Browse Topic: Maintenance, repair and overhaul (MRO)

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Predictive Maintenance Solution with Real-Time Insights and Cost Estimation for Machine Health Management2025-28-0302To be published on 11/06/2025
This paper introduces a comprehensive solution for predictive maintenance, utilizing statistical data and analytics. The proposed Service Planner feature offers customers real-time insights into the health of machine or vehicle parts and their replacement schedules. By referencing data from service stations and manufacturer advisories, the Service Planner assesses the current health and estimated lifespan of parts based on metrics such as days, engine hours, kilometers, and statistical data. The user interface displays current part health, replacement due dates, and estimated replacement costs. For example, if air filter replacement is recommended every six months, the solution uses manufacturer advisories to estimate the remaining life of the air filter in terms of days or engine hours. It also suggests replacement dates, suitable part options, replacement costs, and available service slots through an operator guidance mobile app and portal. The solution features a 360-degree view of
Chaudhari, Hemant Ashok
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
Off-Highway Vehicles for Sustainable Development and Empowerment: Innovation and Technology.- Diagnosis2025-28-0301To be published on 11/06/2025
Off-highway vehicles (OHVs) play a crucial role in industries such as agriculture, construction, and mining, contributing to sustainable development and economic empowerment. Ensuring their optimal performance requires a robust customer support system focused on efficient diagnosis and resolution of technical issues. This paper explores the importance of advanced diagnostic techniques in OHVs, emphasizing innovation and technology-driven approaches to minimize downtime and enhance productivity. The evolution of diagnostic tools, from traditional manual inspections to AI-powered predictive maintenance, has transformed customer support in the OHV sector. The integration of telematics, IoT-enabled sensors, and cloud-based analytics allows real-time monitoring of vehicle health, enabling proactive maintenance and reducing unexpected failures. Additionally, remote diagnostics and augmented reality (AR)-assisted troubleshooting empower field technicians with real-time insights, improving
Tripathi, Ashish, Thakur, Anil
A unit Product Energy mapping framework2025-28-0247To be published on 11/06/2025
Combining energy management and value stream mapping In today's industrial landscape, manufacturing plays a central role in driving economic growth. However, this crucial sector is also a major contributor to global energy consumption and greenhouse gases (CO2eq) emission. Energy management focuses on the systematic use of management and technology to improve energy performance in a selected site, such as a building, facility, or an entire organization. It requires that energy procurement, energy efficiency and renewable energy y be integrated proactive and incorporated in order for it to be fully effective. Value Stream Mapping (VSM), a widely used tool of Lean Manufacturing, is a type of symbolic model that graphically enables the end user to observe the material and information flow as a product or service travels through a value chain. The model represents the flow of resources such as materials, information and personnel along with their interactions, beginning with a sales order
Sumbe, Ankita Surendra, Kumar, Rahul, Shrivastava, Swapnil
AI in Off-Highway Fleet Management: Driving Towards a Smarter Future2025-28-0335To be published on 11/06/2025
AI in Off-Highway Fleet Management: Driving Towards a Smarter Future Managing fleets of off-highway vehicles presents unique challenges that significantly impact operational efficiency, safety, and sustainability. These vehicles, often used in industries such as mining, construction, and agriculture, face several issues like maintenance and repair, reduced fuel efficiency, fleet tracking and monitoring. Tackling these challenges is crucial for enhancing the efficiency, safety, and sustainability of off-highway vehicle fleet management, and this paper presents an AI-driven solution to address these issues. AI systems leverage real-time data from telematics devices, sensors, and GPS tracking to optimize various aspects of fleet management. Key areas of impact include: Predictive Maintenance: AI algorithms analyse vehicle data to predict potential failures before they occur, reducing downtime and maintenance costs. By monitoring indicators such as engine performance and battery health
Selvaraj, Ajith Kumar, Nashipudi, Sandesh, Ramanathan, Vadivel, Durairaj, Manikandan
Connected Aftermarket Services for Off-Highway Vehicles: Enhancing Fleet Management Through Real-Time Data and Predictive Maintenance2025-28-0307To be published on 11/06/2025
Off-highway vehicles (OHVs) are critical to industries such as construction, agriculture, and mining, where they often operate in challenging environments requiring constant maintenance and repair. This paper presents a connected platform designed to enhance customer support and fleet management by integrating real-time data monitoring, predictive maintenance, and e-commerce capabilities. Through IoT-enabled sensors, cloud computing, and data analytics, the system continuously collects and analyzes vehicle performance data, providing fleet owners with actionable insights for efficient resource allocation and maintenance scheduling. The platform offers automated alerts for part replacements, tracking of repair history, and optimization recommendations based on vehicle condition. By integrating e-commerce for aftermarket parts and services, fleet managers can easily purchase and manage the inventory required for their operations. This connected system not only improves operational
Vashisht, Shruti
Analysis of maintenance strategies of electrical systems of Electric bus charging station2025-28-0407To be published on 10/30/2025
Charging management has a profound impact on the reliability and safety of electric bus (EB) services. However, the actual charging operation of EB fleets is a critical challenge due to uncertain energy consumption, limited charging resources and other factors. At present there are no operational and maintenance guidelines present for operation of EV bus charging stations since the running and operation of these facilities are at the initial stages of development. There is a need to develop these strategies that provides smooth operation of these newly developed facilities. In the present work maintenance strategies of electrical systems of Electric bus charging station were designed. The complete maintenance is divided into quarterly and annual maintenance based on the requirements and nature of work for smooth operation. Quarterly Maintenance is devised on detecting early signs of wear through visual inspections of key components, including transformers and ventilation systems while
Soam, Kumaresh, Vashist, Devendra
Application of Machine Learning to Engine Fuel System Failure Prediction2025-01-0377To be published on 10/07/2025
The automotive industry prioritizes reliability and minimizes downtime, leading to a rapid embrace of predictive maintenance to curtail unforeseen failures and associated expenses. Traditional reactive maintenance strategies often prove inadequate in accurately forecasting failures, resulting in costly operational disruptions. This paper introduces a novel machine learning-driven method for predicting engine fuel system failures using anomaly detection algorithms applied to telematics data. By analyzing intricate relationships between fuel system components and operational features, our approach aims to enhance vehicle reliability and reduce maintenance costs. We present a comprehensive methodology encompassing data acquisition, data preprocessing, and feature engineering, leveraging key features such as rail pressure deviation, fuel pump metering valve current, engine torque, and engine speed to establish a benchmark for healthy vehicle operation, all sampled at one-minute intervals
Wang, Tingting, Goswami, Anil, Akinola, Michael, Yang, Tina, An, Qi
A Novel Chemical Kinetics-Based Approach for Studying Feasibility and Optimise Retrofitting Strategies of Hydrogen CI Engines: Application to a Laboratory-Scale Single-Cylinder Engine2025-24-005409/07/2025
The climate emergency has prompted countries to adopt strategies to limit the rise in global temperatures by promoting low-carbon technologies. In this context, hydrogen (H2) can be considered a viable solution, especially in road and marine transportation, where Compression Ignition (CI) internal combustion engines (ICEs) are widely used. Despite its potential to significantly reduce pollutant emissions compared to fossil fuels, hydrogen presents a major challenge for CI engines due to its high autoignition temperature (greater than diesel). To overcome this problem, a novel methodology is proposed to evaluate the feasibility of hydrogen retrofitting. Each engine operating point is simulated as an ideal zero-dimensional (0D) reactor into which a diesel-hydrogen-air mixture is introduced. A fully detailed kinetic mechanism is used to simulate the complex chemical interactions between the two fuels, as well as its significant effect on engine behaviour, obtaining accurate predictions of
Episcopo, Domenico, Rossetti, Salvatore, Mancaruso, Ezio, Saponaro, Gianmarco, Camporeale, Sergio, Laera, Davide
The VERT GPF-Retrofit Program for Cleaner Urban Mobility within the HORIZON Europe AeroSolfd Project2025-24-009509/07/2025
Launched in 2022, AeroSolfd, a HORIZON Europe project, aims to advance clean urban mobility by developing affordable and sustainable retrofit solutions for gasoline vehicles. This three-year initiative addresses not only tailpipe emissions but also brake emissions and pollution in semi-enclosed environments. Within AeroSolfd, the Swiss-based VERT association focuses on reducing tailpipe emissions using state-of-the-art Gasoline Particulate Filter (GPF) technology featuring an uncoated ceramic multicell wall-flow filter. VERT, in partnership with HJS, CPK, BFH, developed and tested a GPF-retrofit system at Technology Readiness Level 8 (TRL 8). Results demonstrate over 99% filtration efficiency for particles smaller than 500 nm on standard cycles (WLTC) and real-world driving cycles (RDE). Forty-two gasoline vehicles (GDI and PFI) were retrofitted with the GPF retrofit across Germany, Switzerland, Israel, and Denmark over a 6 to 8-month operational period. No issues were observed with
Rubino, Lauretta, Mayer, Andreas C., Lutz, Thomas W., Czerwinski, Jan, Larsen, Lars C.
Reducing Range Prediction Uncertainty in Heavy-Duty Electric Vehicles Using a Route-Informed Transformer-Based Model2025-24-012209/07/2025
Electrification of heavy-duty on-road trucks used for regional freight transportation is a viable option for fleets to reduce operation and maintenance costs and lower their carbon footprint. However, there is considerable uncertainty in projecting their daily range because highly variable payload mass, among other factors, confounds battery state of charge (SOC) prediction algorithms. Previous work by the authors proposed an electric vehicle range prediction model based on two parallel recurrent neural networks (RNNs). The first RNN used mean-variance estimation to output a predicted mean and variance, and the second used bounded interval estimation to provide bounds on the SOC required to complete a trip. The dual RNN approach resulted in estimating the remaining range and error bands of the SOC over the route. The previous work was limited because it did not incorporate driving conditions, like road type and ambient temperature, that affect driver behavior and energy consumption
Jayaprakash, Bharat, Eagon, Matthew, Northrop, William F.
AeroSolfd: Advancing Air Quality through Retrofitted Gasoline Particulate Filters – Insights from Laboratory and Real-World Evaluations2025-24-008809/07/2025
This article details the experimental and testing activities of the EU project AeroSolfd, with a particular focus on the project's efforts to reduce combustion-based nanoparticle emissions in exhaust gases for the European fleet of vehicles by developing a GPF retrofit solution. The technical activities undertaken the process of developing such a retrofit are examined in this article. The findings illustrate the viability of reducing nanoparticle levels in gasoline-powered vehicles with the utilization of appropriate GPFs. For this purpose, in addition to a fleet, four vehicles were examined in great detail and underwent the process of obtaining component approval for the particulate filter. The vehicles were measured in a preliminary state, then following the installation of the GPF, and subsequently after several months of continuous field operation. A total of four vehicles were selected for evaluation as a representative subgroup of a larger test fleet of vehicles in the project
Engelmann, Danilo, Mayer, Andreas, Comte, Pierre, Rubino, Lauretta, Larsen, Lars
Retrofit in Industrial Production: Digitization of Existing SystemsTBMG-5353208/01/2025
Development of a SaaS Platform for Fleet Management2025-36-033108/01/2025
Technological solutions to monitor and manage fleets are important to increase efficiency and reduce cargo transport costs. This work presents a SaaS (Software as a Service) platform for fleet management, aimed at optimizing operational efficiency and improving vehicle safety. It distinguishes itself as an innovative solution by integrating various functionalities related to cargo transport into a unified environment. The platform allows for route tracking, with different alert notifications generated from sensors, virtual geographic fences, driver identification, and smart cameras. Tire management is another critical aspect that encompasses the unique identification of each tire and its association with vehicles, along with monitoring data such as mileage, speed, temperature, pressure, tread wear, retreading, and performance based on distance traveled. Alerts for tire rotation, tread depth measurements, and excessive tread wear enhance performance management, while key performance
Fonseca, Murilo L., Mochiutti, Eric, Rosa, Rodrigo K., Benczik, Paulo H., Gonçalves, Vitor M., Zanolli, Willians S.
Increasing Wear Strength and Life Cycle of Tamping Machine Tool by Silicon Carbide Coating for Railway Maintenance05-19-02-001106/19/2025
When a train passes continuously over a section of the track, the track gradually moves away from the intended vertical and horizontal alignment with time and repeated use. Regular maintenance on the track, such as leveling, lifting, lining, and tamping, is necessary to maintain the optimal geometry of the track. Ballast is leveled and squeezed by hydraulic rams in tamping machines. The tamping is a process of ballast packing under railway tracks. In current system a set of tungsten carbide chips are attached either by welding or by coating on tamping tool tip made of EN24 steels. These tungsten carbide chips directly come in contact with the ballasts. After few tamping works, gradually these chips torn out and need to be replaced after certain period. Tungsten carbide is a costly material, therefore this research deals with replacement of tungsten carbide with silicon carbide (easily available cheaper) coating used for tamping tools tip. The study consists of microstructural
Mishra, Mamta, Pandey, Manas, Singh, Shruti, Srivastava, Sanjay, Kumar, Jitendra
A Machine Learning–Based Predictive Modeling for Optimizing the Critical Useful Life of Aeroengines: A Field Maintenance Perspective01-18-02-000906/19/2025
Establishing critical useful life plays a central role to determine aeroengine health status including aeroengine parameter changes from adverse material conditions or metal fatigue. The useful life assessment serves to support maintenance teams by enabling predictive maintenance followed by part replacement or conditions improvement. The proposed research works to improve the ability of turbofan aeroengine useful life estimation while targeting practical deployment during maintenance operations at field locations. A field maintenance–oriented ensemble bagged regression model for aeroengines represents the proposed method within this research. The present study reaches an error index of 7.06 with 98.95% model fitness when applying it to critical useful life training data. The projected model received its validation through experiments on test and field datasets. Field tests revealed that among 25 machine learning models the proposed model delivered optimal results since its error index
Singh, Shaktiyavesh Nandan Pratap, Shringi, Rohitashwa, Chaturvedi, Manish, Kumar, Ajay
Cobots Repair and Refurbish Electronic Appliances for a Sustainable FutureTBMG-5321306/01/2025
Repartly, a startup based in Guetersloh, Germany, is using ABB’s collaborative robots to repair and refurbish electronic circuit boards in household appliances. Three GoFa cobots handle the sorting, visual inspection and precise soldering tasks enabling the company to enhance efficiency and maintain high quality standards.
Soft Sensing, Self-Healing Materials for Robotic Hands and ArmsTBMG-5323206/01/2025
Low-cost jelly-like materials, developed by researchers at the University of Cambridge, can sense strain, temperature, and humidity. And unlike earlier self-healing robots, they can also partially repair themselves at room temperature.
SAE TOMORROW TODAY - How Autonomy is Breathing New Life into Farming1351505/19/2025
Labor shortages are pushing many family farms to the brink. The solution? Autonomous technology which is emerging as a game-changer--boosting productivity, cutting risk, and giving family farms a fighting chance to thrive for generations to come. At the forefront of this transformation is Blue River Technology, a John Deere subsidiary leading the charge in precision agriculture. From AI-driven tools to autonomous machinery, the company is helping to build the future of farming the John Deere way, meeting farmers in the field and designing solutions grounded in real-world challenges. With safety and scalability built in, farmers can start small with retrofit kits that upgrade existing tractors, making automation more accessible than ever. To learn more, we caught up with Aaron Wells, Director of Engineering at Blue River, to explore how automation is transforming agriculture and giving farmers the tools they need to stay ahead--despite labor challenges. We'd love to hear from you. Share
Hineman, Marcie
Feasibility of In-Situ Vehicle-Level Sound Transmission Loss Measurement to Guide Dash Pass-Through Grommet Selection2025-01-012205/05/2025
Noise transmission through the vehicle dash panel plays a critical role in isolating passengers from noise sources within the motor bay of the vehicle. Grommets that contain electrical harness routing as well as HVAC lines are examples of dash panel pass-throughs that should be selected with care. Acoustic performance of these components is generally characterized in terms of measured quantities such as noise reduction (NR), sound transmission loss (STL), and insertion loss (IL). These measurements need to be carried out per SAE or ASTM standards in appropriate anechoic or reverberant chambers as this is important for consistency. This work explores an in-situ measurement of the grommet STL performance in the vehicle environment. It utilizes a repurposed vehicle with its cabin retrofitted to serve as an anechoic chamber and its frunk acting as a reverberant chamber. Results of this in-situ measurement are then compared to measurements following industry standards to discuss the
Joodi, Benjamin, Jayakumar, Vignesh, Chang, Michael, Geissler, Christian, Pilz, Fernando, Conklin, Chris
Segment Manipulator Retrofit2025-01-015905/02/2025
The segment manipulator machine, a large custom-built apparatus, is used for assembling and disassembling heavy tooling, specifically carbon fiber forms. This complex yet slow-moving machine had been in service for nineteen years, with many control components becoming obsolete and difficult to replace. The customer engaged Electroimpact to upgrade the machine using the latest state-of-the-art controls, aiming to extend the system's operational life by at least another two decades. The program from the previous control system could not be reused, necessitating a complete overhaul.
Luker, Zachary, Donahue, Michael
Enhancing Airworthiness Security: SysML-Based Approach to Modelling Security Scope Definitions2025-01-017205/02/2025
Airworthiness certification of aircraft requires an Airworthiness Security Process (AWSP) to ensure safe operation under potential unauthorized interactions, particularly in the context of growing cyber threats. Regulatory authorities mandate the consideration of Intentional Unauthorized Electronic Interactions (IUEI) in the development of aircraft, airborne software, and equipment. As the industry increasingly adopts Model-Based Systems Engineering (MBSE) to accelerate development, we aim to enhance this effort by focusing on security scope definitions – a critical step within the AWSP for security risk assessment that establishes the boundaries and extent of security measures. However, our findings indicate that, despite the increasing use of model-based tools in development, these security scope definitions often remain either document-based or, when modeled, are presented at overly abstract levels, both of which limit their utility. Furthermore, we found that these definitions
Hechelmann, Adrian, Mannchen, Thomas
Material Adapted Method for the Repair of Curved Thermoplastic Composite Structures by Induction Welding of Patches2025-01-016505/02/2025
Thermoplastic fiber-reinforced polymer composites (TPC) are gaining relevance in aviation due to their high specific strength, stiffness, potential recyclability and the ability to be repaired thanks to their meltability. To maximize their potential, efficient repair methods are needed to maintain aircraft safety and structural integrity. This article introduces a novel repair technique for damaged TPC structures, involving the joining of a repair patch with induction welding using a susceptor material. The susceptor consists of a material with high electrical conductivity and magnetic permeability and therefore reacts stronger to the electromagnetic field than the composite, even if the composite is carbon fiber based. I. e. the thermal energy is specifically concentrated in the repair area. In this study, the susceptor was placed on the patch and also in the welding zone. The repair process begins by identifying and preparing the damaged area, followed by precise scarfing. Care is
Geiger, Markus, Glaap, Anton, Schiebel, Patrick, May, David
3D Printing Parts for Ships, Submarines and Underwater Vehicles25AERP05_0105/01/2025
Additive manufacturing has been a game-changer in helping to create parts and equipment for the Department of Defense's (DoD's) industrial base. A naval facility in Washington state has become a leader in implementing additive manufacturing and repair technologies using various processes and materials to quickly create much-needed parts for submarines and ships. One of the many industrial buildings at the Naval Undersea Warfare Center Division, Keyport, in Washington, is the Manufacturing, Automation, Repair and Integration Networking Area Center, a large development center housing various additive manufacturing systems.
Management, Repair, and Overhaul: Vol. 2EPRCOMPV08202404/30/2025
Reeve, Tammy, Phillips, Paul
Air Conditioning Service Procedures for Off-Road Work Machines and Agricultural Tractors Using HFC-134a or HFO-1234yf RefrigerantJ3126_202504 (Historical)04/14/2025
This SAE Recommended Practice is intended to provide technicians with safe and efficient techniques and general equipment recommendations for servicing mobile air conditioning systems in off-road, self-propelled work machines as defined in SAE J1116 and tractors and machinery for agriculture and forestry as defined in ASABE standard ANSI/ASAE S390. Both refrigerants HFC-134a (R-134a) and HFO-1234yf (R-1234yf) are covered. Many service procedures are similar for both refrigerants, but recovery, recycling, charging, and electronic leak detection tools can be unique to each refrigerant.
HFTC6, Operator Accommodation
SAE TOMORROW TODAY UNPLUGGED - The Fragmentation of the Robotaxi Market1351004/10/2025
The robotaxi market is experiencing significant change, with the once-dominant Waymo now facing competition from new entrants like Nuro and Wayve who are licensing their autonomous driving technology -- a strategy that could reshape the industry. In addition, Tesla's Cybercab is aiming to launch a commercial service by the end of 2025 that allows owners to generate revenue through the Tesla network. Lyft and Uber are also adapting through the power of partnership, emphasizing the importance of fleet management in the operation and maintenance of robotaxis. In this Unplugged episode of SAE Tomorrow Today, host Grayson Brulte breaks it all down and discusses how the impact of a fragmented market will likely result in a convergence of personally owned AVs, traditional robotaxis, and niche players. 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
Hineman, Marcie
Next-Gen Italian Urban Mobility: Emissions LCA and TCO Prospective for Innovative Transportation Solutions2025-01-859304/01/2025
Reducing vehicle numbers and enhancing public transport can significantly cut emissions in the transport sector. Hydrogen-fueled and battery electric buses show the potential for decarbonization, but a Life Cycle Assessment (LCA) is essential to evaluate carbon emissions from energy production and manufacturing. In addition, even associated pollutant emissions, together with components’ wear, must be taken into account to evaluate the overall environmental impact. Total Cost of Ownership (TCO) analysis complements this by assessing long-term expenses, enabling stakeholders to balance environmental and economic considerations. This study examines carbon and pollutant emissions alongside TCO for innovative urban mobility powertrains (compared with diesel), focusing on Italian current and future hydrogen and electricity mix scenarios, even considering 100 % green hydrogen (100GH), the goal being to support sustainable decision-making and to promote eco-friendly transport solutions. The
Brancaleoni, Pier Paolo, Damiani Ferretti, Andrea Nicolò, Corti, Enrico, Ravaglioli, Vittorio, Moro, Davide
Decoding User Experience: A Study of Public EV Charging Stations Based on Amap Comments2025-01-811504/01/2025
The rapid expansion of the electric vehicle (EV) market has intensified the need for robust charging infrastructure. The quality of their experiences at public charging stations has become crucial to sustaining this transition. Key factors such as station accessibility, charging speed, and pricing transparency significantly affect user satisfaction. In Guangzhou, a China's major metropolitan city with an EV penetration rate exceeding 50%, this city offers an ideal context to assess the alignment between expanding EV infrastructure and user needs. This study examines user satisfaction with EV public charging stations in Guangzhou using a dataset of over 2,000 user comments from Amap. The comments are first processed using the Jieba segmentation library, with sentiment analysis conducted through the Natural Language Processing tool SnowNLP, categorizing comments by sentiment (419 positive, 156 neutral, and 1,690 negative). Term Frequency-Inverse Document Frequency(TF-IDF) is then applied
Guo, Haifeng, Ou, Shiqi (Shawn), Jing, Hao, Qi, Hao, Shi, Lanxin
Enhancing Tire Predictive Maintenance with Next-Generation TPMS Sensors2025-01-875904/01/2025
This paper presents findings on the use of data from next-generation Tire Pressure Monitoring Systems (TPMS), for estimating key tire states such as leak rates, load, and location, which are crucial for tire-predictive maintenance applications. Next-generation TPMS sensors provide a cost-effective and energy-efficient solution suitable for large-scale deployments. Unlike traditional TPMS, which primarily monitor tire pressure, the next-generation TPMS used in this study includes an additional capability to measure the tire's centerline footprint length (FPL). This feature offers significant added value by providing comprehensive insights into tire wear, load, and auto-location. These enhanced functionalities enable more effective tire management and predictive maintenance. This study collected vehicle and tire data from a passenger car hatchback equipped with next-generation TPMS sensors mounted on the inner liner of the tire. The data was analyzed to propose vehicle-tire physics
Sharma, Sparsh, Son, Roman
Designing Software for SAE J1939 ECUs to Improve Cybersecurity2025-01-808204/01/2025
SAE J1939 is a CAN-based standard used for connecting various ECUs together within a vehicle. There are also some related protocols sharing many of the features of SAE J1939 across other industries including ISO11783, RVC and NMEA 2000. The standard has enabled the easy integration of electronic devices into a vehicle. However, as with all CAN-based protocols, several vulnerabilities to cyberattacks have been identified and are discussed in this paper. Many are at the CAN-level, whilst others are in common with those protocols from the SAE J1939 family of protocols. This paper reviews the known vulnerabilities that have been identified with the SAE J1939 protocol at CAN and J1939-levels, along with proposed mitigation strategies that can be implemented in software. At the CAN-level, the weaknesses include ways to spoof the network by exploiting parts of the protocol. Denial of Service is also possible at the CAN-level. At the SAE J1939-level, weaknesses include Denial of Service type
Quigley, Christopher
Telematics-Based Managed EV Charging: A Pilot Case Study for Utility Bulk and Distribution Grid Services2025-01-812204/01/2025
Growth in the EV market is resulting in an unprecedented increase of electrical load from EV charging at the household level. This has led to concern about electric utilities’ ability to upgrade electrical distribution infrastructure at an affordable cost and sufficient speed to keep up with EV sales. Adoption of EVs in the California market has outpaced the national average and offers early insight for other regions of the United States. The Sacramento Municipal Utility District (SMUD) partnered with two grid-edge Distributed Energy Resource Management System (DERMS) providers, the OVGIP (recently incorporated as ChargeScape, a joint venture of Ford, BMW, Honda, and Nissan) and Optiwatt, to deliver a vehicle telematics-based active managed charging pilot. The pilot program, launched in Summer 2022 enrolled approximately 1,200 EVs over two years including Tesla, Ford, BMW, and GM vehicles. The goal of this pilot program was to evaluate the business case for managed charging to mitigate
Liddell, Chelsea, Schaefer, Walter, Dreffs, Kora, Moul, Jacob, Kay, Carol, Aswani, Deepak
Machine Learning-Based Digital Twin for Optimizing Automotive Components2025-01-820604/01/2025
This paper presents a Digital Twin approach based on Machine Learning (ML), aimed at creating software-based sensors to reduce the auxiliary devices of the vehicle and enabling predictive maintenance, thus reducing carbon footprint. The solution is applied to the electric Lubrication Oil Pump (eLOP), a crucial component within a vehicle's powertrain system. The proposed eLOP Digital Twin integrates ML-based sensors to estimate critical parameters such as temperature, pressure and flow rate, reducing the reliance on physical sensors and associated hardware. This approach minimizes manufacturing complexity and cost, enhancing energy efficiency during both production and operation. Furthermore, the Digital Twin facilitates predictive maintenance by continuously monitoring the component's performance, enabling early detection of potential failures and optimizing maintenance schedules. This leads to lower energy consumption and reduced emissions throughout the component's lifecycle. The
Khan, Jalal, D'Alessandro, Stefano, Tramaglia, Federico, Fauda, Alessandro
Matchit: A Domain-Adaptable Information Extraction and Categorization Tool for Enhanced Decision Making2025-01-810704/01/2025
This paper presents Matchit, a novel method for expediting issue investigation and generating actionable insights from textual data. Recognizing the challenges of extracting relevant information from large, unstructured datasets, we propose a domain-adaptable approach by integrating expert domain knowledge to guide Large Language models (LLMs) to automatically identify and categorize key information into distinct topics. This process offers two key functionalities: fully automatic topic extraction based solely on input data, providing a concise overview of the problem and potential solutions, and user-guided extraction, where domain experts can specify the type of information or pre-defined categories to target specific insights. This flexibility allows for both broad exploration and focused analysis of the data. Matchit's efficacy is demonstrated through its application in the automotive industry, where it successfully extracts repair diagnostics from diverse textual sources like
Wang, Lijun, Arora, Karunesh
Kalmar launches 3rd-gen electric terminal tractor25TOFHP04_1004/01/2025
Electric vehicle (EV) growth may be stagnant in certain market sectors amid pushback on EV mandates along with lingering infrastructure and TCO concerns, but in terminal tractor operations electrification is growing in demand. As part of its initial Run on Less - Electric demonstration, the North American Council for Freight Efficiency (NACFE) concluded that terminal tractors are “one of the best, if not the best, paths for heavy-duty tractor fleets to learn about and implement a BEV in a fleet operation.” Fleets operating in ports, intermodal yards and other logistics hubs have a new option from which to choose now that Kalmar officially began sales of its Ottawa T2 EV electric terminal tractor. The order book opened at the Technology & Maintenance Council's (TMC) 2025 Transportation Technology Exhibition in Nashville, Tennessee, in March. Kalmar states that select customers have already placed preorders. Initial deliveries will begin in Q2 2025.
Gehm, Ryan
Advancing Oil Maintenance Practices: Insights from Viscosity Analysis2025-01-501903/21/2025
There is a lack of data to support the efficacy of traditional mileage and time-based criteria for oil changes in vehicles. In this study, used-oil samples from 63 vehicles were collected and analyzed. Besides dynamic viscosity, viscosity index and activation energy were evaluated as measures of thermal stability of viscosity. The results revealed that mileage and time of use are not significantly correlated with (p > 0.05) and are thus poor indicators of oil viscosity and viscosity thermal stability measures. These findings highlight the limitations of current criteria and underscore the need for new sensing and evaluation methods to reduce costs, waste, and environmental impact while ensuring vehicle performance.
Salvi, Nilesh, Tan, Jinglu
Traffic Event Extraction and Geographization from Natural Language Web Text2025-01-721303/19/2025
Real-time traffic event information is essential for various applications, including travel service improvement, vehicle map updating, and road management decision optimization. With the rapid advancement of Internet, text published from network platforms has become a crucial data source for urban road traffic events due to its strong real-time performance and wide space-time coverage and low acquisition cost. Due to the complexity of massive, multi-source web text and the diversity of spatial scenes in traffic events, current methods are insufficient for accurately and comprehensively extracting and geographizing traffic events in a multi-dimensional, fine-grained manner, resulting in this information cannot be fully and efficiently utilized. Therefore, in this study, we proposed a “data preparation - event extraction - event geographization” framework focused on traffic events, integrating geospatial information to achieve efficient text extraction and spatial representation. First
Hu, Chenyu, Wu, Hangbin, Wei, Chaoxu, Chen, Qianqian, Yue, Han, Huang, Wei, Liu, Chun, Fu, Ting, Wang, Junhua
The Logistic Lasso and Ridge Regression Algorithm-Based Airline Passenger Satisfaction Prediction Model2025-01-716803/19/2025
Airline passenger satisfaction is important for airline operation service quality management. When airline companies carry out advertisement campaigns or plan a marketing strategy, the resources and budgets are not unlimited. Thus, an airline can only focus on improving a few factors that drive passenger satisfaction. To understand the key satisfies for the young and the old adults, respectively, we leverage five airline passenger satisfaction methods to identify the key factors that explain the airline service satisfaction of different passengers. In particular, we investigate and compare the ridge and the Lasso regularization in terms of the resulting model’s sparsity and computational efficiency. The top three important factors that influence the old’s satisfaction are departure and arrival time convenience, legroom service, and baggage handling. Our findings indicate that the young people place a higher value on entertainment, while the old adults place a higher value on usefulness
Ma, Jie, Hu, Song, Wang, Haipeng
Isolation and Corrosion Protection of Dissimilar Materials, Carbon Composite Structure RepairARP4118C (Current)03/05/2025
This SAE Aerospace Recommended Practice (ARP) provides methods and guidelines for isolating dissimilar repair patch materials from carbon fiber reinforced plastic (herein also referred to as carbon composite) structure during a repair operation.
AMS G9 Aerospace Sealing Committee
Synthetic On-Board Diagnostics Data Generation and Evaluation for Vehicle Diagnostic Testing2025-01-501003/04/2025
The generation of data plays a vital role in machine learning (ML) techniques by providing the foundation for training and improvement of forecast models. As one application area for these models, in-vehicle systems, like vehicle diagnostics, have the potential to enhance the reliability and durability of vehicles by utilizing ML models in the testing phases. However, acquiring a high volume of quality onboard diagnostics (OBD) data is time-consuming and poses challenges like the risk of exposing sensitive information. To address this issue, synthetic data generation offers a promising alternative that is already in use in other domains. Thereby, synthetic data allows the exploitation of knowledge found in original data, ensuring the privacy of sensitive data, with less time costs of data acquisition. The application of such synthetically generated data could be found in predictive maintenance, predictive diagnostics, anomaly detection, and others. For this purpose, the research
Vučinić, Veljko, Hantschel, Frank, Kotschenreuther, Thomas
R-1234yf Service Hose, Fittings, and Couplers for Mobile Refrigerant Systems Service EquipmentJ2888_202502 (Current)02/25/2025
This SAE Standard covers fittings, couplers, and hoses intended for connecting service hoses from mobile air-conditioning systems to service equipment such as charging, recovery, and recycling equipment (see Figure 1). This specification covers service hose fittings and couplers for MAC service equipment service hoses, per SAE J2843 and SAE J2851, from mobile air-conditioning systems to service equipment such as manifold gauges, vacuum pumps, and air-conditioning charging, recovery, and recycling equipment.
Interior Climate Control Service Committee
Intelligent Pavement Maintenance Optimization Technique for Automatic Driving2025-01-715302/21/2025
Compared to manual driving, autonomous driving is more prone to the rapid development and deterioration of pavement distress due to the concentration of driving paths. Therefore, a reasonable and efficient maintenance strategy is required. To address the challenges posed by the numerous constraints and objectives in the maintenance strategy generation process, this paper proposes a multi-objective optimization-based method for generating pavement maintenance strategies. The approach leverages advanced pavement distress detection technologies to establish an initial maintenance program, incorporating a range of constraints and maintenance objectives, such as cost-efficiency, performance longevity, and environmental impact. The method applies a genetic algorithm (GA) to iteratively refine and optimize the maintenance strategy, ensuring that the solutions align with both immediate and long-term performance goals for autonomous vehicle operations. A case study utilizing real-world road
Yang, Liwenyun, Li, Wei, Chen, Leilei
Maintenance Scheduling Optimization of Urban Non-intrusive Road Intelligent Transportation System Equipment under the Autonomous Driving Environment2025-01-714802/21/2025
The increasing traveling demands are putting higher pressure on urban networks, where the efficient driving modes highly depend on various non-intrusive ITS equipment for interaction, which asks for higher maintenance scheduling plans minimizing network loss. Current studies have researched methodologies with the aspects of deterministic methods and metaheuristic algorithms under different scenarios, but lack the simulation considering maintenance work type, urban traffic characteristics as well as the ITS equipment. This study aims to optimize the maintenance scheduling plan of urban ITS systems by using the genetic algorithm (GA) and Dijkstra algorithm, as well as other judgmental algorithms to minimize traffic delays caused by maintenance activities, and presents a novel method to assess economic losses. A mixed integer programming model is established simulating the real urban network while considering multiple constraints, including the route selection principle, network updating
Pei, Haoyi, Ji, Yanjie, Chen, Ziang
Modeling Internal Node Impedance in High-Speed Rail Passenger Hubs Based on Queuing Theory2025-01-717202/21/2025
High-speed railway (HSR) hubs play a pivotal role in the integrated transport system, efficiently connecting various modes of transport and facilitating transport integration. Characterized by their large scale, complex functional spatial layouts, and diverse interchange types, these hubs see a growing proportion of passenger traffic annually. Thus, studying the interchange impedance in high-speed railway passenger transport hubs is crucial for enhancing interchange efficiency and service quality. However, current research lacks a quantitatively comparable impedance model for high-speed railway hubs, particularly under peak passenger flow conditions. This paper addresses this gap by examining the internal node impedance at Nanjing South Railway Station, focusing on the entry gate turnstile node and security check node. It begins by analyzing passenger passing behavior at these nodes and then constructs a integrated queuing model for inbound gates and security checks, considering the
Zhang, Zhenyu, Wang, Jian
Research on Triple-Frequency Dual-Ionosphere-Free Combination PPP Based on PPP-B2b Service2025-01-715702/21/2025
The recent public release of the PPP-B2b service, along with advancements in multi-frequency and multi-GNSS systems, has opened up significant new opportunities for the development of Precise Point Positioning (PPP) technology. Utilizing the precise orbit and clock corrections provided by PPP-B2b and the increasing availability of multi-frequency signals, this paper introduces a novel tri-frequency, dual ionosphere-free PPP model based on PPP-B2b services. The model is designed with twelve unique tri-frequency combinations, tailored to various frequency choices, combination methodologies, and single/dual GNSS systems. Results from static positioning experiments indicate that the BDS-only tri-frequency dual ionosphere-free model offers substantial improvements over traditional models. Specifically, it achieves approximately a 25% increase in vertical accuracy and reduces convergence time by around 30% when compared to the BDS-only tri-frequency undifferenced uncombined model. This
Xu, Dawei, Gao, Chengfa, Xu, Zhenhao, Zhan, Kaidi, Guo, Songlin
Classification of Pavement Distress Images Using Fusion Convolutional Neural Network of Dual Branch2025-01-713102/21/2025
In recent years, the issue of highway maintenance has become increasingly prominent. How to precisely detect and classify fine cracks and various types of pavement defects on highways through technical means is an essential foundation for achieving intelligent road maintenance. This paper first constructs the DenseNet201-PDC and MobileNetV2-PDC sub-classification networks that incorporate the three-channel attention judgment mechanism MCA. Secondly, based on the principle of parallel connection, a brand-new dual-branch fusion convolutional neural network DBF-PDC capable of classifying pavement defects in highway scenarios is proposed. Finally, this paper builds the Pavement Distress Datasets of Southeast University and conducts relevant ablation experiments. The experimental results demonstrate that both the attention mechanism module and the feature fusion strategy can significantly enhance the network's ability to classify pavement defects in highway scenarios. The average
Zhang, Ziyi, Zhao, Chihang, Shao, Yongjun, Wang, Junjun
Tunnel Lining Crack Intelligent Recognition Based on YOLOv11 Algorithm2025-01-713702/21/2025
Tunnel linings are an important safeguard for the integrity and stability of tunnels. However, cracks in the tunnel lining may have extremely unfavourable consequences. With the acceleration of urbanisation and the increasing construction of tunnels, the problem of cracks in the concrete lining is becoming more and more prominent. These cracks not only seriously affect the stability of the structure, but also pose a serious threat to the safety of tunnel operation. If left unchecked, the cracks may expand further and cause various safety hazards, such as water leakage and falling blocks. This in turn will undermine the normal function of the tunnel and endanger the lives of tunnel users. It has been proved that the traditional manual method of detecting cracks in tunnels has problems such as low accuracy and low efficiency. In order to solve this problem, it is very necessary for this study to pioneer an intelligent method for identifying tunnel lining cracks using the YOLOv11
Zhang, Yalin, Niu, Pei, Guo, Feng, Yan, Wei, Liu, Jian, Kou, Lei
REPAIR SLEEVE, LARGE WIRE/CABLE INSULATION DAMAGE, ELECTRIC, PERMANENT, ENVIRONMENT RESISTANT, 260 °C MAXIMUM OPERATING TEMPERATURE, TYPE IIAS6224/2A (Current)02/07/2025
AE-8C2 Terminating Devices and Tooling Committee
Atomic Fountain for Research in Quantum Sensing Nears Completion of First PhaseTBMG-5252202/01/2025
Using a Defense University Research Instrumentation Program (DURIP) award bestowed last year and plenty of elbow grease, Dr. Frank Narducci, Chair of the NPS Department of Physics, and his Ph.D. student U.S. Navy Cmdr. Jens Berdahl, a former Navy pilot currently pursuing his doctorate through the service’s Permanent Military Professor program, are nearing completion of the first phase of construction in what will be a superlatively precise atomic-based instrument.
SAE TOMORROW TODAY: Launching Human Space Travel with a Luxury Balloon1349801/23/2025
Imagine a six-hour journey to outer space that includes a world-class meal, cocktail service, Wi-Fi, and unprecedented views of Earth. This experience could soon become reality. Space Perspective, the world's first carbon-neutral spaceflight experience company, is commercializing space travel with Spaceship Neptune, a pressurized capsule propelled by a giant SpaceBalloon(TM). The experience is designed to be gentle and accessible with no rockets, weightlessness, heavy g-forces, or training required. Alongside world-class meal and cocktail service, space travelers will also enjoy views through the largest windows ever flown to space, Wi-Fi, and a proper restroom. To learn more, we sat down with Taber MacCallum, Founder and Chief Technology Officer, Space Perspective, to discuss the technical development of the SpaceBalloon(TM) and how the company is unlocking the market for space travel in a new and innovative way. We'd love to hear from you. Share your comments, questions and ideas for
Hineman, Marcie
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