Browse Topic: Maintenance and Aftermarket

Items (10,413)
Monitoring inputs and states of a structural dynamic system is often challenging, as direct measurements are costly or even infeasible. A virtual sensing methodology is presented for jointly estimating the input and state of a structure when subjected to multi-directional base excitations. The approach uses a tuned Kalman Filter combined with a model-order reduction of the system model to ensure a low computational cost whilst allowing accurate estimation from a limited number of acceleration measurements. This enables real-time virtual health monitoring strategies and reduction in instrumentation during data acquisition without additional information such as location and direction of application about the inputs. The proposed methodology is validated numerically and experimentally using a notched aluminum beam excited on a multi-directional shaker table, driven simultaneously in two in-plane directions. The study demonstrates accurate full-field estimation of multiple responses along
Salazar Colunga, RodrigoPandiya, NimishDindorf, ChristianNaets, Frank
Individuals who complete the applicable modules aligned with this training document will be able to define the type of damage, define the extent of damage, determine if further inspection is required, evaluate the damage against published allowable damage limits, and provide accurate documentation of the damage. The intended outcome of the training is increased safety such that no aircraft is released with unknown damage and that the aircraft meets continued airworthiness requirements. The goal is to change the culture from damage discovery to damage reporting while also reducing or eliminating flight delays due to incorrect or insufficient information. Teaching levels have been assigned to the curriculum to define the knowledge, skills, and abilities graduates will need. Minimum hours of instruction have been provided to ensure adequate coverage of all subject matter including lecture and practical exercise. These minimums may be exceeded and may include an increase in the total
AMS CACRC Commercial Aircraft Composite Repair Committee
This SAE Aerospace Information Report (AIR) provides descriptions of test methods for determining if an aircraft surface coating of any thickness has adverse effects on aircraft deicing/anti-icing fluids with respect to fluid holdover time performance and aerodynamic performance. Although not the primary mandate of the G-12 Aircraft Ground Deicing Committee, this document also provides descriptions of suggested test methods for evaluating aircraft surface coatings with respect to durability, hardness, weathering, aerodynamic drag, ice adhesion, ice accumulation, contact angle, and thermal conductivity. These additional tests can provide informational data for characterizing the coatings and may be useful to operators when evaluating the coatings.
G-12ADF Aircraft Deicing Fluids
Hydrogen-fueled rotary engines offer a promising zero-emission solution for compact commercial powertrains. This study reports experimental results from the further development of a naturally aspirated, direct-injection hydrogen rotary engine by HTM. Initial applications, such as an airport baggage tractor, demonstrated technical feasibility but revealed pre-ignition that limited maximum torque. To address this, mixture formation was investigated using an experimental setup with two independently controlled injectors feeding a single rotor injection channel. The effects on operating behavior, efficiency, and NOx emissions were evaluated. The dual-injector configuration significantly shortens injection duration and improves spatial distribution of hydrogen within the combustion chamber. Enhanced mixture control suppresses pre-ignition and enables higher mean effective pressure. Systematic variation of injection timing under representative steady-state conditions also shows potential for
Endres, JonasBeidl, ChristianHerold, TimLavall, PhilippSchmidt, MarvinHofmann, SilasKahl, Jonas
This work presents the development of a user-oriented software tool for the cradle-to-grave Life Cycle Assessment (LCA) of passenger cars, enabling robust comparisons of greenhouse gas emissions across heterogeneous vehicle configurations. The tool supports informed decision-making by quantifying and visualizing environmental impacts associated with alternative mobility choices over the full vehicle life cycle, including production, use, maintenance, and end-of-life stages. The proposed framework allows key parameters describing both the vehicle and its usage to be explicitly defined, including powertrain type, dimensions and weight, ownership profile (new or second-hand vehicles, partial ownership periods, leasing scenarios), annual mileage, vehicle lifetime assumptions, and the carbon intensity of fuels or electricity sources. Country-specific energy mixes are incorporated, enabling the same vehicle to be assessed under different geographic contexts and highlighting the strong
Gastaldi, ChiaraCibrario, Luca
Researchers discover texts, phone calls, military communication, internal corporate networks all easily eavesdropped on using off-the-shelf equipment. University of California San Diego, La Jolla, CA With $800 of off-the-shelf equipment and months' worth of patience, a team of U.S. computer scientists set out to find out how well geostationary satellite communications are encrypted. And what they found was shocking. Close to half of the communications beamed from satellites to the ground that the researchers were able to listen in on were not encrypted. This included sensitive data including cellular text messages, voice calls, as well as sensitive military information, data from internal corporate and bank networks, and the in-flight online activity of airline passengers.
Researchers from CompPair and the European Space Agency have developed a new composite material for spacecraft with an embedded healing agent. European Space Agency, Paris, France Healable spacecraft structures could soon be possible thanks to cutting-edge composite technology. Swiss companies CompPair and CSEM, and Belgian company Com&Sens have partnered with the European Space Agency (ESA) to modify their self-healing carbon fiber product for use in space transportation. Project Cassandra - an abbreviation for Composite Autonomous Sensing and Repair - includes sensors and a heating element within a composite carbon-fiber material, allowing spacecraft to autonomously repair initial stages of damage.
Unscheduled maintenance due to the failure of critical components, such as aero-engine rolling element bearings, is a leading cause of costly Aircraft-on-Ground (AOG) events; consequently, current time-based maintenance practices are inefficient and prone to risk. This paper develops a resource-efficient Hybrid Digital Twin (HDT) model for an engine bearing, focusing on the dynamic prediction of spall growth due to Rolling Contact Fatigue (RCF), thereby enabling a condition-based maintenance paradigm. The HDT architecture integrates two core models: (1) a physics-informed model that uses established life and fatigue theory to define initial degradation thresholds, and (2) a data-driven Recurrent Neural Network (RNN), specifically a Long Short-Term Memory (LSTM) network, for dynamic degradation rate modeling. The methodology utilizes a Monte Carlo simulation coupled with RCF progression equations to generate a large, high-fidelity synthetic run-to-failure dataset under varying
Mohamed, Abbas
Acoustic-induced vibrations pose a significant risk to launch vehicle hardware and payload reliability during critical phases such as lift-off and transonic phase. Reducing such vibrations is especially challenging when the hardware has already been fabricated, limiting the possibility of structural redesign. This study demonstrates a practical post-fabrication solution using a thin viscoelastic polymer coating applied externally to fully assembled hardware. Comprehensive evaluations were conducted using both acoustic testing and Experimental Modal Analysis (EMA) before and after coating application. During acoustic test, a substantial decrease in structure response from 150Hz to 2000Hz, with a reduction of approximately 50% in the grms values was observed for the coated structure demonstrating significant vibration mitigation over a wide frequency range. In contrast, EMA measurements using impact excitation revealed that the response transfer functions did not show a significant
Avirah, Nohin KPanda, Ajay KumarShaikh, Altafhusen
Aircraft Maintenance, Repair, and Overhaul (MRO) operations are highly complex, involving coordination among multiple stakeholders including airlines, MRO providers, OEMs, and regulatory authorities. A significant challenge in this space is managing unplanned events such as Aircraft on Ground (AOG) conditions, where delays can lead to major financial losses to airlines and safety risks. Engineers must quickly diagnose the damage, evaluate compliance against regulatory limits, coordinate with OEMs, and make critical decisions—all while navigating a fragmented ecosystem of disconnected systems, diverse document types, and time-sensitive processes. This paper presents a real-world, intelligent MRO solution that addresses these challenges through the use of Agentic AI and context engineering. The system is designed to automate and augment key MRO workflows such as damage detection, repair pathway selection, compliance verification, and supplier coordination. At its core, the solution is
Abburu, SunithaG.V.V., Ravi KumarPoovalingam, SundaresanVaderahobli, Devaraja Holla
Static electricity is an electrical imbalance on the surface of a material which can interact with other components having same or different materials. Fluid flow within the hose assembly generates static voltage due to friction caused by fluid flow in pipes, that needs to be appropriately quantified and dissipated. Accumulation of such static charge may lead to sudden discharge leading to spark generation. Spark generation around fuel flow might lead to system failure and failure in aircraft engines. Test experiments were conducted to analyze static voltage generated in hose assembly due to fuel flow with the objective that voltage achieved is within the acceptable range to avoid ESD (Electrostatic Discharge) failure. Procedure includes flow rate monitoring and voltage measurement using fuel as test fluid. The testing revealed that the curvature of the hose affects the readings, highlighting the importance of consistent meter alignment. Using a grounding strap is essential to prevent
Waghmare, Shashank
As aerospace platforms adopt increasingly interconnected architectures for avionics, telemetry, and predictive diagnostics, lightweight publish–subscribe protocols have become integral to communication efficiency. The Message Queuing Telemetry Transport (MQTT) protocol is widely employed due to its small footprint and low network overhead. The release of MQTT 5.0 introduces new control features—reason codes, session expiry, user properties, topic aliasing, shared subscriptions, and improved error feedback—aimed at enhancing scalability and diagnostic reliability. However, these benefits come with trade-offs in complexity and potential overhead, particularly in real-time and resource-constrained environments typical in aerospace. This paper evaluates MQTT 3.1 and MQTT 5.0 within aerospace IoT contexts using a Raspberry Pi–based experimental framework. The analysis is done using practical throughput benchmarks implemented via popular open-source tools like Eclipse Mosquitto Clients
Bhuyar, PrabhudevM, MeghanaKaniraja, ChristinaThomas, Tinto
This novel method deals with emulation of Strain of a Structural Measurement System which includes software validation, acceptance tests and training. Current methods for simulating strain and force data for developing and verifying data acquisition (DAQ) software typically rely on costly electronic simulators or specialized hardware, making it challenging and expensive for developers, researchers, and small organizations to test their solutions under realistic conditions. To verify DAQ software, multiple specialized hardware solutions are deployed, that include Electronic Simulators, Commercial DAQ Modules and Hydraulic/Pneumatic test rigs. These technologies pose a challenge with limited flexibility and scalability options for small-scale prototyping, especially in budget-constrained scenarios. The sensors on these equipment may or may not be company approved inducing acceptance challenges. Our invention is an inexpensive, scalable, and mechanically simple alternative. Using a 3D
Murthy, HarshaBhat Venkatesh, AditiK Padmanabhan, RahulMadhu, SheetalGarag, Naveen
Aircraft interior defects, including seat structural damage, cushion degradation, liquid contamination, and foreign object presence, contribute to increased maintenance burden, extended ground time, and operational inefficiencies. Current inspection practices rely predominantly on manual visual checks, which are time-intensive and limited in detecting concealed anomalies. This paper presents a non-contact, AI-enabled inspection framework integrating millimeter-wave (mmWave) radar sensing with high-definition optical imaging for automated aircraft seat condition assessment. The proposed system captures interior scans when the aircraft is unoccupied and compares them against a digitally established baseline reference obtained under certified, defect-free conditions. Data fusion and machine learning algorithms analyze deviations to identify surface and subsurface defects at seat-level resolution and generate zone-based maintenance maps. The primary technical contribution lies in combining
Nagoal, Chandrasekhar ReddyPrathipati, Krishna ChaitanyaKandukuri, Ravindra
Circular-economy principles are increasingly central to aerospace sustainability strategies, aiming to extend asset life, improve asset valuations, and enhance benefits to stakeholders in the part ownership and maintenance lifecycle. In aircraft engines, achieving circularity hinges on safe reuse, repair, and recirculation of high-value components. Life-Limited Parts (LLPs) are among the most critical in this context, but their reuse is strictly contingent on complete Back-to-Birth (BtB) traceability. Any gap in BtB records—often due to fragmented data across multiple airline operators, shop visits, document formats, and time expanse—renders otherwise serviceable LLPs unusable, leading to premature scrappage and lost circular value. This paper presents a Generative AI (GenAI)-driven methodology to reconstruct and validate complete LLP BtB histories from heterogeneous, unstructured, and legacy maintenance datasets. By combining aerospace domain-trained language models with embedded life
Bhate, UjwalJain, Dilip KumarKulkarni, NinadKalaiyarasan, AravindhJha, AshishShenoy, Karthik
This specification establishes requirements for a standard contaminant that can be used to represent typical soils encountered in aerospace cleaning. This standard contaminant consists of materials that are common contaminants found in aircraft maintenance depots and manufacturing facilities.
AMS G9 Aerospace Sealing Committee
This document establishes the minimum training and qualification requirements for ground-based aircraft deicing methods and procedures. All guidelines referred to herein are applicable only in conjunction with the applicable documents. Due to aerodynamic and other concerns, the application of deicing fluids shall be carried out in compliance with engine and aircraft manufacturers’ recommendations. The scope of training should be adjusted according to local demands. There are a wide variety of winter seasons and differences of the involvement between deicing operators, and therefore, the level and length of training should be adjusted accordingly. However, the minimum level of training shall be covered in all cases. As a rule of thumb, the amount of time spent in practical training should equal or exceed the amount of time spent in classroom training.
G-12T Training and Quality Programs Committee
This Surface Vehicle & Aerospace Recommended Practice offers best practices and a methodology by which IVHM functionality relating to components and subsystems should be integrated into vehicle or platform level applications. The intent of the document is to provide practitioners with a structured methodology for specifying, characterizing and exposing the inherent IVHM functionality of a component or subsystem using a common functional reference model, i.e., through the exchange of design-time data and the application of standard vehicle data communications interfaces. This document includes best practices and guidance related to the specification of the information that must be exchanged between the functional layers in the IVHM system or between lower-level components/subsystems and the higher-level control system to enable health monitoring and tracking of system degradation severity. The intent is to provide an IVHM system that can robustly report the degradation of a given
HM-1 Integrated Vehicle Health Management Committee
SAE JA6097 (“Using a System Reliability Model to Optimize Maintenance”) shows how to determine which maintenance to perform on a system when that system requires corrective maintenance to achieve the lowest long-term operating cost. While this document may focus on applications to Jet Engines and Aircraft, this methodology could be applied to nearly any type of system. However, it would be most effective for systems that are tightly integrated, where a failure in any part of the system causes the entire system to go off-line, and the process of accessing a failed component can require additional maintenance on other unrelated components.
HM-1 Integrated Vehicle Health Management Committee
To enhance the economic efficiency and operational security of distribution grids, this paper develops a reactive power optimization model that incorporates distributed power sources. The model aims to minimize the costs of reactive-load compensation equipment, reduce voltage deviations, and lower network losses while satisfying operational constraints. To overcome the common drawbacks of the standard genetic algorithm—such as limited optimization precision and a tendency to converge to local optima—four improvement strategies are introduced. These include an enhanced encoding scheme, an initial population generated via opposition-based learning, an elite retention strategy, and the adaptive adjustment of crossover and mutation rates. Together, these modifications strengthen the algorithm’s global search capability. The proposed approach is validated using the IEEE30 node system. Compared with both the conventional genetic algorithm (GA) and an adaptive genetic algorithm, the improved
Wang, MaozeXiao, WenyuLiu, YujiaXu, ZhengweiXia, Yinyong
When simulating spray atomization process involving VOF method, a core problem is the conflict between high grid detail and limited computer power. Although VOF and DPM methods have recently been coupled to reduce computational cost, their application in practical engineering calculations still imposes a considerable computational burden. To solve this, a better adaptive mesh refinement (AMR) plan is put forward. This plan uses a 0.2 mm initial grid (twice the usual 0.1mm) and allows refinement up to four levels. This improved technique makes high computational efficiency for large-scale simulations. Two types of nozzles are employed to evaluate the proposed method. However, for circular nozzles, the new method does not increase calculation speed, while lowers the accuracy of the simulation.In contrast, for square nozzles, it greatly boosts computation speed and keeping high accuracy. This makes the technique a useful tool for modeling transverse jet atomization in industry. Overall
Zhou, TaotaoMa, MingZhang, HaitaoZhang, FenganChen, XianhuiChen, QiXia, Hongwei
The monorail crane is important in mining operations, and its operation affects both safety and efficiency. Currently, fault diagnosis for monorail cranes has several challenges, such as heterogeneous mixing of multimodal data, poor use of knowledge, low real-time requirements, and high deployment costs for large-scale models. To solve these problems, we present an agent framework using a multimodal knowledge graph and a lightweight large model. In particular, we construct a fault knowledge graph for monorail cranes, organizing professional knowledge about components, failure modes, symptoms, and maintenance. By employing retrieval-augmented generation (RAG) technology, the knowledge graph is merged with the Qwen lightweight large model (low-rank adaptation) for fine-tuning to develop a diagnostic agent with task planning, tool invocation and memory. The experimental results show that the agent framework reduces “machine hallucination” and outperforms conventional diagnostic accuracy
Zhang, YixuanXue, ShunBi, XiangWei, XingKang, RanyuJue, JieCheng, Liruiran
Causal inference from observational data, particularly the estimation of a treatment’s causal effect on an outcome, has long been challenging, primarily because it hinges on correctly identifying confounders. This is typically accomplished in two main ways within causal inference frameworks: either by using causal discovery algorithms to recover the underlying causal structure through a causal graph, or by assuming that the relevant confounders are already known. Both approaches have been shown to be unreliable or simply infeasible in practical applications. Although large language models (LLMs) are advancing rapidly, their emerging capabilities in causal inference have only recently begun to receive significant attention. Nevertheless, LLMs currently lack the ability to directly interpret structured tabular data, which is widely used in causal inference. To address this limitation, we introduce a novel framework, CauExecutor, for causal inference. Our framework enables a novel
Yang, JiaoyunChen, JinxiYin, YueLiu, LiLi, LianAn, Ning
As a densely populated public place, exhibitions feature spatial layouts with multi-area linkage and instantaneous crowd flow mutations. Thus, developing a crowd flow early warning system adapted to exhibition dynamics is a key focus at the public safety and smart exhibitions to avoid risks like local congestion-induced stampedes. In general, two core challenges in exhibition crowd counting: 1) Key dynamic gathering information is hidden in high frequency components, but no correlation mechanism between frequency components and scene has been established; 2) Instant crowd gatherings cause high-frequency local density mutations, leading to time delays and spatial ambiguity of dynamic signals. To solve these, we propose a novel Crowd Counting Network for Risk Early Warning in Exhibition Scenarios with two core modules: 1) A bidirectional feature filtering module optimizes frequency information through low-frequency suppression to reduce redundancy and high-frequency activation to
Zhang, JinZhang, WanyueYuan, JingjingChen, ZhenGu, Dazhi
This article focuses on the problem of high labor cost, low processing efficiency and poor automation of the existing equipment in the postharvest processing of Chinese cabbage. It will design and produce an automated Chinese cabbage processing method called Smart Fresh Pack. Root removal, leaf removal, washing, loading, weighing, packaging and labeling functions were integrated, and smart dexterous intelligence was applied to core concepts and this can be used in the bulk production scenario of supermarkets in the city and countryside Compared with traditional assembly line equipment, obvious advantages in terms of structure, function and processing capacity: Key innovations include: Low-pressure air jet cleaning replaces water washing, which prevents a second contamination and weighing error due to surface moisture; pneumatic gripper and multi-DOF robotic arms combine to package and dynamically weigh simultaneously, streamlining these tasks; machine vision relies on an SSD
Chen, YuhuiZhang, YixuanRuan, JiaZhu, HuayunHe, LianzhengZhao, Ping
Causal discovery within time series is crucial for revealing the actual causal mechanisms in dynamic systems, and it has major impacts in various fields like economics, healthcare, and climate science. Even though it’s important, accurately figuring out causal relationships from observational temporal data is still quite a difficult task. Traditional Granger causality based methods are often limited by noise sensitivity, large amount of data, and the inability to distinguish between real causality and false correlation caused by hidden factors. In order to solve these problems, this paper presents CausalAugVeri, which is a new algorithm that cleverly mixes data augmentation with causal verification to make causal discovery more solid and precise. This work has three main points: First, we carefully check that using convolutional data augmentation techniques can greatly improve how well time series predictions work, giving a steadier base for detecting Granger causality. Second, the
Yang, JingChen, XiaotaoQin, XuanliXu, XianjunHu, Zhangxiang
This SAE Aerospace Information Report (AIR) provides information and guidance for the selection and use of technologies and methods for lubrication system monitoring of gas turbine aircraft engines. This AIR describes technologies and methods covering oil system performance monitoring, oil debris monitoring, and oil condition monitoring. Both on-aircraft and off-aircraft applications are presented. A higher-level view of lubrication system monitoring as part of an overall engine monitoring system (EMS) is discussed in ARP1587. The scope of this document is limited to those lubrication system monitoring, inspection, and analysis methods and devices that can be considered appropriate for health monitoring and routine maintenance. This AIR is intended to be used as a technical guide. It is not intended to be used as a legal document or standard.
E-32 Aerospace Propulsion Systems Health Management
This SAE Standard specifies requirements for a foaming liquid cleaning compound which, when diluted with water 1:9 v/v, is suitable for cleaning the soiled exterior of Service aircraft. The cleaning compound may be applied by spraying, either as foam or liquid, by brushing or by swabbing. The surfaces to be cleaned may be unpainted metal or surfaces painted with glossy or matt schemes, including strippable acrylic paint complying with DTD 5599. This Standard includes tests to limit specific forms of corrosion that affect aircraft structural materials.
AMS J Aircraft Maintenance Chemicals and Materials Committee
This document applies to off-road forestry work machines defined in SAE J1116 or ISO 6814.
MTC4, Forestry and Logging Equipment
This SAE Aerospace Recommended Practice (ARP) document establishes criteria and recommended practices for the use of airborne icing tankers to aid in design and certification of aircraft ice protection systems and components. Several icing tankers are described, along with their capabilities and suggested use. Sample data for these tanker spray systems are included, shown with 14 CFR Parts 25 and 29, Appendix C icing envelopes for continuous maximum and intermittent maximum icing conditions. (Note: In the remainder of this document, the phrase “Appendix C icing envelopes” will be used for brevity.) This ARP is intended as a guide toward standard practice and is subject to change to keep pace with experience and technical advances.
AC-9C Aircraft Icing Technology Committee
USC Viterbi researcher received Office of Naval Research's Young Investigator Program award with Study on dexterous robotics. University of Southern California, Los Angeles, CA In dynamic, unstructured environments like ship decks and even home kitchens, robots today still struggle to perform precision tasks such as tightening bolts or handling wires. This makes critical ship maintenance tasks difficult. USC researcher, Erdem Bıyık, aims to advance robots' finger manipulation and integrate human feedback to enable real-time learning for robots in an upcoming three-year, $750,000 project funded by the Office of Naval Research (ONR).
Meta-wheels—non-pneumatic wheels whose performance is governed by structural geometry rather than internal pressure—offer new opportunities for directional stiffness control. Yet achieving independent tuning of longitudinal, lateral, and vertical stiffness within a single wheel architecture has remained challenging due to the inherent coupling in conventional radial and planar curved spokes. In this study, we introduce a three-dimensional (3D) discrete curved-spoke design that provides explicit geometric control through two independent parameters: the in-plane curvature angle (α) and the out-of-plane inclination angle (β). Using spoke-level and full-wheel finite-element (FE) simulations, supported by a simplified cantilever-beam analytical model, we show that these two geometric parameters govern stiffness in fundamentally different ways. The curvature angle α serves primarily as a geometric softener, reducing stiffness in all directions while maintaining a high top-loading ratio (TLR
Han, HeeseungLiu, ZhipengJu, Jaehyung
Understanding the fluid flow behavior over and into narrow gaps is crucial for many industrial applications, particularly in the automotive sector. Evaluating the potential of water ingress into narrow pathways and towards components is of great importance to design the water management of such components. The employment of CFD simulations supports the evaluation of potential water ingress into such gaps. Lagrangian based 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 our previous work, a validated simulation setup was developed using the meshless simulation tool MESHFREE from Fraunhofer ITWM [8] for simulating water entering small gaps. Especially for industrial use cases, the computation time of several days is too expensive. Thus, we enhanced this approach to a fast and robust CFD simulation that realizes industrial use cases within appropriate time. The development was
Zrnic, DinoKonstantinovics, AthenaKospach, AlexanderRugerri, EvelynLoy, MichaelBäder, DirkMichel, Isabel
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 a few tools: crash analysis tools such as LS-Dyna, non-linear structure analysis tools, or multi-body dynamics (MBD) analysis tools like Ansys Motion. The three simulation tools have pros and cons, respectively. In this study, a curb impact simulation was performed using the multi-body dynamic approach with nonlinear structural analysis capabilities included in Ansys Motion. The tool demonstrated the simulation was completed faster than other MBD tools due to smartly recycling the system Jacobian matrix when structural deformation was not significant. The results were compared with structural analysis and correlated reasonably well. The post-impact suspension alignment changes can also be simulated for reviewing design requirements. This approach proposes a new way to simulate
Hong, Hyung-JooKim, Wangoo
The useability of development processes in the automotive sector has decreased in the past years to a level at which their application and true benefit to is being questioned. 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 the traditional ‘plan–implement–test–roll-out' methodology to more agile methods. In addition, process departments typically in charge of these processes, focus on compliance to the letter of the standard to achieve certification, often with little thought to the actual implementation and the process they will be used by their engineering teams. Process growth to meet the needs of new and more complex technologies often mandates the use of new tools, which if implemented incorrectly can lead to unnecessary bureaucracy and additional overheads. Furthermore, the language of these new processes is in a form from assessor, making it difficult for
Weber, MatthiasKmiec, MateuszRomijn, MarcelNedkov, Detelin
The proven usefulness of large language models (LLMs) as tools for software development and the recent rapid increase in their capabilities have made it possible and attractive to extend their scope of application to almost all tasks in the engineering of complex and even safety-critical systems. While these tools promise substantial efficiency gains and improved engineering productivity, they remain prone to errors, and the generated artifacts may not meet the stringent quality requirements for safety-critical systems. In this paper, we systematically analyze potential applications of LLMs throughout the engineering lifecycle of safety-critical systems and identify associated risks as well as practical approaches to risk mitigation. We classify LLM-supported use cases according to LLM autonomy, impact, and artifact observability, and compare the corresponding mitigation strategies with established approaches used for traditional engineering automation. In addition, we examine the
Thomas, CarstenWagner, Michael
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, VinayaYoo, Dong YeonChavare, Sudeep
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, an 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 soot
Bagga, Harleen KaurNagare, Mukund B.Patil, Bhushan D.Ravishankar, HariharanMelapudi, VikramVanderheide, CraigPatil, Abhijit
In the stringent market of BEV, the development of integrated Drive Modules (iDM) fitting environmental and customer needs is mandatory. It is important to extract the best from the less. To achieve those goals, a deep insight into 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, ArnaudBourniche, EricBossi, AdrienDavid, PascalNanjundaswamy, Harsha
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 XTX, 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 changes. We compare
Zhang, JiadiLi, XiaoKolmanovsky, IlyaTsutsumi, MunecikaNakada, Hayato
The lifetime and aging of the high voltage battery is one of the major discussion points for the end-customer to decide between buying a car with an electric powertrain or still using a conventional powertrain. Therefore, the provision of adequate vehicles to the end-customer, the aging of the high voltage battery become an important topic for the complete vehicle development. In addition, also legal regulations (e.g. EU7) will preset minimum requirements for the warranty of the high voltage battery. These circumstances define the lifetime / aging of the HV battery to be a complete vehicle development target, which needs to be developed. The paper will present a method for the development process of a lifetime target from complete vehicle perspective. The method is based on the generation of a representative monthly power profile and temperature profile. Depending on a monthly user routine, ambient temperature profile and charging behavior, the vehicle specific battery power profile
Martin, Michael
At present, tire failures directly affect road safety, and the number of incidents caused by them is gradually increasing. Examining wheel attachment loosening 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 wheel attachment loosening. 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
Liu, JianjianZhang, ZhijieWang, ZhenfengMa, GuangtaoShi, MeijuanLiu, JingZhao, BinggenLu, Yukun
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-ChenNorris, WilliamPatterson, AlbertSreenivas, Ramavarapu S.Soylemezoglu PhD, AhmetNottage, Dustin S.
The present study investigates optimization of ultimate tensile strength (UTS) in FSW of AA2024-T3 and SS304 in a butt joint configuration. An L18 mixed-level orthogonal array was used to design 18 experiments, varying tool rotational speed (450, 560, and 710 rpm), traverse speed (20, 25, and 40 mm/min), and pin offset (1 and 1.5 mm toward the Al side). The tool rotational speed had the greatest influence on UTS, contributing nearly one-third of the total variance, followed by pin offset and traverse speed. The optimal combination, 450 rpm, 20 mm/min, 1.5 mm offset, yielded a UTS of 344.7 MPa and a joint efficiency of 78.3%. At this setting, peak temperatures reached ~356 °C, ensuring sufficient plasticization and uniform mixing of the Al–SS interface, producing a refined stir zone with an average grain size of 4.2 μm. Fracture analysis revealed ductile failure at the optimal parameters, whereas suboptimal conditions resulted in brittle or mixed fractures due to either insufficient or
Mir, Fayaz AhmadKhan, Noor ZamanPali, Harveer Singh
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, AndrewMohammad, Utayba
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, WeiminLv, ZhilongOu, Shiqi(Shawn)
The onset of the COVID-19 pandemic in early 2020 introduced an unprecedented disruption to global industries, including automotive service and maintenance. As technicians and service shops struggled to balance operational continuity with safety, uncertainty surrounded best practices for servicing potentially dangerous vehicle cabins and air conditioning systems. This paper traces the evolution of these early efforts, from initial confusion and informal guidance to the establishment of the SAE Cabin Disinfection Practices Committee (SAE TEVCDPC) and the eventual publication of SAE J3260 and SAE J3290. It also considers work done by ASHRAE (the American Society of Heating, Refrigerating and Air-Conditioning Engineers), which simultaneously worked on ASHRAE Standard 62.1 and 241. These standards, along with contributions from subject matter experts, formalized the automotive industry’s response to infection control in vehicle environments, integrating scientific understanding with
Schaeber, StevenMathur, GursaranTaylor, Dwayne
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