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Analysis of simulators for designing network architecture in Wireless Sensor Network(WSN) applications2025-28-0338To be published on 11/06/2025
Recent advancements in energy-efficient wireless communication protocols and sensor technologies have led to the development of wireless sensor network (WSN) applications in diverse industries. Wireless sensors are crucial in both smart factory applications and in introducing autonomy in harsh environment agricultural operations, where traditional wiring systems have higher chances of failure. These WSNs are generally designed using Bluetooth Low Energy (BLE), ZigBee, and Wi-Fi communication protocols, depending on the range and reliability requirements of the application. The design of these WSN applications also depends on several factors. First, the environment in which devices operate varies with the industries and products they are employed in. Second, the energy availability for these devices is limited, so higher signal strength for transmission and retransmission significantly reduces the lifetime of these nodes. Finally, the size of networks is increasing, making scheduling
Periwal, Garvit, Koparde, Prashant, Sewalkar, Swarupanand
Transformative Deep Learning for Image Colorization with Machine Learning-Based Classification2025-28-0317To be published on 11/06/2025
Imagine a user opening a technical manual, eager to troubleshoot an issue, only to find a mix of stark black-and-white illustrations alongside a few color images. This inconsistency not only detracts from the user experience but also complicates understanding. For technicians relying on these documents, grayscale graphics hinder quick interpretation of diagrams, extending diagnostics time and impacting overall productivity. Producing high-quality color graphics typically requires significant investment in time and resources, often necessitating a dedicated graphics team. Our innovative pipeline addresses this challenge by automating the colorization and classification of existing grayscale graphics. This approach delivers consistent, visually engaging content without the extensive investment in specialized teams, enhancing the visual appeal of materials and streamlining the diagnostic process for technicians. With clearer, more vibrant graphics, technicians can complete tasks more
Khalid, Maaz, Akarte, Anurag, Kale, Aniket, Rajmane, Gayatri, Nalawade, Komal
Challenges & approaches for Cost modelling in off highway electric vehicles2025-28-0212To be published on 11/06/2025
The electrification of off-highway vehicles presents a complex landscape of challenges, particularly in the realm of cost engineering for motors. These challenges stem from technological complexities, use of specialty materials and processes, economics of scale, and operational factors, each requiring careful consideration to ensure accurate and efficient cost modeling. The lack of standardized cost data for specialty materials poses a significant barrier to accurate cost engineering. Furthermore, the cost of key materials and components, such as electrical steel and permanent magnets, can fluctuate due to supply chain disruptions, material shortages, introducing uncertainty into cost projections. The economies of scale play a crucial role in cost engineering for off-highway electrification. Many off-highway vehicles are produced in lower volumes compared to on-road vehicles, which can result in higher unit costs for electric motors and other. In this paper, we delve into the primary
Chauhan, Shiv, Padalkar, Bhaskar
Design IQ2025-28-0327To be published on 11/06/2025
Weight and cost are critical parameters in any new product development program, influencing aspects such as homologation and efficiency. Traditionally, tracking these parameters at the machine, subsystem, and module levels involves a manual, time-consuming process. This reactive approach often delays the program and hampers the productivity of design engineers. These challenges can be managed with an automation and simulation. WCOSAP automates the extraction of weight details, identifies outliers, calculates module-level impacts, and predicts future weight changes. This proactive tool eliminates repetitive manual work, enhances data accuracy, and supports dynamic updates. By integrating real-time data and predictive models, WCOSAP enables sound decision-making and proactive weight control during the design phase, ultimately improving efficiency and reducing the need for part revisions. This paper discusses the development, implementation, and benefits of the WCOSAP tool, highlighting
Patil, Vivek, Sahoo, Abhilash, ballewar, Sachin, Chidanandappa, Basavaraj, Chundru, Satyanarayana
Leveraging AI for Autonomous Simulations in SIL and HIL Frameworks2025-28-0271To be published on 11/06/2025
This paper offers recent ideas and its implementation on leveraging AI for off highway Autonomous vehicle Simulations in SIL and HIL frameworks. Our objective is to enhance software quality and reliability while reducing costs and efforts through advanced simulation techniques. We employed multiple innovative solutions to build a System of Systems Simulation. Physics based models are prerequisite for detailed and accurate representation of the real-world system but it poses challenges due to its computational complexity and storage requirements. Machine learning algorithms were used to create surrogate/reduced order models to optimize by preserving the expected fidelity of models. It helped to speedup simulation and compile model code for SIL & HIL Targets. Built AI driven interfaces to bridge windows, Linux and Mobile Operating systems. Time synchronization was the key challenge as multiple environments were needed for end-to-end solution. This was resolved by using reinforcement
Karegaonkar, Rohit P., AOLE, Sumit, Dasnurkar, Swapnil, Singh, Vishwajeet, SAHA, Soumyadeep
Dynamic Stiffness Simulation Driven Design Changes for Tractor Cab to Mitigate Structure Borne Noise Levels2025-28-0291To be published on 11/06/2025
The dynamic stiffness of mount systems is a critical factor influencing the overall dynamic behavior and vibration isolation capabilities of mechanical assemblies. Effective cab isolation in product design can reduce structure borne noise and tactile vibrations experienced by operators. Detailed dynamic stiffness analysis of mounting brackets coupled with modal analysis using finite element method provide insights into the vibration response and resonant frequencies of components. By systematically varying parameters such as material properties, shape and geometry, the study elucidates the sensitivity of dynamic stiffness to design alternations. This study investigates on dynamic stiffness and their consequential impact on system dynamics on various design alternations by considering the space constraints at mount locations due to components, wiring harness and structural analysis driven solutions. In overall, this paper emphasizes the pivotal role of dynamic stiffness analysis in
Saveenkumar, Valakeerthi, Cone, Kerry, Mandke, Devendra Laxmikant, Fapal, Anand
Eyes of Robot operating system for future hands2025-28-0246To be published on 11/06/2025
In today’s competitive market, factories need to harness their full potential by smart and adaptive thinking to keep up with changing technology, demand, and manufacturing process. This demands multiple product manufacturing on same line, less time for changeovers and robotic automations for efficiency improvements. Each custom automation piece requires human efforts for development and maintenance. Robot programming is major pain area for industries requiring skilled professionals and adapting to shifting market demands. Enabling ROS with Cameras for learning natural/traditional way of manufacturing for Robots and incorporating that to program them will reduce manual efforts, skilled professionals and help factories in sustainability, highest customization, and even higher quality. Enabling ROS with Camera to capture -> connect -> compile -> create for reducing development time and increasing efficiency. This will help industries to manage even the complex product portfolio on a
Hepat, Abhijeet
Investigation of Driving Characteristics for Road Alignments with High Traffic Accident Rates on Hilly and Mountainous Roads Using a Motorcycle Simulator2025-32-0035To be published on 11/03/2025
Accidents involving riders visiting mountainous areas such as Nagano Prefecture in Japan on motorcycles for sightseeing and driving are common. In a previous study, analysis of traffic accident statistics data suggested that the fatality and serious injury rates for uphill right curves and downhill left curves are high, however the true causes of these accidents remain unclear. Therefore, in this study, a motorcycle simulator was used to evaluate the driving characteristics due to these road alignments. Evaluation courses based on combinations of uphill/downhill slopes and left/right curves were created, and experiments were conducted. The subjects of the study were expert riders, specifically police motorcycle riders, and novice student riders. The results showed that right curves are even more difficult to see near the entrance of the curve when accompanied by an uphill slope, making it easier to delay recognition and judgment of the curve. Expert riders recognized curves faster than
Kuniyuki, Hiroshi, Katayama, Yuta, Kitagawa, Taisei, Numao, Yusuke
Impact of air pressure load on HVAC kinematic mechanism2025-28-0368To be published on 10/30/2025
In vehicle AC system, HVAC is one of important component as it control the air flow and air distribution based on cabin requirement. There are different air mode like face, foot and defrost mode to control the air flow inside vehicle and HVAC kinematic mechanism is used for controlling the air flow based on requirement. The air passing inside HVAC have a severe impact on the torque on the servo motor which controls the mechanism. Simulation driven design method is used globally in recent days in highly competitive automotive industry. Launching the product at the market within short span of time, with good quality and less cost is more challenging. Hence CAE/MBD based approach is more significant as it will reduce number of prototypes as well as the cost of testing. The objective of the analysis is to find the torque required to operate the HAVC linkages under operating conditions. The fluid air pressure will induce force at the damper face which will affect the torque. The torque
Parayil, Paulson
A methodology to couple simulation and economics to analyze emerging power train architectures for Heavy-duty Commercial Vehicles2025-28-0362To be published on 10/30/2025
Current paper presents the methodology to couple the physics-based simulation of vehicle with power train architectures like IC engine, hybrid, Battery Electric Vehicle (BEV) and Fuel Cell (FCEV) vehicle with economic analysis. The Techno economic analysis is performed for Heavy duty Commercial Vehicles (HCV) using in-house simulation tool as well as cost projections for emerging fuels substituting Diesel and key components. India specific drive cycle for optimized thermal efficiencies and ecosystem trends are used for on-highway application market. Accordingly, fuel economy, carbon signature and Total Cost of Ownership (TCO) is estimated for individual architecture over next two decades. The analysis enables industry and businesses to understand the most desirable & feasible solutions, prioritize the time wise investments and identify potential areas to collaborate with external partners like university and government agencies. The results for rigid truck use case are presented in
Kanikdale, Tushar, Pantvaidya, Siddharth, Yadav, Dhananjay
Risk Assessment of Delayed MAC Compressor Engagement on Occupant Thermal Comfort2025-28-0399To be published on 10/30/2025
Mobile air conditioning (MAC) systems play a critical role in ensuring occupant thermal comfort, particularly under extreme ambient conditions. Any delay in compressor engagement directly affects cabin cooldown performance, impacting both perceived and measured comfort levels. This study assesses the thermal comfort risks associated with compressor engagement delays of 6.5 seconds and 13 seconds under varying ambient conditions. A comprehensive frontloading approach was employed, integrating 1D CAE simulations with objective and subjective experimental testing. Initial simulations provided insights into transient cabin heat load behavior and air distribution effectiveness, enabling efficient test case selection. Physical testing was conducted in a controlled climatic chamber under severe (>40°C) ambient condition, replicating real-world scenario. Objective metrics, including cabin air temperature, vent temperature and cooldown rates, were measured to quantify thermal performance
Kulkarni, Shridhar, Deshmukh, Ganesh, Joshi, Gaurav, Shah, Geet, Jaybhay, Sambhaji
Reinforcement Learning with Adaptive Discount Factor for Clutch Judder Suppression with Stable Learning in Two-Speed EV Transmission2025-01-0375To be published on 10/07/2025
Designing gear shift control for automotive transmissions requires advanced control techniques to handle nonlinear behaviors that are only partially observable, such as variations in friction coefficients resulting from changes in relative speed between clutch plates and oil temperature fluctuations. Although recent studies employing deep reinforcement learning have effectively suppressed shift shock, they have not sufficiently addressed divergence-type vibrations (judder) arising from the negative gradient of friction coefficients with respect to relative clutch plate speed, which tends to become more pronounced due to clutch plate aging. Conventional reinforcement learning algorithms assume constant state transitions and rewards over time; thus, their learning processes may become unstable when environmental changes occur. Consequently, these methods often fail to stably suppress clutch judder caused by variations in friction coefficients due to repeated clutch engagements. To
Ogawa, Kazuki, Aihara, Tatsuhito, Goto, Takeru, Minorikawa, Gaku
Simulation study of wheel bearing friction losses at vehicle level2025-01-0399To be published on 10/07/2025
With the ongoing electrification of vehicles, components contributing a minor share of overall drivetrain losses are coming into focus. Analyzing these losses is crucial for enhancing the energy efficiency of modern vehicles and meeting the increasing demands for sustainability and extended driving range. These components include wheel bearings, whose friction losses are influenced by parameters such as temperature, mechanical loads, and mounting situation. Therefore, it is essential to analyze the resulting friction losses and their dependence on the mentioned influencing parameters at an early stage of development, both through test bench measurements and with the help of simulation models. To achieve these objectives, this submission presents a methodology that combines test bench measurements with a measurement-based simulation of the friction losses of wheel bearings occurring in the vehicle as a complete system under varying driving cycles and parameters. For this purpose, an
Hartmann, Lukas, Sturm, Axel, Henze, Roman, Notz, Fabian
Understanding End-of-Line NVH Scatter Bands in Electric Drives with High-Precision Simulations2025-01-0406To be published on 10/07/2025
An important characteristics of battery electric vehicles (BEVs) is their noise signature. Besides tire and wind noise, noise from auxiliaries as pumps, the electric drive unit (EDU) is one of the major contributors. The dynamic and acoustic behavior of EDUs can be significantly affected by production tolerances. The effects that lead to these scatter bands must be understood to be able to control them better and thus guarantee a consistently high quality of the products and a silent and pleasant drive. The paper discusses a simulation driven approach to investigate production tolerances and their effect on the NVH behavior of the EDU, using high precision transient multi-body dynamic analysis. This approach considers the main effects, influences, and the interaction from elastic structures of electric motor and transmission with accurate gear contact models in a fully coupled way. It servs as virtual end of line test, applicable in all steps of a new EDU development, by increasing
Klarin, Borislav, Schweiger, Christoph, Resch, Thomas
COMVEC 2025 Reviewers02-18-03-002609/11/2025
COMVEC 2025 Reviewers
Sandu, Corina
Effect of PEM Fuel Cell Technology Advancement on the Energy Efficiency of a Heavy-Duty Vehicle2025-24-011109/07/2025
Fuel cell hybrid electric vehicles (FCHEVs) are a promising solution for decarbonizing heavy-duty transport by combining hydrogen fuel cells with battery storage to deliver long range, fast refuelling, and high payload capacity. However, many existing simulation models rely on outdated fuel cell parameters, limiting their ability to reflect recent technological improvements and accurately predict system-level performance. This study addresses this gap by integrating a state-of-the-art, physics-based model of a polymer electrolyte membrane fuel cell (PEMFC) into an open-source heavy-duty vehicle simulation framework. The updated model incorporates recent advancements in catalyst design and membrane conductivity, enabling improved representation of electrochemical behavior and real-time compressor control. Model performance was evaluated over a realistic 120 km long-haul drive cycle. Compared to the traditional fuel cell model, the updated system demonstrated up to 20% lower hydrogen
Dursun, Beyza, Johansson, Max, Tunestal, Per, aronsson, Ulf, Eriksson, Lars, Andersson, Oivind
Flexible an Low Cost Fuel Consumption Prediction in Heavy-Duty Vehicles Using Machine Learning2025-24-012109/07/2025
This study presents a novel approach for predicting fuel consumption in heavy-duty vehicles using a Machine Learning-based model, which is based on feedforward neural network (FFNN). The model is designed to enhance real-time vehicle monitoring, optimize route planning, and reduce both operational costs and environmental impact, making it particularly suitable for fleet management applications. Unlike traditional physics-based approaches, the FFNN relies solely on a refined selection of input variables, including vehicle speed, acceleration, altitude, road slope, ambient temperature, and engine power. Additionally, vehicle mass is estimated using a methodology presented elsewhere and is included as an input for a better generalization of the consumption model. This parameter significantly impacts fuel consumption and is particularly challenging to obtain for heavy-duty vehicles. Engine power is derived from both engine torque and speed (RPM), ensuring a direct relationship with fuel
Vicinanza, Matteo, Pandolfi, Alfonso, Arsie, Ivan, Giannetti, Flavio, Polverino, Pierpaolo, Esposito, Alfonso, Paolino, Antonio, Adinolfi, Ennio Andrea, Pianese, Cesare, Frasci, Valentino
Thermal Characterisation of a High-Power Lithium-Ion Pouch Cell and Surface Temperature Prediction for Motorsport Applications2025-24-014209/07/2025
Accurate cell thermal characterisation is vital for battery modelling and thermal management, especially in motorsport, where minor temperature estimation errors can have severe consequences. Conventional methods for determining key thermal parameters, such as the specific heat capacity, often require costly calorimeters or destructive testing. Recent studies propose an alternative approach using a 1D lumped thermal network to solve the thermal balance of a heat-generating cell. However, these studies often overlook critical aspects of the heat generation equation, particularly the entropic term, which is essential for capturing nonlinear thermal behaviour, especially under dynamic cycling conditions. This study presents a cost-effective approach for rapid cell thermal characterisation and accurate surface temperature prediction. A pouch LCO cell was first tested to determine the entropic coefficient, followed by experiments under two convective conditions to evaluate its specific heat
Sciortino, Davide Domenico, Schommer, Adriano, Costa, Andre
Vehicle Under-Hood Thermal Management: Development of a Reduced-Order Model for Accurate and Computationally Efficient Temperature Distribution Simulations2025-24-011809/07/2025
Electrified vehicle energy management plays a crucial role in the context of the European Green Deal by facilitating the transition toward sustainable mobility. The development of predictive and robust simulation tools is essential to implement and test different energy management strategies. This study aligns with this objective by presenting the development of an under-hood flows model designed for integration into a 1D vehicle simulator, which is used to perform vehicle simulations about longitudinal performances, energy consumption and range. Vehicle under-hood thermal management is inherently complex due to the interplay of internal flow dynamics and multiple heat transfer mechanisms. A purely 1D modeling approach lacks the spatial resolution required to capture detailed flow field characteristics, while a fully 3D CFD model is computationally prohibitive for scenarios requiring efficient simulations. To address this trade-off, a reduced-order model (ROM) approach is proposed. The
Miccio, Stefano, Grattarola, Federico, Baratta, Mirko, Giraudo, Gabriele, Frezza, Davide, Bartolucci, Lorenzo
Optimal Design of Electric Motors for Automotive Applications2025-24-013209/07/2025
The paper describes how, exploiting AI, it is possible to design electric motors for automotive applications. Both traction motors and motors for auxiliary functions are dealt with. Given the requested performance of the motor (objective functions) and the constraints, the design variables defining the motor are derived by means of a multi-objective programming approach. Usually, tenth of either objective functions or design variables are considered. Aspects related both to electromagnetic and mechanical performance are taken into account, in a multi-physics framework. The issues referring to thermal, structural and noise-vibration-harshness are considered for defining the Pareto-optimal sets both in the design variable domain and in the objective function domain. Such domains can be found by either supervised learning or reinforced learning, two well-known AI algorithms. Basic constraints related to manufacturing are included in the optimization process. A couple of examples are
Guidotti, Giacomo, Barri, Dario, Soresini, Federico, Ballo, Federico, Gobbi, Massimiliano, Di Gerlando, Antonino, Mastinu, Gianpiero
Simulation Driven Thermal Optimization of an Innovative Battery System2025-24-013809/07/2025
BATSS project objective is to design a safe, effective and sustainable battery pack. To achieve this, the battery system (BS) will be mechanically, electrically and thermally optimized using cutting edge technology. Consequently, the battery system includes innovative 4695 cylindrical cells and advanced thermal management, carried out with the Miba FLEXCOOLER®. This work focuses on the BS thermal optimization using system simulation tools. First a simplified version of the BS is simulated with all physical phenomena involved in thermal behavior to identify first order parameters. It appears that various BS component and heat transfer can be neglected in comparison with the heat transfer due to cooling system. Then the simulation of the full battery system is conducted under nominal condition. Cooling system appears to be performant as it allows a controlled averaged temperature and very low cell-to-cell temperature variability. Finally, impact of both design and operating parameters is
Chevillard, Stephane, Popp, Hartmut, Galarza, Igor, Petit, Martin
Dust-Powered 3D PrintingTBMG-5373709/02/2025
After 3D printing a habitat designed for Mars and working with NASA on print material made from synthetic Moon dust, AI SpaceFactory Inc. has commercialized two separate 3D printers. The Secaucus, NJ-based company’s latest offering, Starforge, is a large-capacity 3D printer that uses innovative print material inspired by SpaceFactory’s work with NASA’s Kennedy Space Center in Florida under an Announcement of Collaboration Opportunity agreement.
Patient-Centric Design and Collaboration in Drug-Delivery DevicesTBMG-5376809/01/2025
Imagine being handed a device that’s meant to help you — but instead feels intimidating, confusing, or painful to use. For millions of patients around the world, that’s the reality of managing treatment at home. Across ailments, the burden of self-administered care is growing, and with it, the importance of designing drug-delivery systems designed with the patient experience at their core.
New Technique Could Accelerate Noise-Free Superconducting Qubits for Quantum ComputingTBMG-5371909/01/2025
A research team led by scientists at Lawrence Berkeley National Laboratory (Berkeley Lab) has developed a new fabrication technique that could improve noise robustness in superconducting qubits, a key technology for enabling large-scale quantum computers.
A Technological Breakthrough for Ultra-Fast and Greener AITBMG-5370209/01/2025
Artificial intelligence systems like ChatGPT are notorious for being power-hungry. To tackle this challenge, a team from the Centre for Optics, Photonics and Lasers (COPL) has come up with an optical chip that can transfer massive amounts of data at ultra-high speed. As thin as a strand of hair, this technology offers unrivaled energy efficiency.
Energy Prediction for Hotel Loads in Mild-Hybrid Heavy-Duty Vehicle02-18-03-002008/29/2025
Long-haul truck drivers are mandated to take off-duty time of 10 h (a.k.a. hoteling) before driving. During the hotel phase, drivers spend time inside their trucks (sleeper cabs) and idle the internal combustion engine for comfort by utilizing the heating, ventilation, air-conditioning (HVAC), and other onboard appliances. For one 10-h period, the average cost is about $40, which can be a lot when considering a million truck drivers idling overnight. SuperTruck II is a 48 V mild-hybrid heavy-duty truck with auxiliary loads powered by an onboard battery pack. An optimal control algorithm is developed to charge the battery pack during the drive phase up to a certain state-of-charge (SOC) level, sufficient to meet the power demands of the auxiliary load during the hotel phase. This article captures the research done to predict energy consumption in a mild-hybrid heavy-duty sleeper truck during hoteling. Physics-based gray box models are developed to estimate the power consumption of an
Khuntia, Satvik, Hanif, Athar, Ahmed, Qadeer, Lahti, John, Jorgensen, Iner
Optimizing Hybrid Powertrains for Off-Highway Vehicles02-18-03-002408/23/2025
This article details the development of a plug-in hybrid electric powertrain system for a wheel loader. The work included both computer modeling and fired engine testing. A methodical approach was utilized, which included identifying system requirements, an architecture study, component sizing, and cost analysis. After the optimal system was designed, the engine and hybrid motor were installed in a powertrain test cell and evaluated over an in-use duty cycle. A bespoke utility factor, relevant for wheel loader operation, was developed to enable realistic fuel economy and emissions weighting between charge depleting and charge sustaining operation. Finally, an exhaust heater was used to ensure rapid warmup of the aftertreatment system. Compared to an internal combustion engine–only baseline, the hybrid powertrain system resulted in a 48% reduction in CO2 and an 84% reduction in NOX emissions when operated over an 8-h shift, with daily recharging.
Bachu, Pruthvi, Michlberger, Alexander, Meruva, Prathik, Bitsis, Daniel Christopher
Training and Approval of Thermal Processing PersonnelARP1962C (Current)08/22/2025
This SAE Aerospace Recommended Practice (ARP) describes training and approval of personnel performing certain thermal processing and associated operations that could have a material impact on the properties of materials being processed. It also recommends that only approved personnel perform or monitor the functions listed in Table 1.
AMS B Finishes Processes and Fluids Committee
SAE TOMORROW TODAY - How the NVIDIA-Magna Collaboration Is Redefining Autonomy1353108/21/2025
From next-gen chipsets to scalable autonomous driving solutions, Magna's groundbreaking partnership with NVIDIA is paving the way for the next generation of software-defined, AI-powered vehicles. By harnessing NVIDIA's new Blackwell GPU architecture to enable ADAS and L2+ through L4 capabilities, Magna is blending its deep automotive expertise with powerful AI compute to redefine what's possible for both in-vehicle experiences and autonomous driving. To learn more, we sat down with Steven Jenkins, Vice President of Technology & Strategy at Magna International, to discuss the company's collaboration with NVIDIA, navigating legacy mindsets, and scaling vehicle intelligence across global markets. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists
Patterson, Lori
SAE TOMORROW TODAY - Women Breaking Barriers in Aerospace & Beyond1352108/19/2025
Despite decades of progress, the number of women in engineering remains stubbornly low -- especially in aerospace and mechanical engineering. But that isn't stopping the winner of the Aerospace/Defense category in the inaugural Women in Engineering: Rising Star Awards. Heather Cummings is Senior Engineer, Flight Controls & Autonomy for Sikorsky, a Lockheed Martin company. She leads the development of hybrid electric propulsion controls and vehicle management systems for Sikorsky's next-gen HEX and RBW, including groundbreaking work on fully autonomous cargo aircraft. A licensed pilot, Heather is passionate about improving flight safety through automation and mentoring the next generation of aspiring engineers. In this special episode, Heather and Chitra Sethi, Director of Editorial & Digital Content, SAE Media Group, discuss the mission behind the Rising Star Awards, the importance of visibility for women in STEM, and why inspiring the next generation is just as critical as
Hineman, Marcie
Small, Mobile, and Autonomous Agricultural RobotsEPR202501208/13/2025
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
Muelaner, Jody E.
A Twist in Topology Optimization Leads to High-Performing Heat ExchangerTBMG-5359008/01/2025
By combining topology optimization and additive manufacturing, a team of University of Wisconsin-Madison engineers created a twisty high-temperature heat exchanger that outperformed a traditional straight channel design in heat transfer, power density and effectiveness.
Solving problems and seeking big ideas25TOFHP08_0208/01/2025
PACCAR's Phil Stephenson previews SAE COMVEC 2025 and offers insights into powertrain diversification, the role of AI, a software-defined future and the importance of people. Advancing technology to solve challenges involving regulation, compliance, autonomy, electrification, combustion engines and other areas is an obvious focus of SAE International's flagship gathering for the commercial vehicle and off-highway industries, COMVEC 2025 (https://comvec.sae.org/). But advancing people, which is vital to navigating this challenging environment, is a particular focal point for this year's engineering event being held near Chicago in September. Workforce development is just as critical as technology development, stresses Phil Stephenson, general manager of PACCAR Technical Center, where he leads a team of engineers, technicians, mechanics, scientists and business leaders. Stephenson is serving as the executive chair of SAE COMVEC 2025, which carries the theme “Advancement, Empowerment
Gehm, Ryan
Mid-Air Transformation Helps Flying, Rolling Robot to Transition SmoothlyTBMG-5355508/01/2025
Specialized robots that can both fly and drive typically touch down on land before attempting to transform and drive away. But when the landing terrain is rough, these robots sometimes get stuck and are unable to continue operating. Now a team of Caltech engineers has developed a real-life Transformer that has the “brains” to morph in midair, allowing the dronelike robot to smoothly roll away and begin its ground operations without pause. The increased agility and robustness of such robots could be particularly useful for commercial delivery systems and robotic explorers.
Q&A25TOFHP08_1308/01/2025
Volvo Construction Equipment made a big statement at Bauma 2025 by displaying an all-EV lineup and revealing a new electric articulated hauler to boot. The company has come a long way since the 2019 event when it unveiled its first two commercial electric machines, said Melker Jernberg, president of Volvo CE. “Today we are leaders in many different segments when it comes to electrification,” he said. Jernberg helped to drop the curtain on a claimed “world first” EV, the A30 electric hauler. Five “cubes” of 600V Liion batteries provide 270 kWh of usable energy (450 kWh installed) and a runtime of 4 to 4.5 hours. A 350-kW charger can charge the machine to between 20-80% in one hour. Delivery of A30 and A40 electric haulers will start in Europe in 2026 for selected customers, “then we'll ramp up for all other markets in 2027 and 2028,” he said. Jernberg answered questions about Volvo CE's electrification and product strategy during a Bauma press conference.
Gehm, Ryan
Moving targets: How improvements to SiC, GaN power electronics will redefine EVs25AUTP08_0108/01/2025
Smaller devices that can do the same or more efficient work than silicon can lead to markedly smaller EV powertrain components. This story starts in 2017, when the Department of Energy's U.S. DRIVE partnership laid out targets for power electronics for 2025 in a technical team roadmap: power density of 100 kW/l for a powertrain that would last either 300,000 miles or 15 years, at a cost of no more than $2.70 per kW. Progress in the intervening years led to an updated roadmap in 2024, specifying stricter 2025 targets of 150 kW/l power density at a cost of no more than $1.80 per kW, based on a 600-volt system. Along with that came more refined targets for 2030 and 2035. For 2030, the goal is an 800-volt system that produces peak power of 200 kW maintained for 30 seconds, and a power density of 200 kW/l that costs no more than $1.35 per KW. The goal for 2035 now sits at 225 kW/L for $1.20.
Ramsey, Jonathon
New Copper Alloy Could Provide Breakthrough in Durability for Military SystemsTBMG-5359108/01/2025
U.S. Army researchers, in collaboration with academic partners, invented a stronger copper that could help advance defense, energy and aerospace industries thanks to its ability to endure unprecedented temperature and pressure extremes. Extreme materials experts at the U.S. Army Combat Capabilities Development Command (DEVCOM) Army Research Laboratory built on a decade of scientific success to develop a new way to create alloys that enable Army-relevant properties that were previously unachievable. An alloy is a combination of a metal with other metals or nonmetals.
Pilot Training and Certification for VTOL-Capable AircraftAS7062 (Current)08/01/2025
This standard is intended for use by original equipment manufacturers (OEMs), regulators, operators, training organizations, and any others who wish to develop curricula for pilot, instructor, and evaluator training courses for new aircraft - VCA. Continuous updates to this standard will be necessary to incorporate advancements in VTOL technologies and training methods. This standard describes the knowledge, skills, and attitudes required to safely operate VCA for commercial purposes. A Civil Aviation Authority (CAA) may, at their discretion, use this standard to aid the development of existing or future regulations. OEMs and operators may use this standard to develop a curriculum for acceptance or approval by civil regulators. This standard includes a Pilot Training Program developed to address the theoretical and practical training and assessment for VTOL-capable pilot licensing/certification. Additionally, this standard contains the requirements for pilot training and licensing for
G-35A Pilot Training and Certification Committee
Careers in Aerospace: A Student’s Guide to the Sky and BeyondR-56807/24/2025
Have you ever looked up and wondered how humans conquered the skies—and what lies beyond? This book requires no prior knowledge of math—just curiosity and a passion for discovery. From the Wright brothers’ 12-second flight in 1903 to spacecraft that reach the edge of our solar system, aerospace engineering has propelled us to new frontiers. It is the foundation of modern flight, blending physics, chemistry, biopharmaceuticals, mechanics, electronics, and communications to push the limits of speed, altitude, and exploration. In just over a century, we have progressed from envying birds to flying over three times the speed of sound, launching space shuttles, and venturing into the cosmos. The urge to explore is unstoppable, and the future promises even greater achievements. Whether you’re a curious spectator or an aspiring professional, this book offers an engaging introduction to the principles behind aviation and space travel. Understanding the fundamentals will deepen your
Baghchehsara, Ali
SAE TOMORROW TODAY UNPLUGGED: What Happens When EV Tax Credits End?1352607/18/2025
The signing of the "Big Beautiful Bill" by President Trump is poised to end both the $7,500 new EV tax credit as well as the $4,000 used EV tax credit on September 30. If these EV tax credits go away, what happens? Do EV sales slow down dramatically? Or do they hold steady? How with automakers and battery manufacturers react? In this Unplugged episode of SAE Tomorrow Today, host Grayson Brulte discusses how the end of EV tax credits could impact new and used EV sales, consumer behavior, and the broader battery manufacturing industry. 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. Follow host Grayson Brulte on LinkedIn, Twitter, and Instagram.
Patterson, Lori
800P3-2 Cabin Connectors and Cables, Part 3, Specification of CablesARINC800P3-2 (Current)07/07/2025
This specification describes the general cable and wire characteristics recommended for use in cabin systems for commercial aircraft. Supplement 1 adds new definitions of 26 AWG 2-pair (Quad), 4-pair (Oct) data cables, and copper-fiber optic hybrid composite cables. Supplement 2 includes definitions of shielded twisted pair ethernet over single pair for data rates up to 1000Base-T1.
Airlines Electronic Engineering Committee
Study on Driver-Dependent Stabilization Capabilities for Safe Chassis Control with Steer By Wire2025-01-027607/02/2025
Steer-by-wire actuators represent a transformative advancement in chassis control, opening up new potential for optimizing driving behavior across the entire range of driving dynamics - including driver-dependent automatic counter steering in critical driving situations. However, from a functional safety perspective, the increased potential also introduces new risks with respect to possible system failures. To mitigate these risks, sophisticated monitoring functions are essential to ensure vehicle controllability at all times. Current research approaches for monitoring functions use safe driving envelopes. This set of safe driving states is often found by open-loop simulations, which provide a phase portrait of the nonlinear system under control and from which stability limits can be derived. However, it remains open how these open-loop stability limits correspond to the stabilization capability of a real human driver in the loop. And secondly, how these closed-loop stability limits
Birkemeyer, Janick, Naidu P.M, Tarun, Borkowski, Lukas, Müller, Steffen
Theory behind a Novel Method for the Quantification of Subjective Ride Comfort Phenomena2025-01-026707/02/2025
In the automotive development process objective criteria are commonly used to evaluate the full vehicle ride comfort of vehicles. Based on these characteristics, vehicle concepts can be evaluated and compared at an early stage without using physical prototypes. Usually, these characteristics are determined in subjective studies using real vehicles. However, limitations in the implementation of vehicle variants, the controllability of external influences and longer intervals between the individual assessments have a negative impact on the quality of results using these approaches. Therefore, this paper presents an improved method to transfer the subjective perception and evaluation of ride comfort phenomena to objective characteristics. The corresponding procedure is shown on the basis of a one-dimensional, periodic phenomenon that is transferred to a frequency-dependent weighting function. In this process, a 6-degree of freedom driving simulator is used to overcome the limitations
Stroesser, Simon, Angrick, Christian, Zwosta, Tobias, Neubeck, Jens, Wagner, Andreas
Reducing Traffic Congestion with Reinforcement Learning-Driven Signal Control Systems2025-01-028307/02/2025
The road network is a critical component of modern urban mobility systems, with signalized traffic intersections playing a pivotal role. Traditionally, traffic light phase timings and durations at intersections are designed by transportation engineers using historical traffic data. Some modern intersections employ trigger-based mechanisms to improve traffic flow; however, these systems often lack global awareness of traffic conditions across multiple intersections within a network. With the increasing availability of traffic data and advancements in machine learning, traffic light systems can be enhanced by modeling them as agents operating in an environment. This paper proposes a Reinforcement Learning (RL) based approach for multi-agent traffic light systems within a simulation environment. The simulation is calibrated using real-world traffic data, enabling RL agents to learn effective control strategies based on realistic scenarios. A key advantage of using a calibrated simulation
Kalra, Vikhyat, Tulpule, Punit, Giuliani, Pio Michele
Development of a Cost Model for ADAS and AD Functions2025-01-026107/02/2025
Computer-aided synthesis and development tools are essential for discovering and optimizing innovative concepts. Evaluating different concepts and making informed decisions relies heavily on accurate assessments of system properties. Estimating these properties in the early stages of vehicle development is challenging due to the depth of modelling required. In order to enable a cost prognosis for driving assistance and automated driving functions including software and hardware properties a cost model was developed at the Institute of Automotive Engineering. The methodology and cost model focuses on multiple combined approaches. This includes a bottom-up approach for the hardware. The costs of the software components are integrated into the model with the help of existing literature data and an exponential regression. For a comprehensive view of the total costs, the model is the model is also supplemented by a top-down approach for estimating the costs of other hardware components. The
Sturm, Axel, Hichri, Bassem, Rohde García, Álvaro, Henze, Roman
Requirements, Methods and Models for Early Electrified Drive Concept Development2025-01-030407/02/2025
Computer-aided synthesis and development tools are essential for discovering and optimizing innovative concepts. Evaluating different concepts and making informed decisions relies heavily on accurate assessments of drive system properties. Estimating these properties in the early stages of development is challenging due to the depth of modelling required. In addition, defined requirements play a critical role in drive system sizing. This paper presents a tool chain for the synthesis of new electrified drive concepts, with emphasis on requirements definition and modelling. The requirements definition method combines market analysis with a generalized calculation and estimation approach, providing a novel perspective. In addition, we introduce mass and cost modelling capabilities integrated into the tool chain. The mass model achieves high accuracy, with deviations of only 1.6 % at the vehicle level and 6.1 % at the component level. Finally, the paper examines the mass and cost
Sturm, Axel, Henze, Roman
Inside the OEM: Boston Scientific to Focus on Cardiology InnovationTBMG-5345007/01/2025
Boston Scientific entered 2025 with significant momentum. Fresh off a standout first quarter, the company’s leadership has outlined a compelling vision for sustainable long-term growth rooted in high-performing cardiology franchises, operational precision, and disruptive technologies in electrophysiology (EP). Leaders spoke at a recent Bank of America Healthcare Conference. The discussion marked outgoing CFO Dan Brennan’s final investor presentation and underscored Boston Scientific’s transformation into one of medtech’s most durable growth stories.
AI-Powered Analysis of Stent HealingTBMG-5344007/01/2025
A research team has developed DeepNeo, an AI-powered algorithm that automates the process of analyzing coronary stents after implantation. The tool matches medical expert accuracy while significantly reducing assessment time. With strong validation in both human and animal models, Deep-Neo has the potential to standardize monitoring after stent implantation and thus improve cardiovascular treatment outcomes.
A Chip with Natural Blood VesselsTBMG-5343807/01/2025
Mini organs are incomplete without blood vessels. To facilitate systematic studies and ensure meaningful comparisons with living organisms, a network of perfusable blood vessels and capillaries must be created — in a way that is precisely controllable and reproducible. A team has established a method using ultrashort laser pulses to create tiny blood vessels in a rapid and reproducible manner. Experiments show that these vessels behave just like those in living tissue. Liver lobules have been created on a chip with great success.
NASA Marks Artemis Progress with Gateway Lunar Space StationTBMG-5340507/01/2025
Through the Artemis campaign, NASA will send astronauts on missions to and around the Moon. The agency and its international partners report progress continues on Gateway, the first space station that will permanently orbit the Moon, after visiting the Thales Alenia Space facility in Turin, Italy, where initial fabrication for one of two Gateway habitation modules is nearing completion.
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