Browse Topic: Maintenance and Aftermarket

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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
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
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
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 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
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.
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
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
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
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
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
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
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
Enabling Sustainable E-Mobility: An Edge–Cloud Collaborative Framework for Lifecycle Health Management of Electric Vehicle Batteries2026-01-0460To 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)
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
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
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
Dynamic Stiffness Prediction in Cracked Cantilever Beams Using Enhanced ANN Techniques2026-28-0050To be published on 02/12/2026
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
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
Digital Annex of Medium/Heavy-Duty E/E Systems Diagnosis NomenclatureJ2403DA_202601 (Current)1/31/2026
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
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
Optimisation-Driven Framework for Heterogeneous Battery-Pack Mixing in Fleet Applications2026-26-02091/16/2026
Fleet owners often encounter significant logistical and financial problems when dealing with battery packs of different ages and conditions. The standard industry practice is to replace old batteries with identical new ones. This process is inefficient because it costs a lot, creates too much inventory, and eliminates battery packs that are still useful too soon. The problem worsens when manufacturers stop making older battery models, which can force a vehicle to retire early. This paper puts forward a framework for mixing different types of battery packs to deliver the performance needed for a vehicle’s mission. We show how this works in three everyday service situations: 1) Repair, when a single damaged pack needs replacing; 2) Life Extension, where aged packs are combined with newer ones to meet mission range; and 3) Performance Restoration, which uses next-gen packs when the original parts are obsolete. The study shows that a vehicle can complete its required missions by
Nair, Sandeep R., Ravichandran, Balu Prashanth, Hallberg, Linus
Auto Braking System for Preventing Commercial Vehicle Overloading2026-26-00321/16/2026
Overloading in vehicles, particularly trucks and city buses, poses a critical challenge in India, contributing to increased traffic accidents, economic losses, and infrastructural damage. This issue stems from excessive loads that compromise vehicle stability, reduce braking efficiency, accelerate tire wear, and heighten the risk of catastrophic failures. To address this, we propose an intelligent overloading control and warning system that integrates load-sensing technology with real-time corrective measures. The system employs precision load sensors (e.g., air below deflection monitoring via pressure sensors) to measure vehicle weight dynamically. When the load exceeds predefined thresholds, the system triggers a multi-stage response: 1 Visual/Audio Warning – Alerts the driver to take corrective action. 2 Braking Intervention – If ignored, the braking applied, immobilizing the vehicle until the load is reduced. Experimental validation involved ten iterative tests to map deflection-to
Raj, Amritesh, Pujari, Sachin, Londhe, Mahesh, Shirke, Sumeet, Shinde, Akshay
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
Analysis of Engagement Probability for Dog Clutch Geometry Parameters in Heavy-Duty Automated Mechanical Transmissions2026-26-04371/16/2026
This study presents a simulation-based approach to estimate the dog clutch engagement probability maps under different vehicle operating conditions. The developed probability function incorporates multiple critical parameters including initial speed differential between engaging components, application of countershaft brake, number of tooth in dog clutch, friction coefficients at tooth interfaces, applied actuation force, dog tooth geometry, and component inertia. Using MATLAB and Simulink, comprehensive simulation models were developed to analyze engagement dynamics and produce detailed probability maps at different vehicle speeds. The present work effectively outlines optimal operational zones for successful engagement while identifying critical regions prone to tooth clash and engagement failure. The effect of tooth geometry on engagement probability has been investigated to study its effect on the optimal mismatch speeds. The resulting engagement maps serve as valuable diagnostic
Khan, Mohammad Adeeb, Khan, Nuruzzama Mehadi, Koona, Rammohan
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
Development of a GUI-Based Pitch Sequence Optimization Tool for Tire Noise Reduction2026-26-03301/16/2026
Tire noise reduction is important for improving ride comfort, especially in electric vehicle due to lack of engine noise and majority of the noise generated in-cabin is from tire-road interaction. Therefore, the tire tread pattern contribution is one of the important criteria for NVH performance apart from other structurally generated noise and vibration. In this work a GUI-based pitch sequence optimization tool is developed to support tire design engineers in generating acoustically optimized tread sequences. The tool operates in two modes: without constraints, where the pitch sequence is optimized freely to reduce tonal noise levels; and with constraints, where specific design rules are applied to preserve pattern consistency and manufacturability. The key point to be considered in this pitch sequence is that it should be reducing the tonal sound and equally spread i.e., the same pitch cannot be concentrated on one side which may lead to non-uniformity. So, the restriction is that
Sampathraghavan, Lakshmi, Ramarathnam, Krishna Kumar, Mantripragada PhD, Krishna Teja, Ramachandran, Neeraj
Rear Wiper Motor with Nozzle Integration2026-26-06001/16/2026
In today's dynamic driving environments, reliable rear wiping functionality is essential for maintaining safe rearward visibility. This study sharing the next-generation rear wiper motor assembly that seamlessly integrates the washer nozzle, delivering improved performance alongside key benefits such as better Buzz, Squeak, and Rattle (BSR) characteristics, reduced system complexity, cost savings, and enhanced perceived quality. This integrated design simplifies the hose routing which improves the compactness and the efficiency of the design. This also enhances the spray coverage and minimizes the dry wiping unlike the traditional systems that position the washer nozzle separately. A non-return valve (NRV) is incorporated to eliminate spray delays ass it maintains consistent water flow giving cleaning effectiveness. Since this makes the nonfunctional parts completely leak proof due to the advanced sealing, it increases the durability and reliability in long run. As this proposal offers
Dhage, Prashant, K, Nagarajan, G, Sabari Rajan
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
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
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
Artificial Intelligence in Passenger Cars: Unlocking Intelligent Mobility and Human-Centric Vehicle Innovation2026-26-06721/16/2026
Artificial Intelligence (AI) is radically transforming the automotive industry, particularly in the domain of passenger vehicles where personalization, safety, diagnostics, and efficiency. This paper presents an exploration of AI/ML applications through quadrant of the key pillars: Customer Experience (CX), Vehicle Diagnostics, Lifecycle Management, and Connected Technologies. Through detailed use cases, including AI-powered active suspension systems, intelligent fault code prioritization, and eco-routing strategies, we demonstrate how AI models such as machine learning, deep learning, and computer vision are reshaping both the user experience and engineering workflow of modern electric vehicles (EVs). This paper combines simulations, pseudo-algorithms and data-centric examples of the combined depth of functionality and deployment readiness of these technologies. In addition to technical effectiveness, the paper also discusses the challenges at field level in adopting AI at scale i.e
Hazra, Sandip, Tangadpalliwar, Sonali, Khan, Arkadip
System-Level Simulation to Design a Hydrogen Powered Refuse Collection Vehicle Based on Real-World Fleet Operational Data2026-26-03991/16/2026
This study addresses one of the challenges in the energy transition of heavy-duty vehicles by converting a diesel Refuse Collection Vehicle (RCV) into a hydrogen-powered prototype. The research is part of the VeH2Dem project funded by NextGenerationEU and focuses on dimensioning the complete hydrogen propulsion system for a RCV, including the energy storage capacity, without compromising payload or operational functionality. The development of the propulsion system is based on a comprehensive analysis of operational data extracted from fleet management systems, complemented by detailed instrumental monitoring of various collection routes. This methodology ensured that the prototype inherits performance equivalent to the original internal combustion engine vehicle across all evaluated scenarios. The vehicle performance objectives were established following a comparative analysis with solutions currently available in the RCV market, incorporating statistical analyses to ensure continuous
Cano, Pablo, Barrio, Roberto, Roche, Marina, de-Lima, Daniela, Batista, Sara, Bertolí, Xavier
AI-Powered Intelligent Cognitive Lens for Driver Monitoring for Safe Transportation and Increased Fleet Efficiency Abstract2026-26-06341/16/2026
The rapid evolution of intelligent transportation systems has made drivers’ attentiveness and adherence to safety protocols more critical than ever. Traditional monitoring solutions often lack the adaptability to detect subtle behavioral changes in real time. This paper presents an advanced AI-powered Driver Monitoring System designed to continuously assess driver behavior, fatigue, distractions, and emotional state across various driving conditions. By providing real-time alerts and insights to vehicle owners, fleet operators, and safety personnel, the system significantly enhances road safety. The system integrates lightweight AI/ML algorithms, image processing techniques, perception models, and rule-based engines to deliver a comprehensive monitoring solution for multiple transportation modes, including automotive, rail, aerospace, and off-highway vehicles. Optimized for edge devices, the models ensure real-time processing with minimal computational overhead. Alerts are communicated
Chikhale, Shraddha, Sing, Sandip, Hivarkar, Umesh, Mardhekar, Amogh
Countering the New Threat from the Sky: Advanced IR Imaging Zoom Lenses for C-UAS SystemsTBMG-544341/1/2026
Current world conflicts have proven that drones are now indispensable tools in modern warfare. Whether for reconnaissance, loitering munitions, or asymmetric tactics that exploit vulnerabilities in conventional defenses, unmanned aerial systems (UAS) are redefining the rules of engagement.
Enhancing Signal Integrity and Security in Aerospace: RF-Over-Fiber Optics Hybrid Communications TechnologyTBMG-544351/1/2026
Without reliability and signal integrity, aerospace communications risk severe signal degradation and reduced security, posing risks to both personnel and mission-critical data. These challenges are particularly critical for applications that depend on military aircraft, satellite communications, and unmanned aerial vehicles (UAVs). As global demand for real-time data continues to surge, communication infrastructure requires regular maintenance and upgrades to maintain secure and reliable performance.
FDA Deploys Agentic AI to Modernize Regulatory WorkflowsTBMG-544141/1/2026
The U.S. Food and Drug Administration (FDA) has taken a substantial step in its digital modernization strategy with the deployment of agentic artificial intelligence capabilities across all agency employee groups. The move represents an expansion of the agency’s internal AI tools, intended to streamline complex, multi-step processes that support regulatory science, product review, and compliance activities. The deployment strengthens the FDA’s ongoing effort to embed structured, secure, and transparent AI systems into daily workflows, building on the rapid adoption of the LLM-based tool Elsa earlier this year.
Advances in Fiber Laser Welding for E-Mobility ManufacturingTBMG-544331/1/2026
High-power fiber lasers have become increasingly indispensable tools in automotive manufacturing over the past two decades. They are now widely deployed in welding and brazing applications for body-in-white, powertrains, engine components, and more.
Driver Personalized Lane Change Behavior Analysis Based on Attention Deep Embedding Clustering2025-01-734712/31/2025
The characteristic representation and in-depth understanding of driver personalized driving behavior are fundamental to achieving human-like autonomous driving, enhancing the rationality of autonomous driving decisions, and meeting passengers’ personalized needs. [ADDED]Personalized driving behavior refers to individual-specific patterns in vehicle operation that emerge from drivers’ unique combinations of skills, risk tolerance, and habitual responses.However, current research lacks consideration of cluster analysis in the feature representation stage and ignores the time-varying contribution degree of time series values to low-dimensional features, which inhibits further utilization and development. This study adopts deep embedding clustering method and introduces attention mechanism to investigate driver personalized high-speed lane change behavior.[ADDED] Using a comprehensive driving simulator platform, we collected 15-channel time series data from 12 drivers performing 216 lane
Dong, Haomin, Wang, Wei, Wang, Yue, Li, Lun, Yue, Yi, Tian, Jiaxiao, Han, Jiayi
Research Progress on Pavement Performance Prediction Models: A Review2025-99-024912/23/2025
Road maintenance plays a vital role in maintaining road conditions and ensuring safety, especially in a country with an extensive road network like China. To accurately predict pavement performance, optimize maintenance strategy, reduce cost and improve road efficiency, the paper systematically combed and evaluated the prediction model of pavement performance. Firstly, the importance of pavement maintenance and the background of pavement maintenance performance prediction model are described, and explicit models (mechanical-empirical model, stochastic process, time series analysis) and machine learning models (regression analysis, support vector machine, integrated learning, artificial neural network, deep learning) are introduced respectively. The basic principle, representative study, advantages and disadvantages of each model are introduced in detail. Comparative analysis shows that the traditional explicit model is simple and effective, easy to explain, but difficult to deal with
Ma, Muyun, Dong, Qiao, Lin, Yelong
Research on Energy Consumption Simulation and Carbon Emission Simulation in the Rail Transit Operation and Maintenance Phase Based on DesignBuilder: A Case Study of Tongyuan Road South Station on Suzhou Metro2025-99-022212/23/2025
At present, the rail transit network in China is well-developed and has become an important means of daily travel for residents. Rail transit stations usually achieve seamless connections with other transportation modes such as buses, taxis, and shared bicycles. It will evolve into an integrated transportation hub, effectively alleviating the pressure on urban surface transportation and playing a pivotal role in dispersing a large number of commuters. Meanwhile, with the vigorous development of rail transit, its energy consumption is increasing. It results in considerable carbon emissions, which poses a huge challenge to China’s goal of achieving carbon neutrality by 2030. In this paper, the building energy consumption simulation tool DesignBuilder is used to model the Tongyuan Road South Station of Suzhou Rail Transit. The energy consumption generated during its operation stage is simulated, and the carbon emissions produced by Tongyuan Road South Station at this stage are calculated
Zhu, Ning
Research on Railway Electric Locomotive Styling Design Based on KE-AHP2025-99-020912/23/2025
Objective:Methods:Conclusion:
Dai, Hongzhou, Li, Jian, Zhao, Di, Liu, Haoran
Design and Application of Large-Segment Cable Hanging Baskets for Long-Span High-Speed Railway Cable-Stayed Bridges2025-99-021912/23/2025
With the advancement of cable-stayed bridge construction technology, the application of long-span concrete girder cable-stayed bridge is gradually extensive, making the study of construction technology and equipment for concrete main girders increasingly important. The cable hanging basket, a crucial piece of equipment for cable-stayed bridge construction, maximizes the cable’s bearing capacity, improves construction efficiency, and ensures safety and stability during construction. However, due to the varying structural designs and construction environments, the cable hanging basket must be specifically tailored for different cases. The Hanjiang Bridge on the Xi’an-Shijiazhuang High-speed Railway is China’s first steel-truss-reinforced PC box-girder cable-stayed bridge, with a main span of 420 meters. If conventional diamond-shaped hanging baskets are used for suspended casting of small sections, the construction period will not meet the construction requirements of this bridge. To
Li, Jian
A Literature Review on Application of Maintenance and Management Strategies for Electric-Vertical Take-Off and Landing Aircraft’s Maintenance, Repair, and Overhaul Organizations01-18-03-001612/18/2025
In the context of emerging technology developed for advanced air mobility concept, its maintenance protocols are not yet mature and existing aviation maintenance systems may not support electric-vertical take-off and landing (e-VTOL) needs. Thus, the operation of e-VTOL aircraft during its deployment stage necessitates the need for qualitative maintenance support. The main purpose of this study is to develop the basic structural principles of the projected new maintenance, repair, and overhaul (MRO) organization for e-VTOL air vehicles, which will support airworthiness through comprehensive maintenance approaches. Thus, the operation of e-VTOL aircraft during its deployment stage necessitates the need for qualitative maintenance support. The importance of the study is to offer standard procedures based on management and maintenance strategies, application of predictive and prescriptive maintenance tools, which pose a significant contribution to ensuring safety, reliability, and cost
Imanov, Tapdig, Bozdereli, Arzu
Application of a Process Mining Tool for Three-Way Match Analysis in the Procure-to-Pay Process of a Multinational Auto Parts Company2025-36-023612/18/2025
Process mining emerges as a very important tool in the automotive industry to improve processes and increase efficiency. Its use allows the identification of bottlenecks and opportunities for improvement in production processes, contributing to increased productivity and cost reduction. This article aimed to evaluate the benefits of applying the Process Mining tool by conducting a Three-way match analysis in the Procure-to-pay (PTP) process of a company in the auto parts sector, seeking to identify opportunities for improvement. Analysis using process mining in PTP of the organization allowed us to identify significant number of cases of price discrepancies were observed in relation to orders related to services, being 2.5 times higher than orders related to materials. Additionally, quantity discrepancies represented 24% of the cases analyzed, compared to only 1.5% of price discrepancies. Of the materials involved in these price discrepancies, approximately 63% were not registered in
Rosa da Silva, Petterson Maxwell, Campos, Renato de, Franco, Bruno Chaves
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