Browse Topic: Quality, Reliability, and Durability

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Open Source LLM Performance in Automating Embedded C Software Quality Improvements for Automotive2026-01-0103To be published on 04/07/2026
The study presented in this paper explored the potential of five open-source Large Language Models (LLMs) with parameter counts between 30 billion and 50 billion to automate enhancements in code quality and developer productivity. The evaluated models - CodeLlama, Command-R, Deepseek R1, Nemotron, and QwQ - were assessed on their ability to refactor a large and complex automotive mechatronic C language function. This assessment focused on adherence to provided code quality standards and successful compilation of the refactored function within its original code module. The evaluation also compared the impact of parameter count, hyperparameter tuning, model architecture, and fine-tuning. This comparison revealed that larger models generally outperformed smaller models against the provided quality standards. Additionally, hyperparameter tuning yielded a moderate improvement in performance. The study further highlighted that model architecture and fine-tuning had less predictable effects
Struck, Daniel, Kumaraswamy, Samanth
Self-Supervised Gaussian-Based Framework for Robust Static-Dynamic Decomposition and Real-Time Urban Scene Reconstruction2026-01-0010To be published on 04/07/2026
We propose a self-supervised Gaussian-based framework that enhances the robustness and efficiency of static-dynamic decomposition and high-fidelity reconstruction in autonomous driving scenarios. Existing approaches demonstrate promising performance but remain prone to noisy motion segmentation, overfitting on sparse LiDAR observations, and degraded accuracy in low-texture or distant regions, resulting in unstable geometry. To address these challenges, our method introduces a feature fusion module that jointly exploits image semantics and geometric cues, enabling more reliable motion prior extraction under noise and illumination variations. A cross-sequence geometric consistency constraint is further designed to regularize reconstruction across temporal and viewpoint changes, ensuring physically coherent scene representations. In addition, we formulate an efficient Gaussian parameter optimization strategy that constrains scale and normal updates, preventing unrealistic ellipsoid growth
Feng, Runlei, Wang, Ning, Zhang, Zhihao
Numerical Framework for Predicting Power Loss and Oil Flow Dynamics in Dip-Lubricated Gear Systems2026-01-0411To be published on 04/07/2026
Oil churning and windage power losses in dip-lubricated gearboxes can significantly improve overall transmission efficiency, particularly at high rotational speeds. As modern gearbox systems are pushed toward higher efficiency and reliability, understanding and predicting these losses becomes increasingly important. In addition to energy dissipation, the associated multiphase flow phenomena—such as oil splashing, thin film formation along gear surfaces, and aeration of the sump—strongly influence lubrication effectiveness, heat transfer, and component durability. Capturing these effects requires a robust numerical strategy that can resolve both power loss mechanisms and multiphase flow dynamics with sufficient accuracy. In this study, a single spur gear is numerically analyzed under varying oil depths and rotational speeds to quantify total power loss and investigate oil flow patterns. The computational approach employs a volume-of-fluid multiphase framework, and the predictions are
Mahyawansi, Pratik J., Haria, Hiral, Pandey, Ashutosh, KHAJEH HOSSEINI D, NAVVAB
Study on the Regulation of the Three-Phase Microenvironment in Low-Platinum MEA2026-01-0443To be published on 04/07/2026
With the growth of energy demand, fuel cells as efficient and clean energy devices, have attracted increasing attention. However, the high cost of membrane electrode assembly (MEA) restricts their large-scale application. Therefore, reducing the platinum usage and improving performance have become key research point. In this work, MEA was prepared and excellent performance of 1.52 W·cm-2 was achieved at a low platinum loading. The influence of different ionomer/carbon (I/C) ratio on the performance of fuel cells was systematically investigated. It was found that the performance of the MEA was the highest when the I/C ratio is 0.6. Quantifying hydrophilic and hydrophobic characteristics of catalyst layers with varying ionomer contents revealed that the proton conduction efficiency is optimal when the I/C ratio is 0.6. This balance established efficient proton conduction pathways, from the results of proton conduction impedance testing. SEM analysis demonstrated that pore structure
Li, Xin, Cai, Xin, Lin, Rui
Development of Full Articulation Subsystem FEA Model for Validating Vehicle Suspension Durability2026-01-0190To be published on 04/07/2026
Vehicle durability is a cornerstone of automotive engineering, directly impacting customer satisfaction, brand reputation, and warranty costs. Traditionally durability validation of suspension systems often rely on virtual validation of individual components (an approach which can overlook complex non-linear system interactions) and followed by expensive full vehicle physical tests which happen very late in the vehicle development phase, which often results in correlation gap between virtual and physical realms, resulting in components redesigning and production delays. This paper presents a more efficient, high-fidelity, full-articulation suspension subsystem finite element (FE) model development specifically for durability assessments. This integrated model enables comprehensive block cycle durability assessments, providing a holistic understanding of system behavior and eliminating the inefficiencies of analyzing components in isolation. This methodology yields significant
Bavgi, Sai Kiran
Maintaining a Healthy Safety Culture in Autonomous Vehicle Development and Operations2026-01-0528To be published on 04/07/2026
The deployment of autonomous vehicles (AVs) requires not only technical excellence but also the cultivation of a robust organizational safety culture. While safety engineering standards and assurance processes provide essential structure, a culture that prioritizes learning, accountability, and continuous improvement is critical to ensuring public trust and operational resilience. This paper explores how UL 4600, the comprehensive safety standard for the evaluation of autonomous systems, and Safety Performance Indicators (SPIs) can be leveraged to build and sustain a Just Culture within an AV company. UL 4600 emphasizes systematic hazard identification, safety case construction, and ongoing evidence generation. When applied beyond compliance, it provides a framework for embedding safety considerations into day-to-day engineering and operational decision making. By mapping UL 4600 clauses into organizational processes and linking them with measurable SPIs—such as rates of system
Wagner, Michael, Gittleman, Michele
Predictive Modeling and Sensitivity Analysis of Thermal Runaway in 800V Lithium-Ion Battery Pack Module Using DFSS Methodology2026-01-0124To be published on 04/07/2026
Thermal runaway in high-voltage lithium-ion battery modules should focus on critical safety and design challenges in electric vehicle applications, which need predictive methods that enhance passenger safety and support regulatory compliance. The primary purpose of a lithium-ion battery in an electric vehicle is to provide reliable energy storage while maintaining safe operation under different operating conditions. This study proposes a Design for Six Sigma (DFSS) methodology to virtually predict and correlate thermal runaway and its propagation in an 800V high-power lithium-ion battery module. Conventional propagation analysis relies heavily on physical testing, whereas the DFSS-based virtual framework enables cost-effective evaluation at early design stages. Input factors included are heat transfer pathways, which are sensitive to the temperature changes, as well as thermal propagation time. Control factors are the design or process parameters that engineers use to establish the
Dixit, Manish, Raja, Vinayak, Gudiyella, Soumya
Application of DFSS for Optimizing Thermal Protection in Electric Vehicles During Battery Thermal Runaway Events2026-01-0142To be published on 04/07/2026
Battery thermal runaway is a major safety concern in electric vehicles because of the extreme heat and hazardous gases released during cell failure. These venting events can quickly raise the temperature of the battery enclosure and cabin floor, threatening occupant safety. To address this challenge, this study employs the Design for Six Sigma (DFSS) methodology to design and optimize a thermal protection system that delays and limits heat transfer to the cabin. A physics based transient heat transfer model was combined with DFSS principles to systematically evaluate insulation materials, shield layouts, surface emissivity, and layer geometry. An L 18 orthogonal array was used to identify key parameters and quantify their influence on thermal robustness. The optimized architecture reduced cabin floor temperature rise under severe runaway conditions (600–900 °C vent gas), meeting occupant egress safety requirements. Findings confirm DFSS as an effective framework for developing high
El-Sharkawy, Alaa, Asar, Mona, Taha, Nahla, Sheta, Mai
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
Sensorless Estimation of In-Cabin CO2 Concentration for Model-Based Air Recirculation Control2026-01-0130To be published on 04/07/2026
This paper introduces a sensorless approach for data-driven modeling of in-cabin CO2 concentration to optimize air recirculation flap control without the need for a dedicated CO2 sensor. Elevated CO2 concentrations, resulting from passenger exhalation, can impair occupants’ cognitive function and comfort. Current state-of-the-art solutions rely either on time-based control strategies, which lack responsiveness to actual cabin conditions, or on direct CO2 measurements via sensors, which increase system complexity and costs. In contrast, the proposed approach aims to replicate the benefits of sensor-based control without requiring physical sensors. In this study, a model-based methodology is presented, utilizing empirical CO2 measurement data collected from real-world test drives at varying occupancies, fan stages, vehicle speeds, and flap positions. Data acquisition involves a multi-gas analyzer positioned within the passengers’ breathing zone under controlled operation of the vehicle’s
Stürmer, Michael, Geier, Bertram, Hofstetter, Martin, Hirz, Mario
Data-Driven Objective Road-Driving Classification For Durable Design Of Vehicles2026-01-0181To be published on 04/07/2026
Durability development in the automotive industry depends on a clear understanding of how road surfaces and driving characteristics affect structural road loads and fatigue. Traditionally, road surface classification has been subjective (e.g., city, highway, rural), and done through driving instrumented vehicles over a small selection of roads. The variations in driving characteristics that are often consequent to the road surface quality is rarely accounted for in designing vehicle level durability tests. This makes it difficult to establish targets for the durability testing that accurately match the wide variations in real-world roads and driving across the market of vehicles. This paper presents a data-driven approach to objectively classify road surface and driving characteristics using metrics derived from existing vehicle and road response metrics like Vibration Dose Value (VDV), International Roughness Index (IRI) and statistical estimates of vehicle speed and acceleration
Shaurya, Shubham, Ramakrishnan, Sankaran, Demiri, Albion, Khapane, Prashant
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
Minimal Binary Patching for Safety-Critical Systems2026-01-0088To be published on 04/07/2026
Patching vulnerabilities in safety-critical domains such as automotive and aerospace is costly and complex. A small code modification can trigger a complete rebuild, producing a binary with widespread changes. This inflates patch size, complicates regression testing, and makes over-the-air (OTA) updates inefficient, as traditional binary diffs often replace large portions of the executable. We present a binary rewriting–based experiment that shows the feasibility of a patch that updates only the affected bytes by computing the impact of a code change at the binary level. This produces minimal, localized patches rather than regenerated executables. The preliminary experiment shows that a single source change, which leads to thousands of modified bytes after recompilation, can be captured with only a few bytes using our method. For automotive and aerospace systems, this technique reduces patch size, conserves bandwidth, and minimizes disruption to certified software, offering a promising
Awadhutkar, Payas, Tamrawi, Ahmed, Sauceda, Jeremias
An Updated Correlation Study between the Full Size Wind Tunnels of General Motors, Ford Motor Company, and FCA US LLC2026-01-0612To be published on 04/07/2026
As automotive aerodynamic testing facilities evolve to capture more real-world behavior, updating the correlation between old and new technologies is essential. Recently, the three-member consortium of the United States Council for Automotive Research (USCAR) - FCA US LLC, Ford Motor Company, and General Motors - transitioned from full-size static ground plane facilities to 5-belt moving ground plane wind tunnel facilities. The primary objective of this study was to update the correlation data sets to maintain consistent and robust data sharing among companies, which is the cornerstone of USCAR efforts. To achieve this, a set of updated correlation data sets were calculated to replace the original correlation study results from 2008. Additionally, the methodology for applying correlation equations was revised from using averaged wind tunnel data to employing direct wind tunnel-to-wind tunnel correlation equations. In a two-phase correlation effort conducted in 2022 and 2025, the three
Nastov, Alexander, Lounsberry, Todd, Madin, Trevor, Langmeyer, Gregory, Fadler, Gregory, Skinner, Shaun, Horton, Damien
Active site characterization of CuSCR catalysts under H2-ICE exhaust gas conditions2026-01-0361To be published on 04/07/2026
Hydrogen engines (H2-ICEs) can be a bridge technology for reducing carbon emissions until fuel cells and battery systems reach full commercial readiness. Because they share similar components to diesel, allowing the use of existing components and infrastructure, making them easier to scale. At the same time, H2-ICEs can deliver diesel-like performance, durability, and reliability while maintaining the advantage of fast refueling. Lean-burn H2-ICE offers enhanced thermal efficiency while minimizing engine-out NOx emissions. One of the main challenges under lean-burn H2-ICE operation is the significant drop in turbo-out temperatures combined with higher water content and the possible presence of unburned hydrogen in the exhaust. This study examines the impact of excess water and residual hydrogen on Cu-SCR durability, active site chemistry, and stability for the case with and without an upstream oxidation catalyst, through aging tests at 450 °C and 550 °C. Changes in Cu redox cycles were
Kim, Mi-Young, Daya, Rohil, Kamasamudram, krishna
Predicting Electric Vehicle Interior Noise Quality from Drive Unit End-of-Line Vibration Testing2026-01-0223To be published on 04/07/2026
The Noise, Vibration, and Harshness (NVH) quality of electric vehicles (EVs) is heavily influenced by the performance of the electric drive unit. As a critical step in production, End-of-Line (EOL) testing of drive units is used to assess and control component-level NVH before vehicle assembly. However, the correlation between EOL test results and final vehicle interior noise quality, which directly impacts customer satisfaction, is not always fully understood. This paper presents a methodology for characterizing and predicting vehicle interior noise quality based on data from drive unit EOL vibration testing. Our study investigates the intricate relationship between drive unit assembly variations, component tolerances, and the resulting vibrational response. We establish a robust correlation between these drive unit characteristics and both objective vehicle interior noise levels and subjective customer perception. The findings provide a framework for using EOL data to proactively
Arvanitis, Anastasios, Jangid, Kuldeep
The Necessity of a Holistic Safety Evaluation Framework for AI-Based Automation Features2026-01-0522To be published on 04/07/2026
The intersection of Safety of Intended Functionality (SOTIF) and Functional Safety (FuSa) analysis for driving automation features has traditionally excluded Quality Management (QM) components from rigorous safety impact evaluations. Historically, QM components have not been classified as safety-relevant, and therefore their potential influence on overall system safety has often been overlooked. However, recent advancements in artificial intelligence (AI) integration within automated driving systems have revealed that these components can, under certain conditions, contribute to SOTIF-related hazardous risks. This emerging reality challenges long-standing assumptions and underscores the need for a more inclusive approach to safety analysis. Furthermore, compliance with evolving AI safety standards, such as ISO/PAS 8800, necessitates a re-evaluation of safety considerations for components previously deemed outside the scope of FuSa and SOTIF frameworks. This paper examines the necessity
Abbaspour, Ali Reza, Mahadevan, Shabin, Zwirglmaier, Kilian, Stafford, Jeff
Quality Assurance Sampling and Testing, Corrosion- and Heat-Resistant Steel and Alloy ForgingsAMS2374G (Current)3/13/2026
This specification covers quality assurance sampling and testing procedures used to determine conformance to applicable material specifications of corrosion- and heat-resistant steel and alloy forgings.
AMS F Corrosion and Heat Resistant Alloys Committee
Aerospace & Defense Technology: March 202626AERD033/5/2026
Dassault Systèmes and NVIDIA Partner to Build Industrial AI Platform Powering Virtual Twins RISC-V: Bringing Greater Reliability, Safety, and Security to Military and Aerospace Systems The Enduring Value of Highly Optimized, Non-Standardized Systems Manufacturing Spotlight: Rugged Computing for Infinite Exploration Open Mission Systems: The Standard Driving Defense Innovation New CMOSS Chassis, Plug-in-Card Prototypes in Development for Army Vehicles How Forterra Is Enabling Modular Military Vehicle Autonomy Microchip’s New Processor Enables Scalable Computing Performance In-Memory Computing Chip Is a Processing Breakthrough for On-Device AI Applications
RISC-V: Bringing Greater Reliability, Safety, and Security to Military and Aerospace Systems26AERD03_023/1/2026
Military and aerospace applications have become increasingly complex real-time systems. Multi-core SoCs improve performance but create new challenges in maintaining and verifying deterministic behavior. Connected systems require exceptional security to protect code from external cyberattacks. Evolving functional safety and reliability standards that keep raising the bar mean developers need to begin comprehensive testing sooner if they are going to meet tighter design schedules. Finally, certifying these complex systems has become even more difficult. To help OEMs meet these challenges, the RISC-V architecture has been designed with unique capabilities that support reliability and security in the development of safety-critical applications. With its open instruction set architecture, modularity, and extensibility, RISC-V accelerates the design of functionally safe systems while reducing the complexity, cost, and risk associated with certification to standards like DO-178C and ISO 26262
Manufacturing Spotlight: Rugged Computing for Infinite Exploration26AERD03_043/1/2026
In the rapidly evolving aerospace and defense landscape, simply keeping pace with trends isn't enough. Technology is advancing faster than ever, and in mission critical applications, failure is not an option. Systems must endure harsh environments while meeting uncompromising quality standards - an imperative that demands relentless innovation. Enter the Coyotes: WOLF's specialists in next generation rugged embedded systems, small form factor design, and bold, practical ideas. Whether on Earth or in orbit, they expand what high performance embedded computing can do across ground, orbital, lunar and deep space operations. Their work spans R&D, rapid prototyping and new product development for edge computing and artificial intelligence (AI) enabled imaging.
Counterfeit Materiel; Assuring Acquisition of Authentic and Conforming MaterielAS6174B (Current)2/17/2026
This SAE Standard provides requirements and guidance to: Develop a Materiel authenticity plan. Procure Materiel from reliable sources. Assure authenticity and conformance of procured Materiel, including methods such as certification, traceability, testing, and inspection appropriate to the Commodity/item in question. Control Materiel identified as counterfeit. Report Suspect or Counterfeit Materiel to other potential users and Authorities Having Jurisdiction.
G-21 Counterfeit Materiel Committee
Business Reliability Growth for Automotive Engineering, Volume 4R-5522/17/2026
In a world where every business process is under pressure to perform faster, safer, and more reliably, this book delivers a powerful roadmap for sustained operational excellence. Centered on the proven methodology of Design of Experiments (DOE), it shows how organizations can move beyond reactive problem-solving to systematic reliability growth. From well-defined standard operating practices to management-level decision-making, the book connects strategy, data, and execution to create repeatable, measurable results across the enterprise. Readers are guided through practical, real-world applications of DOE, from selecting the right factors and levels to executing robust experiments, analyzing outcomes, validating solutions, and continuously monitoring performance. Each chapter translates complex statistical and engineering concepts into actionable business value, helping teams improve quality, reduce waste, and increase return on investment. Key capabilities explored in this book
Chiang, Young J.
Dual use Electric Vehicle Infrastructure for Enhancing Grid Resilience and Urban Sustainability2026-28-01142/12/2026
The growing global adoption of electric vehicles (EVs) has resulted in a spike in the number of EV charging stations. As EVs have become more and more popular worldwide, a large number of EV charging stations are opening up to accommodate their demands. During grid failures, an EV charging station can also serve as a flexible load connected to the grid to balance out voltage fluctuations. An EV charging station when powered using a separate source, such as solar or wind, can function as a powerhouse, bringing electricity to the grid when it's needed. Therefore, instead of installing more equipment to sustain voltage, the current EV charging station can be efficiently used to meet the grid's needs during failures. These stations have the potential to be dynamic, grid-connected assets for sustainable cities and communities in addition to their core function of vehicle charging (SDG 11). Because of their dual purpose, they can serve as adaptable loads that reduce voltage variations during
R, Uthra, Rangarajan, Ravi, D, Suchitra, D, Anitha
Efficient Multi-Parameter Optimization of a Twist Beam Rear Axle for Electric Vehicles Using TOPSIS Method for Durability2026-28-00672/12/2026
This study investigates the parameter optimization of a Rear Twist Beam (RTB) for an electric vehicle (EV) during the early stages of product development. Adapting an RTB design from an Internal Combustion Engine (ICE) vehicle platform presents several challenges, one of the challenges is accommodating increased rear vehicle load while minimizing cost, with maintaining existing rear hard points. To address this, we employed an experimental study for Computer-Aided Engineering (CAE) using the Taguchi DOE, which avoids costly physical durability tests. The key design parameters considered were the thickness and material grade of the RTB's components, specifically the cross beam, trailing arms, and reinforcements while preserving their original shapes. L8 Orthogonal array is constructed to design the experiment and identify the influence of the design parameters on durability performance, and the optimal combinations for maximizing durability are identified by using TOPSIS multi objective
Madaswamy, Arunachalam, Dhanraj, Sudharsun, Govindaraju, Karthik, Lokaiah, Srinivasan
A Data-Driven Method for Typical Landing Gear Structure Optimization Based on Neural Networks01-19-01-00022/6/2026
The landing gear, as a crucial component of an aircraft, is pivotal for maintaining the safety and reliability of air travel. This study introduces a data-driven structural optimization method aimed at mitigating the peak strain on the landing gear’s rocker arm. The initial phase involves selecting nine design variables for parametric modeling to generate an initial dataset. Subsequently, the Maximum Information Coefficient (MIC) technique is used to conduct a parameter sensitivity analysis, enabling the identification and elimination of variables with minimal influence. A comparative analysis between the Genetic Algorithm–Backpropagation Neural Network (GA-BPNN) and BPNN reveals that GA-BPNN has a superior fitting capability on the enhanced dataset. By applying Particle Swarm Optimization (PSO), the optimal solution for GA-BPNN is identified. The implementation of this optimized method results in a 38.16% reduction in peak strain, validating its feasibility and reliability in
Chen, Hu, Shi, Shi, Wang, Meng, Fang, Xingbo, Wei, Xiaohui, Nie, Hong
Quality Assurance Sampling and Testing, Carbon and Low-Alloy Steel ForgingsAMS2372J (Current)2/1/2026
This specification covers quality assurance sampling and testing procedures used to determine conformance to applicable specification requirements of carbon and low-alloy steel forgings.
AMS E Carbon and Low Alloy Steels Committee
The Critical Impact Of SAE Aerospace Standards: Certified AS1895/7 and /23 Metal Seals26AERP02_092/1/2026
How engineers can ensure safety, reliability and quality in aerospace systems. Courbevoie, Île-de-France In an industry where failure is not an option and precision is paramount, aerospace manufacturers and suppliers are constantly seeking components and system solutions that deliver trusted reliability, performance, and compliance. Industry standards are a key part of achieving these high expectations, bringing together global leaders in the mobility industries to create defined, repeatable methods and consistent processes. One of these aerospace standards is AS1895 developed by SAE International - a critical standard due to the need for durable components that can withstand extreme conditions and offer high performance: high-temperature resistance, pressure sealing, and long service life with a cost-effective installation method. Leading aerospace companies such as Eaton and Honeywell have been manufacturing components that meet this standard for a long period of time.
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
Investigating Thermal Fatigue Cracks in Exhaust Manifolds of Longitudinally Mounted 1.2L 4-Cylinder Engines2026-26-04881/16/2026
This study addresses the challenge of ensuring the durability of closed couple exhaust manifolds in the compact engine bays of modern vehicles, focusing on a longitudinally mounted 1.2L 4-cylinder engine. The original sheet metal Exhaust manifold design failed the thermal fatigue bench durability test, requiring a complete redesign to improve strength without changing materials. Initial simulation predictions significantly deviated from physical test results, with repeated cracks observed during accelerated thermal fatigue bench testing, despite simulations predicting a higher number of cycles before failure. This difference highlighted the need for a deeper understanding of the manifold's failure modes, primarily thermal fatigue, and mechanical vibration during engine transients. The design of experiment (DOE) approach was used to find the effect of different parameters e.g., gas temperature, surface temperature, air flow, thermal gradient, on the durability result & also to
Krishnan, K.S.Gopala, Mishra, Ashutosh, Yadav, Sanjay Kumar, Kumar, Deepak, Tripathi, Manas, Kumar, Prabhakar
Thermal Shock Test Rig for CNG Shut-Off Valve2026-26-05261/16/2026
In Automobile, Gasoline Engines are being used along with electrically operated shut-off valve installed at the roof of bus in case of higher capacity of CNG systems. In order to start/ stop CNG supply from cylinder for running of engine/ safety/ servicing an electrical operated ignition switch/ key controlled CNG Shut-Off Valve is placed just after the cylinders. There have been few failures of these CNG shut-off valves in field application. On investigation, it was observed that the CNG shut-off valve gets failed due to water ingress in coils from the cracks on surface generated due to spray of water (due to daily washing of bus and rain) on heated shut-off valves. In order to validate this field failure and subsequent validation of modified design, a need was felt to use a test rig which can exactly simulate the water spray based thermal shocks. However, there was no low cost facility available to simulate the field service condition for validation. Therefore, a low cost test set-up
Srivastava, Pravin Kumar, Vivekanand, Vivekanand, Kumar, Satish
Improvement Study of Style Steel Wheel Durability in Multiple Pothole Impacts2026-26-05391/16/2026
This study focuses on improving the durability of steel wheel rims subjected to Multiple Pothole which is commonly found in Indian village roads — a critical scenario affecting vehicle safety and wheel lifespan. Initial steel wheel designs often face significant deformation or failure under repeated strikes and resulting in tyre air loss due to wheel bend, prompting the need for enhanced performance standards. In this research, a combination of finite element modelling, experimental impact testing, and material optimization strategies were employed to assess and improve the structural integrity of steel rims. Key parameters such as rim profile geometry & material composition were systematically varied to evaluate their influence on impact resistance. Results demonstrate that strategic design modifications and material enhancements can significantly increase the rim's ability to absorb energy and resist bending without substantial weight penalties. The findings offer practical
DEsigan, Lakshmipathy, P, Praveen, K, Chandramohan, C, Santhosh
Integrated Quality Assurance Frameworks for Testing Advanced Automotive Systems in the Era of ADAS and E-Mobility2026-26-05681/16/2026
Ensuring the safety and functionality of sophisticated vehicle technologies has grown more difficult as the automotive industry quickly shifts to intelligent, electric, and connected mobility. Software-defined architectures, electric powertrains, and advanced driver assistance systems (ADAS) all require strong quality assurance (QA) frameworks that can handle the multi domain nature of contemporary vehicle platforms. In order to thoroughly assess the functionality and dependability of next generation automotive systems, this paper proposes an integrated QA methodology that blends conventional testing procedures with model-based validation, digital twin environments, and real-time system monitoring. The suggested framework, which includes hardware-in-the-loop (HIL), software-in-the-loop (SIL), and over-the-air (OTA) testing techniques, concentrates on end-to-end traceability from specifications to validation. Simulating intricate situations for ADAS, electric vehicle battery temperature
Komanduri, Arun Srinivas, Srivastava, Anuj
Comparative Analysis and Implementation of Data Streaming Methodologies for Vehicle Navigation Mode for Electric Trucks2026-26-06921/16/2026
As electric trucks become more central to modern logistics, the need for smarter, more adaptive route planning is growing rapidly. This paper presents a key navigation feature for analyzing and recalibrating such optimized routes in real time. Integrating map features into the navigation mode improves user experience by offering real-time navigation and dynamic route adjustments based on traffic updates, road closures, vehicle coordinates and deviation in expected energy consumption. This study compares the performance of Server sent events (SSE), web sockets, and Application programming interface (API) polling methodologies, focusing on metrics such as data transmission efficiency, latency, resource utilization, scalability, and reliability. Our results demonstrate the advantages and limitations of each method, providing insights into their suitability for real-time route optimization in electric truck logistics. The results highlight the potential of SSE in achieving efficient and
Bhandari, Mehul, Kaur, Prabhjot, Dadoo, Vishal, Mahendrakar, Shrinidhi, Ramanaiah, Rachala
An Investigation into the Structural Impacts of Off-Road Maneuvers on Rear Axle Upper Link Mounting Bracket2026-26-04901/16/2026
Multi-link rigid axle suspension is widely used as a rear suspension system for body-on-frame SUVs. The upper link in a multi link rear suspension plays a critical role in managing the vertical and longitudinal positioning of the axle, while the lower link ensures stability by regulating the axle's movement in the horizontal plane. This coordinated functionality of upper and lower link allows for controlled axle dynamics during compression and rebound, significantly enhancing ride comfort and improving vehicle handling characteristics. This study examines the failure of an upper link mounting bracket on the rear axle of an SUV during off-road events, despite no failures observed in other durability tests. Root cause analysis is conducted on failed samples to determine the specific reasons for failure only in off-road conditions. Additionally, the investigation focuses on understanding the dynamic loads experienced by the upper link during vehicle operation across various durability
J, Akhil, Senthil Raja, T, Ghumare, Dheeraj, Chilakala, Raghavendra, Kundan, Lal, Mohapatra, Durga Prasad
Multispeed EV Transmission – Gear Shift Simulation and Validation2026-26-01571/16/2026
The advancement of electric vehicle (EV) transmission systems is currently a prominent trend aimed at decreasing carbon emissions and providing eco-friendly transportation alternatives. Most of the EV transmissions are single speed, but research conducted on multi speed EV transmissions show higher efficiency, good performance, high speed and torque demand when compared with single speed counterparts. Most of the multi speed EV transmissions that are developed are of non-synchromesh type, which have direct effect on NVH, driving dynamics and durability of drivetrain components. Due to aforementioned factors, gearshift analysis becomes critical for development. Simulation model is developed at early development phase for initial feedback. Using the feedback, drivetrain can be optimized furthermore and test on physical parts can be conducted for final verification. This paper provides a simulation based approach for modelling non-synchromesh two speed EV transmission using Simulation X
Kansagara, Smit, Thambala, Prashanth, Sutar, Suresh, Todtermuschke, Karsten, Patel, Hiral
Resilient Design Strategies for Wireless Charger ECUs: A Proactive Threat Analysis and Risk Assessment Framework for Ensuring Cybersecurity in EV Charging Ecosystems2026-26-01731/16/2026
The proliferation of wireless charging technology in electric vehicles (EVs) introduces novel cybersecurity challenges that require comprehensive threat analysis and resilient design strategies. This paper presents a proactive framework for assessing and mitigating cybersecurity risks in wireless charger Electronic Control Units (ECUs), addressing the unique vulnerabilities inherent in electromagnetic power transfer systems. Through systematic threat modeling, vulnerability assessment, and the development of defense-in-depth strategies, this research establishes design principles for creating robust wireless charging ecosystems resistant to cyber threats. The proposed framework integrates hardware security modules, encrypted communication protocols, and adaptive threat detection mechanisms to ensure operational integrity while maintaining charging efficiency. Experimental validation demonstrates the effectiveness of the proposed security measures in preventing unauthorized access, data
Uthaman, Sreekumar, Mulay, Abhijit B, Gadekar, Pundlik
A Machine Learning Approach to Early-Stage Failure Prediction in Traction Motor Manufacturing2026-26-02811/16/2026
Traction motors technology has, driving the EV industry forward with more efficient, lightweight, and durable solutions. However, despite these advancements, noise testing at the end of the production line remains a critical stage for identifying manufacturing defects in traction motors. Hence early fault detection in traction motors is crucial to ensure safety and reliability of EV. This research contributes a solution that predicts early-fault detection, supporting improved reliability, reduced material cost and minimizing process time in the series production line. To identify the root cause of this problem, historical quality data has been acquired from manufacturing plants to enable efficient analysis. Feature selection was then carried out using embedded and wrapper methods to identify the most important features. These selected features were subsequently used as input for ML models. The best accuracy was achieved using SVC model for early-stage motor failure prediction.
Gaikwad, Pooja, Nangare, Kapilraj, Suryawanshi, Chaitanya
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
Dimensional Management in Automotive Vehicle Design & Development for Perceived Quality (PQ) Improvement in Buses2026-26-04471/16/2026
Perceived quality (PQ) is one of the most important factors in engineering signoff as well as customer delight and product improvement (feel, look & touch). The PQ is something related to feel of product in terms of gap, flushness, fitment and appearance as per the costumer perceptions and expectations. Validation of design and engineering quality with respect to perceived quality is required for overall product appearance in the eyes of prospective customers. This is equally applicable in today’s automotive bus industry along with the other customer oriented industry. In this paper we have explored the dimensional management scope in improving the PQ requirements and expectations by utilizing the dimensional variation analysis (DVA) approach. We have tried to explain the fundamentals of vehicle aggregates fitment process and impact of fitment tolerances as used in DVA model to resolve vehicle packaging issues (critical gaps & clearance variation as per expected no. of vehicles to be
Singh, Vinay Kumar, Dewangan, Ved Prakash, Kumar, Rahul, Deep, Amar
Predictive Simulation Framework for Tyre Curb Impact Durability Assessment and Design Optimization2026-26-03961/16/2026
With increased deterioration of road conditions worldwide, automotive OEMs face significant challenges in ensuring the durability of structural components. The tyre being the primary point of contact with the road is expected to endure harshest of impacts while maintaining the other performance functions such as Ride & Handling, Rolling resistance, Braking. Thus, it is considered as the most challenging component in terms of design optimization for durability. The current development method relies on physical testing of initial samples, followed by iterative construction changes to meet durability requirements, often giving trade-off in Ride & Handling performance. To overcome these challenges, a frugal simulation-based methodology has been developed for predicting tyre curb impact durability before vehicle-level testing so that corrective action can be taken during the design stage.
Sundaramoorthy, Ragasruoban, Lenka, Visweswara
Totem-Pole PFC and LLC Resonant Converter based 6.6kW On-Board Charger for LEV Applications2026-26-01601/16/2026
As light electric vehicles (LEVs) gain popularity, the development of efficient and compact on-board chargers (OBCs) has become a critical area of focus in power electronics. Conventional AC-DC topologies often face challenges, including high inrush currents during startup, which can stress components and affect system reliability. Furthermore, DC-DC converters often have a limited soft-switching range under light load conditions, leading to increased switching losses and reduced efficiency. This paper proposes a novel 6.6 kW on-board charger architecture comprising a bridgeless totem-pole power factor correction (PFC) stage and an isolated LLC resonant DC-DC converter. The main contribution lies in the specific focus on enhancing startup behavior and switching performance. In PFC converters, limiting inrush current during startup is crucial, especially with fast-switching wide-bandgap devices like SiC or GaN. Conventional soft-start techniques fall short in of ensuring smooth voltage
Patil, Amruta, Bagade, Aniket
Automated Evaluation of Drive File Simulation Accuracy2026-26-05281/16/2026
In the area of structural durability testing using servo hydraulic actuators, developing drive files for the actuators is a major step. Testing outcomes depend on ensuring the simulation accuracy of each drive file. These drive files are developed in an iterative process for different test track surfaces at different road and load combinations till the time we achieved better correlation. Evaluation of simulation accuracy of the drive files is an extensive manual review process making it time-consuming and resource-intensive. To address this challenge, an application has been develop to automate the comparison of actuator signals with predefined target signal files. This tool enables quick and accurate analysis of each drive file in a test run facilitating a comprehensive review of signal deviations. Each test run is having thousands of drive files based on road-load mix and actuator settings. This application helped us in significantly optimizing the simulation workflow by reducing
Soni, Yash, Katake, Vrishali, Mullapudi, Dattatreyudu, Chaskar, Mithun
A Practical Approach to Reduce Gear Whine Noise through Gear Tooth Contact Analysis in an Agricultural Tractor2026-26-03451/16/2026
Gear noise is a common challenge that all gear manufacturers must contend with. In tractors, while it is often sufficiently low in intensity to not pose a significant issue, there are instances where gear whine may occur which is noticeable. In such cases, identifying the source and effectively addressing the problem can prove to be particularly difficult. This paper addresses the root cause analysis carried out for the evaluation of factors influencing whine noise behavior of Spiral bevel gear pair (SO2) in a tractor transmission system. Numerous publications have been published on gear noise of spiral bevel gear pair, too many to list here. However, once the gearbox assembled into the transmission, such models are of limited practical value. The work explained in this paper is a typical example offers avenues in correcting the issue using more limited means.
P, Bharath, P, Priyadarshan, Janarthanan, Devakumara Raja, Chavan, Amit
Enhanced Methodologies for Predicting Automotive Wheel Bearing Life and Damage Using RLDA2026-26-04821/16/2026
The durability of wheel bearings is assessed in terms of raceway life and flange life. Raceway life focuses on the performance and damage tolerance of rolling elements, while flange life evaluates the structural integrity of wheel flanges under operational stresses. Traditionally, durability predictions relied on conventional design methods and analytic formulas for raceway spalling, as well as static load assumptions for flange fatigue analysis. Recently, integrating design of experiments (DOE) with traditional approaches has enhanced these methods, enabling systematic evaluation of design variables and loading conditions. This paper introduces a methodology for analyzing raceway life and damage in automotive wheel bearings using RLDA (Road Load Data Acquisition) data. The process involves acquiring raw deterministic load data, filtering it to preserve high-peaked signals, and transforming the filtered data into block cycles derived from load time histories. Each block cycle contains
Narendra, Vishwanath, Mane, Yogiraj, Paua, Ketan, Singh, Ram Krishnan, Vellandi, Vikraman
Fatigue Failure Analysis for Automotive Transmission2026-26-05771/16/2026
A fatigue failure in the transmission input shaft was identified during a bench-level endurance test under 2nd gear loading conditions. The test transmission’s input shaft comprises fixed 1st, reverse, and 2nd gears, with the remaining gears mounted as floating. The shaft was subjected to cyclic torsional loads, and failure occurred after a defined number of cycles. Metallurgical analysis revealed a brittle fracture surface with crack initiation at the outer surface, propagating to core in a helical pattern, ultimately resulting in complete shaft fracture. To monitor and replicate the failure, the test setup was instrumented with a Reilhofer Delta Analyzer for early fault detection. TTL signals from accelerometers mounted on the transmission and a bench speed sensor were fed into the system, which generates FFT spectra and trend indices. A warning alarm triggered upon deviation in the trend index, indicating premature damage initiation. The test was subsequently halted for component
Kushwaha, Rakesh, Patel, Hiral, Navale, Pradeep
Combustion Noise Quality Improvement in a Common rail Diesel Engine at Low Idle using Taguchi DOE2026-26-03291/16/2026
Noise quality at idle condition is an important factor which influences customer comfort. Modern diesel engines with stringent emission norms together with fuel economy requirements pose challenges to noise control. Common rail engine technology has advantage of precise fuel delivery and combustion control which needs optimization to achieve the conflicting requirements of noise, emission and fuel efficiency. Engine noise at low idle condition is dominated by combustion noise which depends on rate of pressure rise inside the cylinder during combustion. The important parameters which influence cylinder pressure rise are fuel injection timing, pilot injection quantity and its separation, rail pressure and EGR valve position. The study on effect of these parameters at varying levels demand large no of experiments. Taguchi design of experiments is a statistical technique which can be used to optimize these parameters by significantly reducing no of experiments needed to achieve the desired
P, Priyadarshan, Chavan, Amit, A, Kannanswamy, Patil, Sandeep, Chaudhari, Vishal V
Effect of Pipe Bending by Rotary Tube Bending Process on Durability of Frame Structure2026-26-03701/16/2026
Automobile frames, particularly trellis frame structures, are engineered for superior dynamic performance, with stiffness being a paramount consideration1. These frames frequently utilize welded tubes, a manufacturing process made more complex by the necessity of bending tubes to precise angles to meet packaging and assembly requirements2. This bending, however, induces residual stresses that can substantially compromise the frame's durability3. This investigation employs a detailed finite element simulation to analyse the structural deformation and residual stresses that arise during the bending of Cold Electric Welded (CEW) annealed round pipes4. A comprehensive 3D mechanical model, incorporating realistic tooling and contact interactions, was developed to accurately simulate shape change, ovality, and wall thickness redistribution during the bending process5. CEW pipes, unlike their Electric Resistance Welded (ERW) counterparts, possess minimal initial forming stresses, and the
Rajwani, Ishwar, Khare, Saharash
New Generation Natural Rubber-Based Bump Stopper with Improved NVH Characteristics2026-26-02921/16/2026
In automotive suspension systems, components like bump stoppers and jounce bumpers play critical roles in controlling suspension travel and enhancing ride comfort. Material selection for these components is driven by functional demands and performance criteria. Traditionally, Natural rubber (NR) has traditionally been favored for bump stopper applications due to its excellent vibration absorption, tear resistance, cost-effectiveness, and biodegradability. However, in more demanding environments, it has been largely replaced by microcellular polyurethane (PU) elastomers, which offer superior durability, environmental resistance, and enhanced noise, vibration, and harshness (NVH) performance. This study revisits NR with the goal of re-establishing its viability by enhancing its performance to match or surpass that of PU. Through compound optimization and advanced material processing techniques, significant improvements have been achieved in NR’s mechanical strength, compression set
Murugesan, Annarajan, Hingalaje, Abhijeet, Perumal, Mathavan, Pawar, Rohit
Advanced Defect Detection Techniques Using AI, CAD Data, and Computer Vision2026-26-06441/16/2026
In area of modern manufacturing, ensuring product quality and minimizing defects are utmost important for maintaining competitive advantage and customer satisfaction. This paper presents an innovative approach to detect defect by leveraging Artificial Intelligence (AI) models trained using Computer-Aided Design (CAD) data. Traditional defect detection methods often rely on physical inspection, which can be time-consuming and prone to human error. The conventional method of developing an AI model requires a physical part data, By utilizing CAD data, the time to develop an AI model and implementing it to production line station can be saved drastically. This approach involves the use of AI algorithms trained on CAD models to detect and classify defects in real-time. The field trial results demonstrate the effectiveness of this approach in various industrial applications, highlighting its potential to revolutionize defect detection in manufacturing.
Kulkarni, Prasad Ramesh, Sahu, Dilip, Joshi, Chandrashekhar, Khatavkar, Akshay, Poddar, Shivani, Deep, Amar
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