automation Features

EPR20250138/13/2025

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

Small, Mobile, and Autonomous Agricultural Robots

EPR20250128/13/2025

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

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

EPR20250147/18/2025

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

Product Assurance in the Age of Artificial Intelligence

EPR20250115/21/2025

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

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

Commercial Vehicles

Materials and Manufacturing

Aerospace

Engines

Fuels and Lubricants

Passenger Cars - Mechanical Systems

Recent Books

Browse All 721

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

Electrification: Vol. 3

EPRCOMPV04202512/29/2025

Manufacturing and Industry 4.0 : Vol. 2

EPRCOMPV06202512/29/2025

Recently Published

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Requirements Extract for AS5127D Aerospace Standard Test Methods for Aerospace Sealants Methods for Preparing Aerospace Sealant Test Specimens

SA-DIG-00002

6/9/2026

This digital standard is a requirements extract of AS5127D Aerospace Standard Test Methods for Aerospace Sealants Methods for Preparing Aerospace Sealant Test Specimens. This file contains a general requirements extraction as well as files that are optimized for use with Doors Classic, Siemens Polarian, and PTC.

A Comprehensive Review of System Risk in Automotive Crash Safety

15-19-02-0010

6/9/2026

Occupant protection has been at the forefront of risk evaluation regarding vehicle crashworthiness design. However, the vehicle is a member of a larger transportation system with varied stakeholders. This article identifies an opportunity for assessing risk in a crash event through emerging safety science paradigms. Conventional Safety I and Safety II frameworks handle well-defined hazards but falter with uncertainty, variability, and emergent behaviors in real crashes. A comprehensive literature review was performed on peer-reviewed research to situate automotive crash safety risk within the Safety III paradigms. The review addresses two questions: (1) How is “risk” defined across the crash safety literature and adjacent safety science domains? and (2) What limitations arise from these definitions in practice? Findings show a dominant probabilistic framing alongside a minority of system-oriented interpretations. Current crash safety practice lacks a coherent, system-level definition

Rye, Patrick J.

Requirements Extract for AS861C Minimum General Standards for Oxygen Systems

SA-DIG-00001

6/9/2026

This digital standard is a requirements extract of AS861C Minimum General Standards for Oxygen Systems. This file contains a general requirements extraction as well as files that are optimized for use with Doors Classic, Siemens Polarian, and PTC.

Rapid Fuel Distribution Prediction in RCCI Marine Engines Using CFD-Informed, Active Learning Framework

2026-37-0017

6/9/2026

Accurate prediction of in-cylinder fuel distribution (FD) is fundamental to reduced-order combustion modeling and emissions prediction yet remains computationally prohibitive with high-fidelity CFD alone. This work develops a CFD-informed machine-learning surrogate for spatial FD in a large-bore diesel engine, based on a Wärtsilä W20 injector and representative engine conditions. A fully coupled injector–spray–engine CFD framework under engine-like RCCI inert conditions determines the needle-lift profile and resolves the combined effects of injector geometry, needle dynamics, and operating conditions on in-cylinder flow, capturing physical phenomena not reproducible by isolated free-spray simulations. A high-fidelity database is generated using Latin Hypercube Sampling, from which FD is extracted at 15 CAD before top dead center within an annular multi-zone (MZ) representation consistent with reduced-order combustion models. A multi-output Random Forest (RF) surrogate, augmented with

Moradi, Jamshid, Salahi, Mahdi, Heidarabadi, Shadab, Andwari, Amin, Konno, Juho, Wik, Christer, Mikulski, Maciej

Low-Voltage Electric Vehicle with a Reconfigurable Powertrain Architecture for Urban and Extra-Urban Mobility

2026-37-0025

6/9/2026

This paper presents a novel concept for battery electric vehicles (BEVs), referred to as the low-voltage reconfigurable electric vehicle (LVREV). The LVREV is designed to bridge the gap between L- and M-class vehicles by adopting a <60 V multi-phase powertrain combined with a swappable battery system, maintaining the overall vehicle mass below one ton. This configuration enables adaptable driving range, optimized energy consumption in urban environments, and enhanced safety. The LVREV features two distinct operating modes. Frugal mode is intended for urban use and employs a smaller battery pack to maximize efficiency and reduce vehicle mass, while Dual mode is tailored for longer extra-urban trips through the use of a dual-battery configuration. The key innovations of the LVREV concept include a reconfigurable vehicle architecture capable of meeting both urban and extra-urban mobility requirements, thus providing a highly versatile transportation solution. In addition, the low-voltage

Tramacere, Eugenio, Favelli, Stefano, Galluzzi, Renato, Tonoli, Andrea

Combined EGR-Air Dilution Effects on Performance, Combustion and Emissions of a Single-Cylinder Spark-Ignition Direct-Injection Hydrogen Engine

2026-37-0009

6/9/2026

Hydrogen internal combustion engines (H2ICE) have emerged as a promising solution for decarbonisation of the transport sector, due to low cost and potential for rapid deployment. However, abnormal combustion and high nitrogen oxide (NOx) emissions limit stoichiometric operation, making dilution strategies essential. While lean combustion has been widely studied, combined dilution strategies of air and exhaust gas recirculation (EGR) require further investigation. This work presents experimental results from a boosted 0.5-litre spark-ignition direct-injection single-cylinder research engine equipped with high-tumble ports and cooled high-pressure EGR. Relative air–fuel ratios (lambda) of 1 to 3 and EGR rates of 0 to 40% are evaluated at 5, 10, and 15 bar of indicated mean effective pressure (IMEP) at 2000 rpm to assess effects on net indicated thermal efficiency (nITE), combustion, and emissions. A peak nITE of 43.5% is achieved at 10 bar IMEP, λ = 2.5, and 30% EGR, which can be

King, Aidan, Islam, Reza, Pickering, Simon, Yuan, Hao, Mudge, Henry, Giles, Karl, Goyal, Harsh, Jones, Peter, Akehurst, Sam, Esposito, Stefania

Evaluation of Flamelet-Based Combustion Models for Hydrogen-Ammonia Spark-Ignition Engines

2026-37-0027

6/9/2026

Besides the electrification of the transport sector, the growing interest in alternative fuels for internal combustion engines represents a promising pathway to effectively decarbonize transportation over the coming decades. Predictive combustion models implemented within CFD frameworks are a critical tool to guide the design of next-generation internal combustion engines fuelled with alternative fuels. Accurate prediction of the combustion heat release process is influenced by multiple interacting parameters, requiring combustion models that can reliably adapt to variations in fuel chemical properties and operating conditions. In this study, two well-established combustion models considered to model combustion development in Spark-Ignition engine, namely the Extended Coherent Flame Model (ECFM) and the G-equation model, are compared to assess their capability to adapt to changes in fuel chemical composition. Both models, based on the flamelet formulation are deliberately tested beyond

Sola, Riccardo, Baratta, Mirko, Misul, Daniela, Rousselle, Christine, BREQUIGNY, Pierre, Colin, Olivier

Comparative Toxicological Assessment of Exhaust Emissions from Modern Low-Emission Passenger Vehicles

2026-37-0005

6/9/2026

As vehicle technologies evolve toward electrification and advanced aftertreatment, understanding the biological implications of their exhaust emissions remains essential. This study presents a harmonized comparative toxicological assessment of five Euro 6 vehicles representing gasoline, hybrid, plug-in hybrid, compressed natural gas (CNG), and diesel technologies. Vehicles were tested under realistic driving conditions on a chassis dynamometer. Diluted exhaust was delivered directly to human lung epithelial cells (A549) using a controlled air–liquid interface (ALI) exposure system. Solid and total particle number emissions were measured, and deposited particle mass was estimated from size-resolved distributions and deposition efficiency. Vehicles equipped with particulate filtration showed lower solid particle emissions overall, while differences between gasoline particulate filter-equipped vehicles indicated that hybridization can further influence emission levels. Diesel operation

Tsakonas, Georgios, Stamatiou, Rodopi, Lazou, Antigone, Samaras, Zissis, Elihn, Karine

Nitrogen-Based Emissions from Ammonia Combustion in a Heavy-Duty Spark Ignition Engine

2026-37-0032

6/9/2026

Ammonia (NH3) is a carbon-free fuel with strong potential for spark-ignition (SI) engine applications. However, the engine can produce complex nitrogen-based emissions not adequately captured by conventional engine models. This study consolidated the results of experimental and numerical studies on the use of neat NH3 combustion in a heavy-duty compression-ignition engine converted to spark-ignition operation, first for a sweep of equivalence ratios (ϕ) from 0.7 to 1.0, and another from varying the energy substitution ratio of methane (CH4)– NH3 blends from neat CH4 to neat NH3 at constant ϕ = 0.8. Two 0-D two-zone SI engine models with detailed chemistry (called “original” and “extended”) predicted engine thermodynamics and emissions. While the original model reproduced in-cylinder pressure and combustion phasing, it failed to capture the effect of fuel composition or operating condition on NO trends, both under- and over-predicting them for neat NH3 and CH4-rich operations. An

Trujillo Grisales, Juan, Saenz Prado, Stefany, Alvarez, Luis F., Akkerman, Vyacheslav, Dumitrescu, Cosmin E.

Passenger Car Powertrain for Voltages above 800V

2026-37-0020

6/9/2026

The EU funded innovation project High-Voltage fast-charging Efficient electric vehicle Powertrains (HiVEP) develops innovative technologies for mass-market electric vehicles (EVs) by advancing architectures operating above 800 V. These architectures integrate silicon carbide (SiC)-based power electronics, rare-earth-free electric machines with active winding reconfiguration, high C-rate batteries, and optimized thermal management systems. HiVEP aims to enable fast charging in less than ten minutes, reduce energy consumption by at least 25%, extend the driving range by 20%, and cut system costs by up to 20% in volume production. This article deals in detail with the project objectives, the methodological approach, and the expected key innovations, as well as the technical, environmental, and social impacts. The discussion situates HiVEP within the European research and innovation landscape, emphasizing its role in accelerating adoption of sustainable mobility solutions.

Schernus, Christof, Nada, Shady, Neuhaus, Christoph, Ewald, Jens, Swierc, Daniel, Kallur-Krishnamoorthy, Rajesh, Vasiliadis, Harilaos

Investigation of Influential Parameters on the Integrated Hydrogen Argon Power Cycle

2026-37-0012

6/9/2026

This study investigates hydrogen combustion in an argon–oxygen environment for argon power cycle application using computational fluid dynamics. The numerical framework, developed based on previously validated model, is applied to examine the influence of key operating parameters on combustion efficiency and indicated efficiency under constant cycle pressure conditions. A parametric analysis is conducted to evaluate the effects of excess oxygen ratio, argon rate, start of injection, and injector discharge coefficient on ignition characteristics, combustion efficiency, and engine performance. The results indicate that less fuel injection improves combustion efficiency but leads to a significant reduction in engine load. Increasing the argon rate enhances engine thermal efficiency, primarily due to the higher specific heat ratio of argon, which improves the thermodynamic efficiency of the cycle. However, elevated argon concentrations significantly reduce combustion efficiency because of

Chitsaz, Iman, Ahammed, Sajid, Kakoee PhD, Alireza, Salahi, Mohammad Mahdi, Andwari, Amin, Ahmad, Zeeshan, Hyvonen, Jari, Mikulski, Maciej

Design-Driven Sustainability of Automotive Components: A Comparative LCA from Conventional to Metal and Composite Additive Manufacturing

2026-37-0037

6/9/2026

The increasing pressure to decarbonize manufacturing systems is pushing industry beyond conventional lightweighting strategies toward material and process paradigms, capable of delivering functional performance with radically lower environmental impact. In this context, polymer-based composite Additive Manufacturing (AM) offers an underexplored yet highly promising pathway for sustainable production of load-bearing components. This study presents a preliminary comparative cradle-to-gate Life Cycle Assessment (LCA) of a Formula SAE brake pedal, assessing the environmental transition from conventional sheet metal fabrication and finishing operations of Aluminum 7075-T6 to additive manufacturing solutions, with specific focus on Carbon-Fiber-Reinforced Polymer (CFRP) composites. Two topology-optimized designs, respectively for Powder Bed Fusion (PBF) in AlSi10Mg and Material Extrusion (MEX) in Polyethylene Terephthalate Glycol with Carbon Fiber (PETG-CF) are compared to conventional

Dalpadulo, Enrico, Russo, Mario, Apté MD, Raphaëlle, Leali, Francesco

Enabling Flexibility Services through Interoperable V2X Infrastructures: Advanced Modeling and Operational Validation in the FLEXV2X Project

2026-37-0024

6/9/2026

The integration of Electric Vehicles (EVs) as active grid resources represents a pivotal shift towards decarbonization. However, the implementation of effective Vehicle-to-Everything (V2X) services faces technical challenges regarding interoperability, predictive management, and battery health preservation. This work presents a comprehensive system design and research methodology developed within the framework of the FLEXV2X project, aimed at addressing interdependencies within a unified bidirectional charging ecosystem. The proposed scientific framework addresses two complementary timescales. At the device level, the study details the modelling and optimization of bidirectional converters, focusing on control algorithms designed to ensure robust dynamic response and efficiency. Building upon this hardware foundation, the paper describes a system-level optimization strategy. By employing open-source cyber-physical modelling, the architecture simulates complex EV-grid interactions. This

Lutzemberger, Giovanni, Barater, Davide, Ceraolo, Massimo, Fera, Cesare, Leaver, Ian, Pasini, Gianluca

Predictive Modelling of NO _x and Unburned Hydrogen Emissions in a Direct-Injection Hydrogen Spark-Ignition Engine

2026-37-0007

6/9/2026

Hydrogen is emerging as a compelling energy carrier for future transportation due to its potential to enable fully decarbonised operation and near-zero tailpipe pollutant emissions. Realising this potential in reciprocating internal combustion engines requires a detailed understanding of the complex interactions governing hydrogen combustion and emissions formation. In this context, physics-based reduced-order emission predictive modelling offers a powerful means to accelerate the development and optimisation of hydrogen-fuelled engines by enabling rapid evaluation of operating strategies without the need for extensive experimental campaigns. This study investigates the simulation of nitrogen oxides (NOx) and unburned hydrogen (uH2) emissions from a 0.5L spark-ignition direct injection single-cylinder research engine within a 1D-0D simulation approach. For NOx prediction, a simplified kinetic mechanism is coupled with both a 0D two-zone combustion model and a thermal multi-zone in

Malfi, Enrica, De Felice, Massimiliano, Esposito, Stefania, Ribnishki, Aleksandar, King, Aidan, Akehurst, Sam, Jones, Peter, Goyal, Harsh

Development of a Diesel Combustion System for Next-Generation Heavy-Duty Engines Using a Synergistic Analysis-and-Testing Approach

2026-37-0004

6/9/2026

Regulators and policymakers have introduced increasingly stringent limits on tailpipe CO₂ and pollutant emissions to accelerate the decarbonization of heavy-duty vehicle applications. The development of innovative propulsion technologies — such as advanced combustion systems, low-friction reciprocating components, and improved aftertreatment solutions — combined with hybridization and the adoption of alternative fuels (e.g., biogas, HVO, green hydrogen), is a key pathway for meeting future emission and GHG targets. In this study, advanced combustion systems were developed for a 13-liter diesel engine for heavy-duty truck applications, with the objective of meeting forthcoming Euro VII regulations while maximizing thermal efficiency. The combustion system architecture—including open-bowl geometry with high aspect ratio, injector nozzle with wider spray opening angle, and reduced swirl ratio—was optimized using a Machine Learning–algorithm trained on high-fidelity 3D CFD combustion data

Belgiorno, Giacomo, Centini, Maria Pia, Pezza, Vincenzo, Cozza, Ivan F., Pesce, Francesco C., Vassallo, Alberto, Colombo, Giovanni, Gallo, Alessandro, Mirzaeian, Mohsen, Borg, Jonathan

Alcohol-Based Energy Carriers in Transportation: Status, Standards, and Outlook

2026-37-0042

6/9/2026

The global transport sector accounts for approximately 30 % of total final energy consumption and 15.9 % of worldwide greenhouse gas (GHG) emissions, with road transport alone accounting for the largest share at 11.8 %. Decarbonizing this sector requires energy sources that combine scalable generation from renewable sources with compatibility with various modes of transportation and existing infrastructure. Methanol and ethanol emerge as promising alternative energy carriers that can leverage existing logistics infrastructure while reducing dependence on fossil fuels. Global methanol production reached 112 million metric tons, and global ethanol production totaled approximately 93.5 million metric tons in 2024, compared to more than 2 billion metric tons of gasoline and diesel produced annually. The review assesses production pathways and cost trajectories for both alcohols, evaluates fuel requirements across multiple transport modes, including passenger vehicles, light- and heavy-duty

Fitz, Patrick, Fellner, Felix, Rößlhuemer, Raphael, Härtl, Martin, Jaensch, Malte

Can Large Language Models Enable Sustainable Driving Behavior? A Study on Large Language Model-Based Eco-Driving

13-07-02-0006

6/9/2026

Large language models (LLMs) have shown remarkable capabilities for perceiving driving environments and making interpretable, logical decisions for autonomous driving. However, their potential for more comprehensive driving strategies, especially concerning energy efficiency, remains underexplored. Most existing studies primarily focus on driving safety, which may inadvertently increase energy consumption. To address this issue, this study explores the use of LLMs as high-level controllers to jointly optimize driving safety and energy efficiency. A textual prompt is designed for the LLM, incorporating few-shot examples that describe scenarios, states, and actions. The LLM processes the scenario and state prompts describing the surrounding traffic environment. It generates a high-level control signal, which is then translated into low-level vehicle motion commands in a high-fidelity traffic simulator with realistic physics, vehicle dynamics, road slopes, and network topology

Wang, Haoyu, Li, Zhenning, Wang, Siying, Zhou, Zijing, Zhang, Xiang, Yang, Zhifeng, Ou, Shiqi (Shawn), Qi, Hao

A Novel Looped-Freezing Mean Detached Eddy Simulation (DES) Based Approach to Evaluate Underhood Cooling Performance of Commercial Vehicles

02-19-03-0018

6/9/2026

A novel looped-freezing mean approach based on Detached Eddy Simulation (DES) approach is developed in context of assessing underhood cooling performance in heavy-duty vehicles. The method involves computing a temporally averaged flow field from DES simulations, which is then frozen and used by the energy solver to predict temperature distributions. This process is iteratively repeated until a statistically steady-state temperature field is achieved. It is demonstrated that traditional DES approach demonstrates superior accuracy in capturing forced convection heat transfer compared to the Reynolds-Averaged Navier–Stokes (RANS) method. The validation against experimental data for flow over a heated sphere at a Reynolds number of 105 shows that DES yields Nusselt numbers with better correlation than RANS. However, it is observed that DES approach captures unsteady flow features that introduce temporal fluctuations in heat transfer. In the context of underhood cooling evaluations where

Holay, Sarang, Sankar, Hari, Dixit, Pritish, Singh, Ramanand

Experimental Investigation on Cold Start and Warm-Up Phases for an Ethanol Fueled SI Engine

2026-37-0031

6/9/2026

The reduction of Greenhouse Gas (GHG) emissions represents a key challenge for the transportation sector, requiring the adoption of renewable fuels capable of ensuring both environmental benefits and compatibility with existing internal combustion engine technologies. In this context, bioethanol emerges as a viable solution for Spark Ignition (SI) engines, offering a low life-cycle CO₂ footprint and favorable combustion characteristics. Nevertheless, despite its well-known advantages under steady-state operation, the widespread use of high-ethanol-content fuels is still limited by critical issues during engine cold start. The aim of this work is to experimentally investigate the influence of ethanol content on cold-start behavior and idle warm-up transient operation of a Naturally Aspirated (NA), Port Fuel Injected (PFI) SI engine. The experimental campaign was carried out under idle conditions using four fuels with increasing ethanol content, namely commercial gasoline (E5), E30, E60

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

Effects of Engine Geometries on the Combustion Characteristics of a Heavy-Duty Hydrogen Spark-Ignition Engine

2026-37-0046

6/9/2026

For heavy-duty applications, hydrogen (H2) internal combustion engines offer a practical solution for future transportation. However, the influence of cylinder head flow characteristics and piston geometry on lean H2 combustion remains insufficiently understood. This study presents a comprehensive computational investigation of three engine configurations characterized by distinct in-cylinder flow dynamics: mild swirl and tumble (Engine a), strong tumble (Engine b), and strong swirl (Engine c). High-fidelity three-dimensional computational fluid dynamics simulations were performed for both port-fuel injection (PFI) and direct injection (DI) strategies. The impact of piston geometry was evaluated by comparing the baseline piston with a flat piston, while the spark timing was optimized to achieve favorable combustion phasing. Combustion and NOx formation were modeled using a G-equation-based combustion framework incorporating diffusive-thermal instability effects and a validated in-house

Liu, Xinlei, Menaca, Rafael, Cenker, Emre, Silva, Mickael, Qahtani, Yasser A., Pei, Yuanjiang, Turner, James W.G., Im, Hong G.

Engine Thermal Management Strategies for Emissions Reduction during Real Driving Tests

2026-37-0036

6/9/2026

Thermal management in internal combustion engines (ICEs) strongly affects fuel consumption and pollutant emissions, especially during engine warm-up. Particularly, the oil temperature is strictly related to the organic efficiency of the vehicle: in the early phase of a driving cycle, the low temperature produces a high-viscous oil, which increases friction losses and increases fuel consumption, with respect to full thermal regimated oil. Usually, the oil and coolant thermal behaviours are interconnected, thanks to a coolant/oil heat exchanger in the engine. In this study, a prototyped electrical coolant pump has been applied and integrated in a small SUV vehicle, replacing the original mechanical unit. An off-board experimental campaign allowed a complete hydraulic characterization of the cooling system, including thermostat operation, and led to a physically based correlation between flow rates and pressure drops in each branch. Based on these results, the pump was designed and

Di Battista, Davide, Di Bartolomeo, Marco, Cipollone, Roberto

Investigating the Potential of Two Individually Controlled Injectors per Rotor for a Direct Injection Hydrogen Wankel Engine

2026-37-0008

6/9/2026

Hydrogen-fueled rotary engines offer a promising zero-emission solution for compact commercial powertrains. This study reports experimental results from the further development of a naturally aspirated, direct-injection hydrogen rotary engine by HTM. Initial applications, such as an airport baggage tractor, demonstrated technical feasibility but revealed pre-ignition that limited maximum torque. To address this, mixture formation was investigated using an experimental setup with two independently controlled injectors feeding a single rotor injection channel. The effects on operating behavior, efficiency, and NOx emissions were evaluated. The dual-injector configuration significantly shortens injection duration and improves spatial distribution of hydrogen within the combustion chamber. Enhanced mixture control suppresses pre-ignition and enables higher mean effective pressure. Systematic variation of injection timing under representative steady-state conditions also shows potential for

Endres, Jonas, Beidl, Christian, Herold, Tim, Lavall, Philipp, Schmidt, Marvin, Hofmann, Silas, Kahl, Jonas

Numerical Simulation of Spark-Ignited Flame Kernels towards Prospective Application to Hydrogen SI Engines

2026-37-0015

6/9/2026

The ongoing energy transition demands the decarbonization of the transport sector, for which the use of premixed hydrogen in spark-ignition (SI) engines appears very promising. However, modeling the combustion of the lean hydrogen/air mixtures required for safe, efficient, and low-NOx engine operation involves multiple open issues. Correct prediction of flame kernel initiation and growth is a difficulty that hydrogen shares with hydrocarbon fuels, while properly accounting for the instabilities that characterize lean hydrogen flames is an additional demanding task. In this work, a 1D kernel expansion model of general validity recently proposed by the authors is implemented into OpenFOAM, an open-source 3D CFD software package, to enable numerical simulation of expanding spark-ignited flame kernels. Firstly, the OpenFOAM framework is presented focusing on XiFluid, its flame propagation model based on a regress variable whose evolution depends on the laminar flame speed. Then, the

Dotteschini, Enrico, Pretto, Marco, Giannattasio, Pietro, Gadalla, Mahmoud

On Natural Gas Combustion Split into Diesel Like Architecture of a Compression Ignition Engine Retrofitted for Spark Ignition Operation

2026-37-0029

6/9/2026

In commercial areas that no longer favor diesel engines, such as Europe, it might be interesting to convert an existing compression ignition engine to the spark ignition operation and to use natural gas (NG) because of its advantages: availability of still abundant supplies worldwide and environmental benefits compared to conventional liquid fossil fuels. This paper first presents experimental results on NG combustion inside such a converted engine with diesel-like architecture dedicated to light-duty vehicles and passenger cars. Particularly, our study carried out at the engine test bed revealed that in certain operating points (low speed and load, stoichiometric mixture and rather high spark advance), the combustion is split into two distinct events (first, a fast combustion inside the cylinder and piston bowl and then, a slower combustion occurring outside the bowl-in combustion chamber, in other words, in the squish region), which is not specific to the standard spark ignition

Clenci, Adrian F., Popa, Robert, Berquez, Julien, Iorga-Siman, Victor, Magheru, Catalin, Punov, Plamen, Niculescu, Rodica

Automated Design Sustainability Evaluation Framework: A CAD-Integrated Tool for Real-Time Costing and LCA in Automotive Engineering

2026-37-0044

6/9/2026

As the automotive industry faces increasingly rigorous environmental regulations and an approaching obligation for Digital Product Passports (DPPs), incorporating sustainability metrics into the early design phase has become a necessity. Traditionally, Life Cycle Assessment (LCA) and manufacturing cost estimation are performed during or after the design phase using specific methods and tools, resulting in costly iterations and delayed decision-making. This paper introduces a preliminary computational tool that combines 3D CAD and spreadsheet software via VBA integration. The framework automates the generation of an “Extended Bill of Materials” by extracting geometric and manufacturing data directly from CAD models. This tool’s classification logic is a key innovation that intelligently processes CAD features to identify component categories, such as sheet metal, machined parts, or plastic injections. This automated recognition allows the framework to implement specific algorithmic

Guadagno, Maurizio, Cecconi, Leonardo, Berzi, Lorenzo, Delogu, Massimo

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