Browse Topic: Maintenance and Aftermarket

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Enabling Sustainable E-Mobility: An Edge–Cloud Collaborative Framework for Battery Lifecycle Health Management in Electric Vehicles2026-01-0460To be published on 04/07/2026
The rapid adoption of electric vehicles (EVs) is a cornerstone of the transition to sustainable transportation. However, uncertainty regarding battery degradation remains a significant obstacle, hindering vehicle energy efficiency, operational safety, and the recovery of end-of-life value. Accurate estimation of the battery state of health (SOH) and prediction of the remaining useful life (RUL) are therefore critical for sustainable vehicle lifecycle management. This study proposes an edge–cloud collaborative intelligent framework for in-vehicle deployment that leverages a Transformer-based architecture to jointly model SOH and RUL. The cloud-side model retains the full configuration to capture long-term degradation trajectories for high-accuracy RUL prediction. A lightweight edge-side model, engineered via pruning and knowledge distillation, delivers millisecond-level inference for real-time SOH estimation onboard the vehicle. To ensure efficiency, only four core health indicators are
Gao, Weimin, Lv, Zhilong, Ou, Shiqi(Shawn)
An Efficient Approach to Key Negotiation in an Automotive Environment2026-01-0087To be published on 04/07/2026
Negotiating Keys for applications such as message authentication within a vehicle presents many problems as, in designing the algorithm; the algorithm must be able to be utilized by small, fixed-point processors. In addition, if there is a desire to do this algorithm in the manufacturing environment, there are severe time constraints placed on how long this algorithm can take, as there are strict station time requirements, which are expensive to change, and any time utilized in the plant can negatively affect vehicle throughput. Additionally, negotiating these keys between many ECUs can greatly increase the time required to negotiate a common key using standard multi-party Diffie-Hellman. Timing would also be an issue in the case of using pair-wise Diffie-Hellman for encryption and distribution of keys utilizing a key master. To solve these problems in multi-party key negotiation, we have utilized the Elliptic Curve variation of the Burmester-Desmedt (ECBD) algorithm. ECBD is
Van Dam, Theo, Mazzara, Bill
Development and Application of SAE J3260 & J3290 Recommended Practice for Minimizing Spread of Infections in Motor Vehicles2026-01-0128To be published on 04/07/2026
In response to COVID pandemic, and at the persistent urging of the late Ward Atkinson, long-time SAE leader in Interior Climate Control Committees, the SAE Cabin Disinfection Practices Committee was formed in May 2021. Towards that end, two SAE J-standards have been produced by this committee: SAE J3260, Identification of Acceptable Cleaning and Disinfection Products for Vehicle Interior Surfaces and Exterior Touch Points, and SAE J3290, Selection and Use of Technologies and Methods for Vehicle Cabin Air Disinfection. This SAE paper will unpack the background and application of these J-Standards to minimize the probability of spreading of infection during the operation of motor vehicles while in normal operation, before and after vehicle servicing, and when in use as paid-for-hire operation - for both ‘normal’ environmental conditions, and during times of pandemic emergencies. Additionally, recent advances in air and surface disinfection technologies—including methods relevant to SARS
Schaeber, Steven, Mathur, Gursaran, Taylor, Dwayne
A Quantitative Approach for Mapping and Assessing Diesel Particulate Filter Regeneration Events in Diesel Engines2026-01-0377To be published on 04/07/2026
Regeneration of diesel particulate filters (DPFs) is crucial for maintaining the performance of diesel engines and minimizing harmful particulate matter (PM) emissions from exhaust. However, conventional regeneration strategies often suffer from incomplete soot removal and inefficient monitoring. These issues lead to increased exhaust back pressure, reducing engine efficiency, and potentially damaging the particulate filter. In this paper, a new approach is proposed for mapping and quantifying the real-world DPF regeneration process for diesel engines complying with the stringent emission standards. We introduce a novel metric, the differential pressure drop percentage (DPDP), to detect regeneration events and quantify soot burn quality. The proposed method utilizes real-time sensor data obtained through the vehicle’s On-Board Diagnostics (OBD) system. The algorithm processes sensor data and robustly maps the regeneration quality. The performance of regeneration event detection and
Bagga, Harleen Kaur, Nagare, Mukund B., Patil, Bhushan D., Ravishankar, Hariharan, Melapudi, Vikram, Patil, Abhijit
Optimal Vehicle Sampling for Fleet-Wide Emissions Monitoring using Submodular Maximization2026-01-0283To be published on 04/07/2026
This article addresses the problem of optimal vehicle sampling for fleet-wide in-use emissions monitoring, a necessity driven by the absence of direct emissions sensors in modern production vehicles and the variable impact of in-use changes and operational factors (mileage, time-in-service, workload) on emissions performance across a fleet. Recognizing that comprehensive fleet testing is impractical due to significant downtime and cost, we propose a novel approach to identify a small, yet optimally informative subset of vehicles for sampling. The proposed approach leverages submodular function maximization, a technique rooted in optimal experimental design, specifically D-optimal design, to maximize the determinant of the information matrix (e.g., of $X^TX$, where $X$ is the regressor/design matrix in the case of a linear in parameters model). This approach ensures that the collected data yields maximum information for refining and building accurate models for emissions characteristic
ZHANG, JIADI, Li, Xiao, Kolmanovsky, Ilya, Tsutsumi, Munecika, Nakada, Hayato
A Shared Autonomy Architecture: Utilizing an Advanced Personalized Control System (APeCS) and Shared Autonomy Arbiter (SAB)2026-01-0147To be published on 04/07/2026
The shared autonomy framework has become an option with great potential in the field of autonomous vehicles. Human and machine control decisions typically demonstrate strengths in different scenarios. As a result, the robustness of systems can be enhanced by the collaboration between humans and autonomy. A shared autonomy architecture that takes into account both human and environmental factors was proposed in this work. The authority distribution between the human operator and the autonomy algorithm was determined by the Shared Autonomy Arbiter (SAB). Designed with a two-tier structure, the SAB incorporated a policy-level decision module, as well as a numerical-level arbitration tuning module. A fuzzy inference system (FIS) was incorporated to enhance the noise tolerance of the policy selection module. Furthermore, the human factor was taken into account by applying a projection to the users’ control input. The human operator’s control decision was projected by the Adaptive
Sang, I-Chen, Norris, William, Patterson, Albert, Sreenivas, Ramavarapu S., Soylemezoglu PhD, Ahmet, Nottage, Dustin S.
Vehicle Health Monitoring and Failure Prognosis through Edge-Based Component Wear Tracking2026-01-0094To be published on 04/07/2026
Traditional vehicle maintenance has relied primarily on mileage-based schedules and periodic visual inspections, approaches that often fail to account for variations in driving conditions, component quality, and usage patterns. These conventional methods typically result in either unnecessary premature replacements or unexpected component failures, leading to increased operating costs and unplanned downtime. Reactive maintenance strategies prove particularly problematic for critical wear components like clutch assemblies, brake systems, and suspension parts where undetected degradation can cause secondary damage. This paper presents an advanced monitoring system that shifts from scheduled maintenance to actual condition-based servicing through real-time wear measurement. The solution implements a network of distributed sensors that directly track critical parameters: ultrasonic measurement of clutch plate thickness, resistive wear sensors for brake pads, linear potentiometers for
Saraswat, Shubham, Vishe, Prashant
A Scalable and Accessible Remote Testing Framework for Automotive Development2026-01-0191To be published on 04/07/2026
With the rise of software-defined vehicles and the emergence of cyber threats to vehicular systems, developing teams are compelled to conduct extensive testing on both virtual and physical prototypes at an accelerated pace. This new development landscape necessitates diagnostic tools that are both precise and adaptable. However, proprietary systems dominate this field, often hindering accessibility for students and researchers due to high costs and restrictive licensing. This paper presents the design and implementation of an open-source, low-cost remote testing system tailored for automotive development and diagnostics. The proposed system utilizes Arduino and Raspberry Pi processing units, along with relay-based switching modules, to provide secure remote control of vehicle components through a web-based dashboard equipped with authentication, scheduling, and real-time synchronization capabilities. The tested prototype showcased robust scalability, secure session handling, and
Pries, Andrew, Mohammad, Utayba
Curb Impact: Non-linear structural FE analyses in Multibody Dynamics Models2026-01-0219To be published on 04/07/2026
In a few extreme customer abuse load cases such as Curb Impact and Potholes, automotive structures see non-linear (plastic) deformations as well as large rigid body motion. The load cases can be simulated by crash analysis tools such as LS-Dyna or multi-body dynamics analysis tools like Ansys Motion. The crash analysis has a better representation of structural compliances including large deformation with large rigid body motion. However, it requires a well-defined FE model and suspension multi-body models in detail. Furthermore, it takes a long time to get a result. On the other hand, the multi-body dynamics approach is very quick to get a result, while it has a limitation of representing structural compliance. The limitation is true in representing structural non-linearity such as large deformation associated with plastic yielding. In this study, a curb impact simulation was performed using the multi-body dynamic approach with nonlinear structural analysis capabilities included in
Hong, Hyung-Joo, Kim, Wangoo
Innovation Powered by High-Fidelity Multiphysics Modeling: A Holistic System Optimization of BorgWarner’s Next Generation Integrated Drive Modules2026-01-0497To be published on 04/07/2026
In the stringent market of BEV, the development of integrated Drive Modules (iDM) fitting to environmental and customer needs is mandatory. It is important to extract the best from the less. To achieve those goals, a deep insight of complex multiphysics phenomena occurring in an iDM has been achieved by accurate and validated models. This engineering methodology is applied through the development of BorgWarner products, comprising non-exhaustively iDM 180-HF, Externally Excited Synchronous Machine and Multi-Level Inverter. The paper will review the methodology development for deeper understanding involving in-house technical excellence and complemented by strategic partnerships with academic institutions and start-ups. It will present the approach of integrating advanced multiphysics models with high-quality experimental validations, specifically on loss evaluation on electrical machines and inverters. Complex models involving multiphysics such as thermal/fluid coupling or electric
Leblay PhD, Arnaud, Bossi, Adrien, Bourniche, Eric, DAVID, Pascal, Nanjundaswamy, Harsha
Energy Management Optimization of Sweepers Based on Working Conditions2026-01-0505To be published on 04/07/2026
Against the backdrop of the accelerating global transition to low-carbon development, the electrification of sweepers holds significant importance. Range-extended sweepers have emerged as a vital branch of new energy sanitation vehicles. Influenced by their service characteristics, these vehicles typically exhibit distinct features such as relatively fixed routes, concentrated operational areas, and highly regular working cycles. However, current range-extended sweepers employing conventional energy management strategies often demonstrate shortcomings: upon completing tasks such as sweeping and transportation, the battery State of Charge (SOC) frequently remains at an elevated level, leading to redundant energy waste. Meanwhile, the frequent start-stop cycles of the range extender during operations not only compromise the stability and service life of the power system but also reduce the overall utilization efficiency of battery energy. To address these issues, this study focuses on
Dong, Chenchen, Tan, Gangfeng, Wei, Haoting, Liu, Chongjian, Liu, Dan zhong
The Effects of Collision-Related Power Loss on Toyota Safety Sense 3.0 Event Data2026-01-0548To be published on 04/07/2026
Toyota vehicles equipped with Toyota Safety Sense (TSS) can record detailed information surrounding various driving events. Often, this data is employed in accident reconstruction to better understand the dynamics of a collision. TSS data is comprised of three main categories: Vehicle Control History (VCH), Freeze Frame Data (FFD), and image records. During an event, it is possible that a vehicle undergoes a catastrophic power loss from the damages sustained during the event. In this paper, the effects of a sudden power loss on the VCH, FFD, and images are studied. Events are triggered on a TSS 3.0 equipped vehicle by driving toward a stationary target. After system activation, a total power loss is induced, triggered on the instrument cluster “BRAKE” alert message, at various delays after activation. This testing studies various signals recorded across VCH, FFD and image data including vehicle speed, measured accelerations and time and date. This testing also compares the acceleration
Getz, Charles, Yeakley, Adam, DiSogra, Matthew
Fast and Robust CFD Simulation Method for Water Management in Automotive Interior Design2026-01-0487To be published on 04/07/2026
Knowledge of the behavior of fluid flow over and into narrow gaps is important in many industrial applications, particularly in the automotive sector. Evaluating the potential of water entering narrow pathways and towards components that can be damaged by it is of great importance. CFD simulations can help in evaluating the potential of water getting into such gaps. Meshless tools are used in a variety of simulation scenarios of fluid flow, especially due to their ability to easily simulate free surfaces with strong curvatures. In previous work, a validated simulation setup was created in the meshless simulation tool Meshfree from Fraunhofer ITWM for simulating water entering in small gaps. Currently, the simulation time of the setup needs to be sped up especially for industrial use cases, where simulation times higher than 6-10 days were encountered. Because of these long simulation times a fast and robust CFD simulation method was developed to be able to simulate even industrial use
Zrnic, Dino, Konstantinovics, Athena, Kospasch, Alexander, Rugerri, Evelyn, Loy, Michael, Bäder, Dirk, Michel, Isabel
Multi-material topology optimization using difference-based equivalent static load method2026-01-0173To be published on 04/07/2026
Topology optimization (TO) has become a powerful tool for generating lightweight structural designs. TO has been widely applied to linear static problems, where analytical sensitivities are easy to obtain. However, crashworthiness design requires nonlinear dynamic analysis, for which analytical sensitivities are generally not available. To extend TO into crash problems, approximation methods such as the Equivalent Static Load (ESL) method have been developed. ESL replaces the nonlinear problem with a series of linear static subproblems, ensuring that the displacement fields match at certain time steps. These subproblems can then be efficiently solved using standard TO techniques. A key limitation of ESL is that it relies on the initial mesh for all subproblems, which reduces accuracy for highly nonlinear crash responses. To address this, Triller proposed the difference-based ESL (DiESL) method, which updates the mesh in each subproblem to the deformed configuration, therefore improving
Huang, Yuhao, Kim, Il Yong
АNALYSIS CURRENY SITUATION IN TESTING, RELIABILITY/DURABILITY AND SAFETY OF ENGINEERING PRODUCT2026-01-0138To be published on 04/07/2026
This paper reviews the current situation with testing, reliability/durability and safety of engineering product, that leads to recalls increasing and efficiency decreasing. Considers: inconsistent quality control, and manufacturing standards; historical decline in build quality; design priorities: style over substance; emphasis on power and size; slow adoption of technological advancements; competition American with Japanese and European manufacturers. Briefly describes the system, which the author developed for dramatically decreasing recall number as a result of successful prediction of product efficiency. Demonstrates common strategy of this prediction, five steps for improving engineering product, and step-by-step sequential strategy, which can help to increase the automotive product test level, reliability, quality, safety, durability, maintainability and decrease their life-cycle cost.
Klyatis, Lev
Simulink DevOps Evolution: Bridging Interactive Platforms for Accelerated Model-Based Workflows2026-01-0080To be published on 04/07/2026
This paper builds on last year’s paper presenting DevOps automation in the context of model-based development. Following that paper, we interviewed Simulink users in passenger automotive, motorsports, commercial vehicles, aviation, rocketry, and industrial automation. We discovered that much of the benefit of DevOps platforms to reduce product development cycle time relies on their interactive features. We prototyped new tools to bridge interactive DevOps Git-based platforms with model-based development workflows, and then gathered reactions from another round of interviews. Here we present these interactive DevOps workflows with the feedback from these interviews to contextualize how engineering teams could adopt them to accelerate their own model-based workflows.
Mathews, Jon, Ferrero, Sergio, Tamrawi, Ahmed, Sauceda, Jeremias
The cure for overgrown process garden or why engineers have given up with ASPICE.2026-01-0067To be published on 04/07/2026
The useability of development processes in automotive decreased in the past years to a level at which their application and being able to benefit from them are questionable. Such degradation can be attributed to new additions to the processes and introduction of FUSA and Cybersecurity standards. The processes try to keep up with the shift from “plan-implement- test-roll out” to more agile methods. In addition, process departments, in charge of these processes, did not target the engineers as users of these processes, they focused on the compliance of processes and the assessor in the assessment. Due to reasons mentioned above, processes have grown in size and complexity which creates unnecessary overhead and forces the usage of complex tools to handle this overhead. Furthermore, the language of this process is written mostly in the language of the assessor, making them hard to understand for an average engineer. As a result, engineers are annoyed in their daily work and are not as
Weber, Matthias, Kmiec, Mateusz, Romijn, Marcel, Nedkov, Detelin
Optimizing Weld Placement in Automotive Structures Using Topology and Multi-Disciplinary Approaches2026-01-0514To be published on 04/07/2026
This work presents two approaches for weld optimization aimed at reducing manufacturing cost and process time, while meeting structural performance requirements in automotive structures. The first approach uses topology optimization to identify the most efficient weld layouts. A design space is generated along mating flanges, joints, and panel interfaces, where potential weld locations are defined. Welds are treated as discrete design variables, and the topology optimization systematically evaluates their contribution to global stiffness and load path integrity. Non-critical welds, those with minimal impact on stiffness, durability, or crashworthiness, are eliminated, resulting in a minimized weld pattern that maintains structural performance. The second approach applies Multi-Disciplinary Optimization (MDO) to balance weld reduction with performance targets across multiple domains, including linear and non-linear stiffness, crashworthiness, and fatigue. Using a preprocessing tool
Koppaka, Vinaya, Yoo, Dong Yeon, Chavare, Sudeep
Advanced Tire Looseness Identification through Algorithmic Gear Error Analysis and Probabilistic Assessment2026-01-0590To be published on 04/07/2026
At present, tire failures directly affect road safety, and the number of incidents caused by them is gradually increasing. Examining tire looseness on time is vital for vehicle safety. Tire-related incidents not only put people in peril but also have a detrimental effect on the economy. Therefore, the goal of this research is to develop a new and effective method for identifying tire looseness. A novel gear error reduction approach, distinct from traditional methods, combines advanced computing and probabilistic analysis. This paper involves three key components: extracting looseness eigenvalues, calculating ring gear errors, and computing the tire loosen probabilities. Gear errors derived from the Kalman filter and adjusted for speed, eigenvalues were calculated, and a tire loosening probability analysis was performed. Real-car trials across speeds and roads confirm its accuracy and reliability. This technology can improve automotive safety and maintenance, reducing accidents, claims
Zhao, Gaoming, Zhang, Zhijie, Liu, Jianjian, Ma, Guangtao, Wang, Zhenfeng, Zhao, Binggen
Integrating Anti-Idle Power Systems into Military Tactical Vehicles: Use Case Development and Analysis2026-01-50203/11/2026
Military tactical vehicles are increasingly incorporating anti-idle kits as a method to reduce fuel consumption. The larger battery pack associated with the anti-idle kit has the potential to provide new capabilities to the warfighter, who can use the battery pack to power pieces of equipment. This study analyzes a set of these new capabilities derived from the U.S. Army Universal Task List, supplemented with user interviews and doctrinal analysis. These capabilities include powering dismounted soldier systems, counter-drone and surveillance equipment, mobile refrigeration for medical applications, field maintenance tools, and mobile food services. The study then uses geolocation data collected from the U.S. Army’s National Training Center to model daily fuel consumption for soldiers performing each of these activities. The model was subsequently adapted to incorporate an anti-idle kit, revealing significant reductions in fuel usage. The analysis uses the results to define common
Lusian, Trevonte, Mummert, Taige, Kaiser, Caleb, Greer, Michael, Black, Nathaniel, Ong, Bennett, Tapahonso, Eugene, Mittal, Vikram
Prognostics of Battery State of Health Using Hybrid Modeling of Electric Vehicle Charging Data2026-01-70022/27/2026
Accurate estimation of the state of health (SOH) of lithium-ion batteries is essential for ensuring the safety, reliability, and performance optimization of electric vehicles. In practical operating environments, however, data quality is often compromised by noise interference, frequent fluctuations in load conditions, and the inherently non-stationary nature of battery degradation features. These challenges reduce the effectiveness of conventional modeling approaches, which often struggle to maintain both high prediction accuracy and strong generalization capability. To address these issues, this study develops a comprehensive SOH estimation approach encompassing data quality enhancement, degradation feature extraction, and hybrid deep learning-based modeling. In the first stage, multi-stage anomaly detection techniques are applied to remove noisy or inconsistent measurements. A week-based indexing strategy is introduced to generate temporally coherent labels, ensuring that time
Wang, Sijing, Jiao, Meiyuan, Huang, Weixuan, Lin, Yiting, Liu, Honglai, Lian, Cheng
Data-Driven Capacity Estimation Method for Retired Lithium-Ion Batteries Based on Electrochemical Impedance Spectroscopy2026-01-70152/27/2026
With the rapid expansion of global electric vehicles (EVs) deployment, the echelon utilization of retired lithium-ion batteries (LIBs) has emerged as a critical issue. Although these batteries typically retain over 70% of their initial capacity and remain suitable for stationary energy storage systems, the substantial variability in aging states poses safety risks. Conventional capacity estimation methods are often time-intensive and costly, while data-driven approaches face challenges from complex degradation mechanisms and limited historical usage data. This study uses the electrochemical impedance spectroscopy (EIS) method to create a model that estimates the capacity of retired batteries. EIS offers fast measurement, requires no historical cycling data, and provides rich state-of-health (SOH) information. An EIS dataset was acquired from 18650-type LFP and NCM cells aged under multiple cycling conditions. The real part and magnitude of the impedance spectra were extracted as input
Hou, Zhengyu, Luan, Weiling, Sun, Changzheng, Chen, Ying
Rapid Battery RUL Prediction under Different Fast-Charging Protocols via Domain-Adaptive Deep Learning and Model Compression2026-01-70032/27/2026
Accurate and rapid remaining useful life (RUL) prediction of batteries under various extreme conditions is crucial for battery management systems. However, existing methods often face challenges such as limited datasets under extreme conditions, high model complexity, and weak interpretability. Therefore, this paper proposes a hybrid framework based on pruning domain-adaptive convolutional neural networks (CNN) and long short-term memory (LSTM) to study RUL prediction under different fast-charging conditions using the MIT dataset. First, four voltage-related feature matrices are extracted. Using maximum mean discrepancy (MMD) constraints, the CNN-LSTM is trained with source domain and limited target domain data to align distributions. Neuron pruning is then applied to the fully connected layer to compress the model. Results demonstrate that under sparse target domain data, the domain adaptation approach achieves significantly lower prediction errors than fine-tuning. The pruned model
Huang, Mingyue, Chen, Hongxu, Luan, Weiling
Detecting Fuel Adulteration for Otto-Cycle Vehicle Using Onboard Diagnostics Data and Supervised Machine Learning04-19-02-00082/26/2026
Fuel adulteration affects operating costs, vehicle efficiency, and air pollution. Published estimates suggest it accounts for at least 10% of global sales. The Brazilian National Petroleum Agency (ANP) reported noncompliance in about 23% of inspections in 2023, including 4.3% confirmed adulteration. Quality verification requires laboratory equipment, and sensor-based approaches are often inaccessible to end consumers. This article proposes a sensorless (software-only) method that detects water adulteration in hydrated ethanol from standard Onboard Diagnostics (OBD) data using supervised machine learning, enabling on-vehicle fuel quality monitoring without additional hardware. The proposed approach is evaluated on real-world driving data from two production vehicles with three water adulteration levels in hydrated ethanol (0.0%, 2.5%, and 5.0%), achieving 84.85%–95.85% multiclass classification accuracy. These results indicate that software-only, OBD-based monitoring can provide a
Marchezan, Andre Ricardo, Giesbrecht, Mateus
Baggage/Cargo Trailer RequirementsARP1348B (Current)2/18/2026
This SAE Aerospace Recommended Practice (ARP) applies to airline trailer equipment with four wheel running gear pulled and steered through an integral tow bar, for use on airport ramps and other airport areas for transporting baggage, freight, and other materials. This ARP can apply to any airline/airport trailer chassis regardless of its equipment; the trailer bed can be designed to carry either bulk baggage/cargo, or a cargo unit load device by means of a rollerized conveyor system, or a piece of aircraft servicing equipment (e.g., ground power unit, air start unit, etc.).
AGE-3 Aircraft Ground Support Equipment Committee
Method of Evaluating Pneumatic Ground Power UnitsAIR4545A (Current)2/17/2026
This SAE Aerospace Information Report (AIR) covers, and is restricted to, the behavior of air under conditions of critical and subcritical flow at temperatures less than 500 °F.
AGE-3 Aircraft Ground Support Equipment Committee
Airport Electrical Power System HarmonicsAIR5387 (Current)2/17/2026
This SAE Aerospace Information Report (AIR) is intended to cover all airport 50 or 60 Hz electrical systems as well as all electrical utilization equipment that is attached to those systems.
AGE-3 Aircraft Ground Support Equipment Committee
Teaching Points for a Class on “Critical Issues in Composite Maintenance, Repair, and Overhaul”AIR5719B (Current)2/13/2026
This document is to be used as a checklist by curriculum developers to create courses or training for critical composite repair, maintenance, and overhaul issues. This document will not take the place of courses or training requirements for specific job roles of a composite repair technician, inspector, or engineer.
AMS CACRC Commercial Aircraft Composite Repair Committee
Maintenance of Batteries and Battery Charging and Servicing FacilitiesAIR1898A (Current)2/12/2026
This SAE Aerospace Information Report (AIR) covers, and is restricted to, hands-on servicing/ maintenance of industrial lead acid batteries used solely for motive power and exclusively for ground support equipment (GSE). It does not address or pertain to automotive-type SLI (starting-lighting-ignition) batteries or any other types of batteries (such as nickel-cadmium, zinc, or lithium batteries) which may be on-board airport GSE for either motive power or auxiliary uses. Similarly, the battery servicing and charging facilities described herein are those intended exclusively for industrial lead acid batteries.
AGE-3 Aircraft Ground Support Equipment Committee
Fuels in Ground Support Equipment (Other Than Gasoline or Diesel)AIR5373A (Current)2/12/2026
This SAE Aerospace Information Report (AIR) is intended as a source of comparative information and is subject to change to keep pace with experience and technical advances. This document describes currently used fuels and fuels which may be used in the future. Conventional gasoline and diesel fuels are intentionally omitted from this document.
AGE-3 Aircraft Ground Support Equipment Committee
Ground Equipment Rebuild ProgramAIR1599A (Current)2/12/2026
This Aerospace Information Report (AIR) is intended to be concerned with fleet programs rather than programs for individual units. Technical and administrative considerations in developing an approach to a program will be suggested. Organization of material possibly wanted in the form of a detailed specification for airline rebuilder communication is reviewed.
AGE-3 Aircraft Ground Support Equipment Committee
Maintenance of Ground Support EquipmentAIR4286 (Current)2/12/2026
The following are suggested policies, procedures, and practices required to maintain mobile and fixed ground support equipment at airport passenger and cargo terminals. The principal purpose for ground support equipment maintenance is to provide the owner/user with safe, serviceable equipment, in good appearance, at minimal cost, and with minimum downtime. Maintenance programs initiated on ground support equipment must also conform to regulations controlling airport operations. This document has been divided into three sections corresponding to the three stages of equipment life; acquisition, maintenance, and disposal.
AGE-3 Aircraft Ground Support Equipment Committee
Aircraft Tow BarARP1915E (Current)2/12/2026
This SAE Aerospace Recommended Practice (ARP) specifies dimensional and physical requirements of tow bar connections to tractor and aircraft (see Figure 1). It is applicable to all types of commercial transport category aircraft tow bar. The purpose of this SAE Aerospace Recommended Practice (ARP) is to standardize tow bar attachments to airplane and tractor according to the mass category of the towed aircraft, so that one tow bar head with different shear levels can be used for all aircraft that are within the same mass category and are manufactured in compliance with AS1614 or ISO 8267.
AGE-3 Aircraft Ground Support Equipment Committee
Technical Manual Requirements for Ground Support EquipmentAS4828A (Current)2/12/2026
This document is a guideline for format, structure and content for ground support equipment (GSE) technical manuals. This document focuses on requirements specific to the GSE industry and does not cover general technical publication practices. Additional standards for GSE and for manufacturer’s publications exist and may add requirements beyond what is covered in this standard. This may include EU Directive 2006/42/EC. This document is written in specific terms by intention, and conforms to recognized practices in the industry. When the word SHALL is used in this standard, it indicates a requirement that must be adhered to in total and does not allow for variance. When the word SHOULD is used, it indicates a recommended practice which allows the manual writer to use discretionary judgment. This document does not apply to electronic test equipment.
AGE-3 Aircraft Ground Support Equipment Committee
Main Line Aircraft Tow Bar Attach Fitting InterfaceAS1614D (Current)2/12/2026
This SAE Aerospace Standard (AS) specifies the interface requirements for tow bar attachment fittings on the nose gear (when towing operations are performed from the nose gear) of conventional tricycle type landing gears of commercial civil transport aircraft with a maximum ramp weight higher than 50,000 kg (110,000 pounds), commonly designated as “main line aircraft”. Its purpose is to achieve tow bar attachment fittings interface standardization by aircraft weight category (which determines tow bar forces) in order to ensure that one single type of tow bar with a standard connection can be used for all aircraft types within or near that weight category, so as to assist operators and airport handling companies in reducing the number of different tow bar types used.
AGE-3 Aircraft Ground Support Equipment Committee
GSE Training VideosAIR4730A (Current)2/12/2026
This document provides information on the preparation and use of video for operational and maintenance training of qualified personnel associated with GSE.
AGE-3 Aircraft Ground Support Equipment Committee
Dynamic Stiffness Prediction in Cracked Cantilever Beams Using Enhanced ANN Techniques2026-28-00502/12/2026
This research paper provides a comprehensive study on how Artificial Neural Networks (ANNs) can be deployed to predict the stiffness characteristics of a cantilever beam with a crack of various depths and positions. The most destructive source of failure is considered to be vibration, so the major focus of this paper will be on how the cracks affect the modal stiffness. This study has various applications, such as airplane wings, bridges, stadiums, and arenas. A common research gap was noticed amongst the existing studies; the position of the cracks in the cantilever wasn’t considered, but this paper discusses how the location of cracks severely affects the dynamic behaviour of the cantilever. This study was done by carrying out modal analysis on a cantilever of the same dimensions with different crack configurations. Various crack dimensions and orientations were analysed to understand the effects of the crack on the dynamic behaviour of the cantilever. From the modal analysis results
SB, Harshini, Rajkumar, Manjari, R, Krithika, K, Anusha, K, Divya, Bhaskara Rao, Lokavarapu
Digital Annex of Medium/Heavy-Duty E/E Systems Diagnosis NomenclatureJ2403DA_202601 (Current)2/7/2026
This document is intended to supplement SAE J2403 by providing the content of Table 1, Table 2, and Table 3 from SAE J2403 in a form that can be sorted and searched for easier use. It is NOT intended as a substitute for the actual document, and any discrepancies between this Digital Annex and the published SAE J2403 document must be resolved in favor of the published document. This document provides the content of Table 1 and Table 2 published in SAE J2403 into the single table in the 'Term' tab, while the 'Recommended Term Definitions' tab provides the content of Table 3 in SAE J2403 and the 'Glossary' tab provides the content of Table 4 in SAE J2403.
Truck and Bus Control and Communications Network Committee
WIRING INSTALLATION TOOLS FOR PLASTIC AND METAL TIEDOWN STRAPSAS90387E (Current)2/7/2026
AE-8C2 Terminating Devices and Tooling Committee
Integrated architectures reshape the mobile-hydraulic ecosystem26TOFHP02_062/1/2026
Off-highway equipment operates in an environment defined by extremes - extreme loads, extreme duty cycles, extreme temperatures and extreme expectations. OEMs and fleet operators face mounting pressure to deliver more power, more uptime and more precision from platforms that are becoming increasingly compact, intelligent and complex. Whether the task is hauling, lifting, dumping, clearing or moving materials, the equipment must deliver consistent, reliable performance without compromise. This pressure is reshaping the mobile-hydraulic ecosystem. The industry is steadily shifting away from piecemeal systems and toward integrated, intelligent power architectures that maximize efficiency across the entire vehicle. Leaders in this space, Eaton among them, demonstrate how a system-level approach to PTOs, hydraulic pumps and control valves is enabling a new generation of off-highway innovation.
Bogdan, Corneliu
J1939 Digital AnnexJ1939DA_202601 (Current)2/1/2026
This document is intended to supplement the J1939 documents by offering the J1939 information in a form that can be sorted and searched for easier use.
Truck and Bus Control and Communications Network Committee
REMOVAL TOOLS, CONNECTOR, ELECTRICAL CONTACT, TYPE II, CLASS 1, COMPOSITION AAS81969/27A (Current)1/28/2026
AE-8C2 Terminating Devices and Tooling Committee
Ice Penetration Test Method for AMS1431 and AMS1435 Runway Deicing/Anti-Icing ProductsAS6211A (Current)1/23/2026
This document establishes a standardized test method designed to provide stakeholders—including runway deicing/anti-icing product manufacturers, users, regulators, and airport authorities—with a means of evaluating the relative ice penetration capacity of runway deicing and anti-icing products over time. The method measures ice penetration as a function of time, thereby enabling comparative assessments under controlled conditions. While commonly applied to runway treatments, these products may also be used on taxiways and other paved surfaces. The test is not intended to provide a direct measurement of the theoretical or extended ice penetration time of liquid or solid deicing/anti-icing products. Instead, it offers a practical and reproducible basis for performance evaluation, supporting operational decision-making and regulatory compliance.
G-12RDP Runway Deicing Product Committee
A Centralized Framework for Sustaining Safety-Critical Vehicle Systems Through Periodic Servicing2026-26-00031/16/2026
As vehicles are becoming more complex, maintaining the effectiveness of safety critical systems like adaptive cruise control, lane keep assist, electronic breaking and airbag deployment extends far beyond the initial design and manufacturing. In the automotive industry these safety systems must perform reliably over the years under varying environmental conditions. This paper examines the critical role of periodic maintenance in sustaining the long-term safety and functional integrity of these systems throughout the lifecycle. As per the latest data from the Ministry of Road Transport and Highways (MoRTH), in 2022, India reported a total of 4.61 lakh road accidents, resulting in 1.68 lakh fatalities and 4.43 lakh injuries. The number of fatalities could have been reduced by the intervention of periodic services and monitoring the health of safety critical systems. While periodic maintenance has contributed to long term safety of the vehicles, there are a lot of vehicles on the road
HN, Sufiyan Ahmed, Khan, Furqan, Srinivas, Dheeraj
Assessment of Cybersecurity Risks in State-Operated Connected Electric Passenger Buses in India2026-26-06101/16/2026
State Transport Units (STUs) are increasingly using electric buses (EVs) as a result of India's quick shift to sustainable mobility. Although there are many operational and environmental benefits to this development, like lower fuel prices, fewer greenhouse gas emissions, and quieter urban transportation, there are also serious cybersecurity dangers. The attack surface for potential cyber threats is expanded by the integration of connected technologies, such as cloud-based fleet management, real-time monitoring, and vehicle telematics. Although these systems make fleet operations smarter and more efficient, they are intrinsically susceptible to remote manipulation, data breaches, and unwanted access. This study looks on cybersecurity flaws unique to connected passenger electric vehicles (EVs) that run on India's public transit system. Electric vehicle supply equipment (EVSE), telematics control units (TCUs), over-the-air (OTA) update systems, and in-car networks (such as the Controller
Mokhare, Devendra Ashok
Integrated Powertrain Domain Controller Using Wide Band Gap Devices for EV Applications2026-26-00551/16/2026
The rapid evolution of electric vehicles (EVs) has amplified the demand for highly integrated, efficient, and intelligent powertrain architectures. In the current automotive landscape, EV powertrain systems are often composed of discrete ECUs such as the OBC, MCU, DC-DC Converter, PDU, and VCU, each operating in isolation. This fragmented approach adds wiring harness complexity, control latency, system inefficiency, and inflates costs making it harder for OEMs to scale operations, lower expenses, and accelerate time-to-market. The technical gap lies in the absence of a centralized intelligence capable of seamlessly managing and synchronizing the five key powertrain aggregates: OBC, MCU, DC-DC, PDU, and VCU under a unified software and hardware platform. This fragmentation leads to redundancy in computation, increased BOM cost, and challenges in system diagnostics, leading to sub-optimal vehicle performance. This paper addresses the core issue of fragmented control architectures in EV
Kumar, Mayank, Deosarkar, Pankaj, Inamdar, Sumer, Tayade, Nikhil
EV Powertrain Systems Diagnostics & Prognostics Utilizing AI & ML (LLM) Based Approach2026-26-06641/16/2026
This study introduces a novel Large Language Model (LLM)-driven approach for comprehensive diagnosis and prognostics of vehicle faults, leveraging Diagnostic Trouble Codes (DTCs) in line with industry-standard automation protocols. The proposed model asks for significant advancement in automotive diagnostics by reasoning through the root causes behind the fault codes given by DTC document to enhance fault interpretability and maintenance efficiency, primarily for the technician and in few cases, the vehicle owner. Here LLM is trained on vehicle specific service manuals, sensor datasets, historical fault logs, and Original Equipment Manufacturer (OEM)-specific DTC definitions, which leads to context-aware understanding of the vehicle situation and correlation of incoming faults. Approach validation has been done using field level real-world vehicle dataset for different running scenarios, demonstrating model’s ability to detect complex fault chains and successfully predicting the
Pandey, Suchit, Joshi, Pawan, Kondhare, Manish, CH, Sri Ram, Gajbhiye, Abhishek, S, Adm Akhinlal
Leveraging AI/ML Algorithms for Analyzing Fleet Vehicles In-Use Performance Ratio Monitoring Data2026-26-06371/16/2026
In recent times, the governments are pushing for stringent emission regulations. These regulations call for reduction of pollutants as well as monitoring of engine components which are critical for emission control. Monitoring these emission critical engine components are to be done in real world driving conditions. The In-Use Performance Ratio Monitoring (IUPRm) framework quantifies how often onboard diagnostic systems check these components within defined boundaries for each vehicle. IUPRm is divided into several monitoring groups like catalyst monitoring, oxygen sensor monitoring, exhaust gas recirculation (EGR) monitoring, gasoline particulate filter monitoring and others. These groups are differentiated based on fuel type, engine technologies and exhaust treatment system configurations. For an Automotive manufacturer analyzing these parameters across large vehicle fleets is a complex and data intensive task. To address this, a user-friendly application was developed in-house
Ghadge, Ganesh Narayan, Jadhav, Marisha, Hosur, Viswanatha
A Scalable ArTOP-Based in-House Toolchain for Automated AUTOSAR Configuration2026-26-06821/16/2026
The rising software complexity in Automotive industry demands reusable, hardware-agnostic development frameworks. AUTOSAR (Automotive Open System Architecture) provides a standardized, scalable ECU software architecture but cost-effective tooling and modern workflows are critical for broad adoption and competitiveness. One such area is for AUTOSAR configuration and authoring of Autosar architecture. Current solutions include commercial offerings built by vendors on top of ARTOP (ArTOP is an eclipse-based ecosystem maintained by AUTOSAR consortium) and open-source python implementations. Commercial tools are prohibitive in cost, have complicated development workflows, are difficult to automate and lack quick integration with other tools. Python-based solutions are often community driven with small developer teams and face challenges. These tools are not mature enough, have staggered development, security concerns, liability issues, lack of approvals and other similar issues. These
Daware, Kartik, Garg, Mudit, Pasupuleti, Raju
Self-Supervised Diagnostics & Prognostics Framework for Predictive Maintenance in Electric Vehicles2026-26-06731/16/2026
Predictive maintenance is critical to improving reliability, safety and operational efficiency of connected vehicles. However, classic supervised learning methods for fault prediction rely heavily on large-scale labeled data of failures, which are difficult to obtain and maintain a manually built dataset of failure events in real automotives settings. In this paper, we present a novel self-supervised anomaly detection model that makes predictions on the faults without the need for labeled failures by using only the operational data when the systems or robots are healthy. The method relies on self-supervised pretext tasks, like masked signal reconstruction and future telemetry prediction, to extract nominal multi-sensor dynamics (i.e., temperature, pressure, current, vibration) while jointly minimizing the deviation between encoded/decoded signals and normal patterns in the latent space. A unsupervised anomaly detection model is then used to detect when the learned patterns are violated
Kumar, Pankaj, Deole, Kaushik, Hivarkar, Umesh
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