Browse Topic: Failure modes and effects analysis (FMEA)

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Smart-ROPS — Machine Learning-Based Rear Occupant Protection System2026-28-0149To be published on 11/05/2026
Children dying in hot cars is not a new problem. Since 1998, more than 1,000 children have died this way in the United States alone — roughly 37 every year. That number has barely been reduced, which tells something alarming: the solutions built so far aren't solving it completely. Door-based reminders are a good example of why. They trigger when a rear door opens, but opening a door doesn't confirm a child was left behind. Single-sensor setups have their own gaps too; no single sensor handles every real-world scenario reliably on its own. Multi-sensor systems get closer, but most use rigid threshold-based rules that fall apart the moment conditions deviate — a sleeping infant barely moves, a child under a blanket reads completely differently on a thermal sensor. This paper proposes Smart-ROPS (Smart Rear Occupant Protection System), an embedded ML architecture that targets these specific failure modes without needing expensive hardware or complex software. Four sensor types feed the system: millimeter-wave radar, CO₂, thermal infrared, and ultrasonic. Data from these passes through three layers — the Perception Layer handles initial sensor fusion, the Processing Layer runs a decision tree as the primary classifier, and when confidence is low, a shallow neural network steps in for ambiguous cases. If a risk is confirmed, the Intervention Layer manages the response: starting with a smartphone alert and cabin ventilation, escalating to emergency services if needed. This is presented as an architectural design contribution — hardware prototyping and real-world testing are left for future work.
Shrimal, Harsh
Research on Failure Mode Verification of Civil Aircraft Based on Reliability Data2026-99-231410/30/2026
To verify the accuracy and completeness of FMEA and FTA, this paper proposes a comprehensive failure mode verification method based on reliability data. This method collects multi-source reliability data and identify actual failure modes occurring in equipment during operation firstly, thereby compiling a list of actual failure modes. Next, this list is compared with the FMEA report from the design phase to verify the failure modes themselves. A deeper qualitative verification of the causes, mechanisms, and impacts of the failures is then conducted, leading to the correction and updating of the FTA logical structure to ensure consistency between the safety analysis model and the actual failure logic.Building upon the qualitative verification, the method proceeds to quantitative verification. A comparative analysis is conducted between the actual failure rates of the failure modes and the estimated values in the FMEA. Using the validated failure rate data, the probability of the FTA top event is recalculated and compared against the safety target probability specified in airworthiness regulations to achieve quantitative verification of the failure condition probability. As a core innovation and enhancement of the method, this paper introduces sensitivity analysis. Through tools such as calculating Birnbaum importance and plotting tornado plots, it quantitatively assesses the sensitivity and impact of uncertainties in the failure rate parameters of each bottom event on the probability of failure condition, thereby identifying the key failure modes. The research findings provide theoretical support and a practical engineering foundation for evaluating the actual reliability level of the aircraft fleet, improving the accuracy of safety analysis during the design phase, and guiding preventive maintenance and design improvements.
Han, Bing, Li, Haiwei
A Method for Evaluating System Robustness in Stochastic, High-Dimensional, Multi-Failure Mode Models2026-01-75289/22/2026
This paper introduces a method of predicting system robustness using engineering models with aleatory uncertainty. The Stochastic Robustness Evaluation and Categorization (SREC) method is useful for the design of systems where performance along some dimension is limited by several failure modes. SREC integrates and extends interaction plots and Monte Carlo methods to complex engineering models. These complex models are often difficult to evaluate and visualize due to the curse of dimensionality. SREC is effective for non-linear, non-convex, non-monotonic, and discontinuous models due to its basis in Monte Carlo methods. The method is based on the identification of low-performing solutions, the construction of probability density functions and intervals from these solutions, and the categorization of the input space based on the likelihood of low-performing solutions occurring. Using SREC in the late stages of the design process provides insight to the designer about possible improvements in the system’s robustness. A ground vehicle model based on a US Army test procedure is used to demonstrate the effectiveness of SREC on high-dimensional, multi-failure mode models.
Louis, Edward, Mocko, Gregory, Taylor, Evan
Physics-Constrained Procedural Generation of Synthetic Environments for the Robust Validation of Autonomous Maneuver and Logistics2026-01-75499/22/2026
The validation of Autonomous Ground Vehicles (AGVs) and intelligent logistics planners is frequently compromised by the ”Sim-to-Real” gap, where simulation environments fail to replicate the physical friction of operational deployment. Ideally, valid test cases must enforce strict mobility constraints and impose realistic sustainment penalties; however, many current generation tools rely on idealized terrain interactions and infinite-resource assumptions. We present a real-time procedural framework designed to generate high-friction validation environments that stress-test the robustness of the System Under Test (SUT). The architecture integrates gradient-based terrain analysis with a stochastic contested logistics model. It ingests synthetic heightmaps to precompute mobility corridors, ensuring that every generated evaluation episode adheres to vehicle-specific traversability limits. Simultaneously, a logistics kernel enforces fuel consumption scaled by terrain gradients and models supply chain interdiction as a parameterized Bernoulli process. We validate this framework through a ”Digital Twin” methodology, demonstrating that terrain-aware generation eliminates invalid initialization states (0% mobility violations) while the logistics model induces operationally relevant failure modes in the SUT. This unclassified, open-architecture approach supports DoD Verification, Validation, and Accreditation (VV&A) requirements by providing deterministic, reproducible edge cases for autonomous system evaluation.
Soykan, Bulent, Rabadi, Ghaith, Bochenek, Grace, Paul, Victor J.
Efficient Integrated Reliability and Maintainability in a Digital Engineering Environment as Part of the Army Transformation Initiative2026-01-75319/22/2026
This paper presents an efficiently structured and integrated Reliability and Maintainability (R&M) process for implementation in a Digital Engineering (DE) environment during the product design phase, in support of the Army Transformation Initiative. This process links key R&M tasks to influence their execution and clarifies the relationship between a system's design risk and its R&M performance. The significant contributions of this process are: 1) establishing intra- and inter-task linkages for R&M activities within a comprehensive, systemic design process; 2) defining the direct impact on component and system-level R&M as a function of strategic design risk mitigation activities through a central Design Failure Modes and Effects Analysis (DFMEA); and 3) executing R&M tasks within a fully integrated, closed-loop R&M modeling and risk assessment approach, supported by a DE and AI-enabled environment.
Bieda, John, Gargrave, Jason, Damiani, Michael, Marlowe, Kasey, McGuinness, Sean
Intelligent Optimization Simulation Framework for Test and Evaluation of Autonomous Systems2026-01-75519/22/2026
This paper describes ongoing research and development of an efficient optimization/search–based modeling and simulation framework for rapidly identifying low-performance scenarios in advanced autonomous systems. Ensuring predictable, safe behavior across complex, integrated systems remains a core operational test-and-evaluation challenge. Our goal is to balance rigorous validation with timely deployment. We are developing TEAAS (Test & Evaluation of Advanced Autonomous Systems), a scalable, faster-than-real-time framework designed to uncover critical failure scenarios efficiently. Key features include GPU-accelerated parallel simulation and learning, computational intelligence–based search of optimal parameters, uncertainty quantification for reproducibility, and real-time physics-accurate sensor models. We conducted simulation experiments to evaluate and demonstrate the framework performance for two black-box ground-vehicle autonomous systems. Key results were that adequate uncertainty quantification can be achieved with as few as 10 repeated runs per simulation scenario, sensor realism has a significant effect on failure rate, distinct differences between the two autonomies failure modes were identified, and our efficient optimization/search methods identify critical performance regions in a small fraction of the number of simulations required by a naïve Monte Carlo search.
Snarski, S., Menozzi, A., Persons, B., Lazar, D., Khan, N.
Robust Fiber Optics for Ground Combat Vehicles: Unlocking the Bandwidth for the Mission2026-01-75419/22/2026
The U.S. Army’s Modular Open Systems Approach (MOSA) is driving data-centric vehicle architectures that demand higher bandwidth, faster decision loops, and greater cross-platform interoperability. Despite these needs, stakeholders hesitate to adopt fiber optics because of perceived fragility, field-retrofit FOD risk, and soldier-handling concerns. This paper characterizes common fiber failure modes in ground-vehicle environments and demonstrates how system-level ruggedization, connector design, and qualified components mitigate those risks. Drawing on demonstrated experience with hardened optics, connector-integrated transceivers, sealed media converters, and rugged cabling, we summarize practical architecture and field maintenance procedures that enable reliable fiber deployment in vehicles. Results show that, with appropriate component selection, installation practices, and built-in diagnostics, fiber optics can provide a robust, maintainable backbone for future ground vehicle networks.
Kouns, Heath, Simms, Marc, Weiss, Evan, Breedlove, Joe
Safe State Definition and Verification for Distributed Multi-Controller EMB Architectures2026-01-08009/14/2026
The Electro-Mechanical Brake (EMB) system is an essential technology for safe braking in modern vehicles. However, the adoption of multi-controller architectures has introduced new challenges to conventional Safe State strategies. Traditionally, the Safe State defined in functional safety means "function shutdown," and in accordance with ISO 26262-1:2018 (Part 1: Vocabulary), aims for an "operational mode without risks exceeding reasonable levels." However, in the multi-controller architecture of EMB systems, the Fail-Operational Safe State concept is applied, where the system continues to provide limited functions even in the event of faults. It is essential to verify whether such operational modes actually satisfy the safety requirements of ISO 26262-3 and ISO 26262-4. This paper redefines the Safe State according to failure modes in EMB systems, analyzes system state transitions, and presents a coherence analysis methodology for validating the availability of resources required to provide limited functions in the Fail-Operational Safe State. Through this approach, potential design defects in multi-controller-based EMB systems can be detected early, validated across 1,149,952 fault scenarios with zero total-failure outcomes, and traceability of functional safety requirements can be established.
Kim, Kang San
Numerical Investigation of In-Plane Antisymmetric Failure Modes and Load-Carrying Mechanisms of Steel Portal Piers2026-99-15949/11/2026
A nonlinear finite element model was applied to study the in-plane instability of steel portal piers, in which initial geometric imperfections, welding residual stresses, and material nonlinearity were considered. The modeling procedure was compared with experimental results from box-section members, and consistent tendencies in load level and deformation evolution were observed. In the numerical analyses, the initial elastic buckling configuration exhibited an in-plane antisymmetric form. As loading continued beyond the elastic range, this deformation pattern persisted. With further loading, the deformation remained purely axial while combining compression with bending. During this stage, plastic hinges appeared near the column tops, while lateral displacement became clearly observable. Comparison models with different geometric proportions show that variations in the span-to-height ratio and the beam–column stiffness ratio influence how instability develops and where plastic deformation tends to localize. From a design perspective, these trends can be considered when distinguishing instability characteristics and selecting stiffness proportions between beams and piers.
Li, Jie, Shangguan, Bing, Cheng, Zhangxu, Ruan, Furong, Bai, Fan
Validation Study of the Jaguar Land Rover Aerodynamic Computational Fluid Dynamics Process Using Metric-Based Assessment Criteria2026-01-50729/3/2026
Credibility of simulation data has always been fundamental in aerodynamic vehicle development, as a significant amount of early design phase work is conducted virtually before a physical test property is made. As the automotive industry pivots toward artificial intelligence and machine learning techniques to assist in aerodynamic development, training these models with simulation data requires a comprehensive understanding of the accuracy and validity of the underlying simulation. It is critical these systems are trained from reliable data with a full understanding of both the limitations and predictive performance of the computational fluid dynamics (CFD) process and the wind tunnel facility it is benchmarked against. Validation and verification studies have been a long-established set of guidelines to determine if the simulation model appropriately reflects reality (validation) or if it has been set with robust numerical schemes, mesh settings, or boundary conditions (verification). The work presented here shows a comprehensive validation study with more than 400 test configurations and 18 vehicle properties. It evaluates Reynolds-averaged Navier–Stokes (RANS) and detached eddy simulation (DES) approaches using moving reference frame (MRF) and rigid body motion (RBM) to account for wheel rotation and comparing STAR-CCM+ CFD process and the FKFS Aeroacoustic Wind Tunnel (AAWT). The results demonstrate that DES—particularly when wheel rotation is modeled using RBM—provides the highest overall predictive performance, with a drag accuracy from −2% to +4% for 80% of cases with corrections applied, which gets to ±2% for over 95% cases with an additional calibration step. A metric-based assessment criterion that combines key performance metrics into a single detection event (DE) score derived from failure mode effects analysis (FMEA) principles is proposed with an example shown for the 2021 Range Rover Velar. The benefit being that it removes a more judgement-based, qualitative approach, aiding toolset selection and methods development gaps.
Beves, Christopher, Simmonds, Nicholas, Dalmau Graells, Eric
Failure Analysis of the Safety Valve Spring in a Dangerous Goods Tanker2026-99-03138/14/2026
During the operation, a spring in the built-in safety valve of a dangerous goods tanker. A comprehensive failure analysis of the material was conducted through macroscopic and microscopic inspections, metallographic analysis, energy spectrum analysis (EDS), and hardness tests. The failure mode of the broken spring was brittle fracture. The fracture morphology was like that of ice sugar, and the chemical composition of the spring steel met the specified requirements. The main cause of fracture failure is the mechanical damage to the inner surface during the spring manufacturing process, which leads to stress concentration in the damaged area and ultimately results in fracture. In addition, manufacturers should strengthen and standardize the production process to prevent mechanical damage and select high-purity spring steel to improve the durability of the springs.
Yang, Lijun, Li, Qingshan, Xiong, Mingming, Liu, Mingming, Wu, Junyao, Yu, Lang, Zhang, Zewei, Xie, Xumeng
683 Guidance for Electronic Shop Reports in Aviation MaintenanceARINC683 (Current)8/4/2026
The purpose of this standard is to provide guidance for the content, format and two-way electronic exchange of data between a Service Provider and the Customer. The standard is focused on the production of an electronic Shop Findings Report by the Service Provider, and to promote automated electronic data exchange.
Aviation Maintenance Committee
Analysis of Leakage Causes of 6ADG011VR Branch Pipe in a Power Plant2026-99-02317/31/2026
The socket-welded branch pipes of a power plant leaked and failed in the ADG System. To find the cause of the failure, this paper analyzed the failure reasons of the socket-welded branch pipes through macroscopic inspection, chemical composition analysis, mechanical performance test, metallographic inspection, and fracture microscopic analysis. The results show that the failure mode leading to leakage in socket-welded pipelines is fatigue cracking, which initiated at the weld toe on the outer wall and propagated inward. The vibration generated by the system environment is the main cause of fatigue cracking of socket-welded branch pipes.
Zhu, Jinhui
Reliability Evaluation of Five-Axis Machining Center based on Improved FAHPEWM-Extension Theory2026-99-01027/31/2026
To address the challenge of accurately assessing the reliability of complex equipment, a reliability evaluation system for a five-axis machining center was developed based on extension theory. By collecting and analyzing the failure modes and data of various subsystems, the strengths of the Fuzzy Analytic Hierarchy Process (FAHP) and the Entropy Weight Method (EWM) were combined to determine the weight of reliability evaluation indicators for both the machining center and its subsystems. A comprehensive assessment of the five-axis machining center's overall reliability was conducted. According to the principle of maximum membership, the reliability grades for the spindle system and the feed system were both rated as “excellent.”
Fei, Shouxiang, Wang, Dechao, Piao, Chengdao, Zheng, Shengkui
Analysis of the Cause of Knocking Noise in a Marine Dual-Power Dual-Branch Transmission Gear System2026-99-16507/24/2026
This study investigates the knocking noise phenomenon in a marine dual-power dual-branch transmission gear system. Vibration mechanisms are analyzed, and potential failure modes are assessed. System vibration data were evaluated using time-domain and frequency-domain methods. Results show that overall vibration levels remained within acceptable limits, with no indication of imminent failure. Physical inspection confirmed that the shaft, gears, bearings, housing, and installation met specifications, with no observed performance degradation or structural damage. By correlating noise occurrence with vessel loading conditions, a strong relationship was identified among gear transmission torque, the power distribution ratio between high-and low-pressure turbines, and the onset of knocking. Specifically, under low-load conditions, uneven power and torque distribution among the four gear branches led to insufficient loading on the low-pressure side. This light-load state induced instability in the low-pressure gears, resulting in periodic tooth disengagement or back-side tooth contact, which is established as the root cause of the knocking noise.
Gu, Chengzhong, Xu, Hanwei, Luo, Rirong, Ren, Fushan
A Review of Physical and Digital Infrastructure Standards and Guidelines to Support Deployment of Automated Vehicles in Rural Environments12-09-04-00307/23/2026
Connected and Automated Vehicles (CAVs) represent a transformative innovation poised to revolutionize roadway transportation by leveraging automated driving systems equipped with advanced sensors, high-performance computing, and communication technologies. While urban areas are the primary focus of current CAV developments, rural transportation systems risk being left behind despite the significant benefits that CAVs can bring to these regions. This article, therefore, explores the physical and digital infrastructure requirements for the safe deployment of CAVs in rural areas, drawing insights from standards, recommendations, and guidelines developed by leading standard organizations. The study highlights the specific design of physical infrastructure, including traffic signs, traffic signals, and pavement markings, and digital infrastructure, including communication, sensing, and mapping, to ensure rural communities are effectively prepared to benefit from the potential of CAVs. As its primary contribution, this article provides a comprehensive review of existing standards and guidelines relevant to rural CAV deployment. By synthesizing guidance across multiple standard-setting organizations, this review delivers a structured analytical assessment of existing standards, revealing their limitations and misalignment with rural transportation contexts while highlighting emerging good practices. The article clarifies the applicability of current guidance to rural infrastructure, identifies systemic infrastructure-related failure modes, and informs context-aware planning considerations for efficient and scalable CAV deployment in rural areas.
Zakaria, Mohammed, Getahun, Tesfamichael, Tavasoli, Mahsa, Pandey, Venktesh, Sarrafzadeh, Abdolhossein, Karimoddini, Ali
Unidirectional Carbon Fiber Tape Epoxy Repair Prepreg, Vacuum Curing Part 2 - Qualification Program for Fiber, Carbon Fiber Tape Prepreg, and Film AdhesiveAMS6885/2 (Current)6/10/2026
AMS6885/2 gives specific information about the qualification program for unidirectional carbon fiber tape epoxy repair prepreg capable of curing under vacuum for repair of carbon fiber reinforced epoxy structures. The prepreg system shall include an epoxy film adhesive to be applied in a co-bonding process with the prepreg for solid laminate and sandwich bonding.
AMS CACRC Commercial Aircraft Composite Repair Committee
Improvement of rCF Behaviour through the Introduction of NF2026-37-00396/9/2026
This study investigates the structural improvement of recycled carbon fibre composites through hybridisation with continuous flax fibres to address sustainability concerns and performance limitations. Recycled carbon fibres, while environmentally beneficial, suffer from short, randomized orientations and lower mechanical properties limiting their application beyond decorative uses. This research explores whether incorporating unidirectional flax fibres can enhance rCF behaviour for structural applications. Six hybrid composite layup variants and two plain composites were manufactured using cold compression moulding with Ampro Bio Resin. Each hybrid configuration comprised eight layers, divided into four layers of recycled carbon and four layers of flax fibres oriented at 0°. Complete mechanical characterization was performed following ISO standards for tensile (ISO 527), flexural (ISO 178), and impact (ISO 179) testing. Results demonstrated significant performance improvements in hybrid composites. Among hybrids, layup 2 achieved 212.5 MPa tensile strength whilst layup 3 managed to achieve 20.5 GPa in stiffness. Flexural testing revealed layup 6 achieved the highest flexural modulus of 19.6 GPa among hybrids. Impact resistance improved dramatically with layup 3 demonstrating 186% improvement in energy absorption over recycled carbon fibre. The study confirms that hybridisation creates a positive effect, producing more predictable and durable materials. The complementary behaviour between brittle and ductile materials enhances damage tolerance and structural integrity, establishing a foundation for sustainable engineering materials suitable for automotive applications without compromising reliability.
Hnatyk, Dawid, Chrysanthou, Andreas, De Vuyst, Tom, Ismail, Sikiru
Novel Material Architecture for Enhanced High Cycle Fatigue Life in Turbofan Engine Fan Blades2026-26-07486/1/2026
High Cycle Fatigue (HCF) is a critical failure mode in turbofan blades, primarily driven by resonance phenomena when the blade’s natural frequency aligns with engine-induced excitations. Traditional approaches to mitigate HCF often involve geometric modifications or damping treatments, which can adversely affect aerodynamic performance or increase component weight. This study explores alternative methodologies to strategically alter the natural frequency of turbofan blades while maintaining aerodynamic efficiency and structural integrity. A novel material architecture is proposed, consisting of a dual-metallic configuration with a high-stiffness core and a lightweight, fatigue-resistant outer shell. This design enables precise tuning of the blade’s dynamic response by leveraging the contrasting mechanical properties of the core and outer materials. The dual-metallic structure shifts the natural frequency away from critical excitation zones, thereby reducing the risk of resonance-induced fatigue failure. Additionally, the hybrid configuration contributes to weight reduction compared to conventional monolithic blade designs, offering further performance benefits. Comprehensive Finite Element Analysis (FEA) is employed to evaluate modal characteristics and stress distribution of turbofan blades. Results indicate that the proposed architecture achieves a favorable balance between dynamic stability, structural robustness, and aerodynamic performance. The dual-metallic blade design not only improves HCF life but also provides a scalable framework for future turbofan blade optimization.
S, Ravivarman, Inamdar, Prachi, De, Rohit
Study on Impact Resistance of Sandwich-Structured Battery Protection Panels2026-99-17285/22/2026
With new energy vehicles developing rapidly, battery safety, as an important part of the impact on the range of new energy vehicles and vehicle safety, has become the focus of attention. The battery pack protection plate is a core component to protect the battery, its performance needs not only impact resistance, but also lightweight, honeycomb sandwich structure with its excellent energy absorption characteristics and weight reduction performance by the battery pack protection plate performance research. At present, the core-to-face sheet interaction in conventional sandwich structures subjected to impact loads has not been fully elucidated, and the quantitative characterization of damage is insufficient, so this paper aims to optimize the lightweight impact-resistant structure by exploring the synergistic energy dissipation mechanism between the high-strength core material and the steel plate. The study combines theory and simulation, adopting ideal rigid-plastic film theory to establish a critical response model to predict the structural failure threshold, equivalent single-layer theory to simplify the analysis of plywood, and a stiffness matrix model to quantify the structural mechanical contribution of each layer. A two-material synergistic design framework is proposed by fully considering the material properties and adopting the corresponding intrinsic structure and failure criteria for different materials. Analysis reveals that geometric confinement is a key characteristic of the honeycomb sandwich panel’s response and a strain gradient driving mechanism at low impact resistance, and a new energy distribution paradigm is found through the analysis of the energy absorption ratio. The theoretical and simulation results are in great agreement with each other, which just has a difference of 0.7% in the peak force, 1.4% in the critical displacement error, and less than 2% in the impulse integration error. The proposed dual-material co-design framework provides a solution for electric vehicle battery protection systems that balances lightweight and impact resistance.
Zhang, Guanghao, Zhang, Mingming, Luo, Changjie, Zhou, Jun, Zhang, Fengqiang, Yu, Wenze, Li, Jiongfeng, Guo, Qingrong
Design And Analysis of Low-Temperature Liquid Nitrogen Tank Car2026-99-17125/22/2026
The design and analysis of the wave plate of the tank body of the low-temperature liquid nitrogen tank car are carried out. According to the design method of the empirical formula, the 0.43 MPa low-temperature mobile liquid nitrogen tank body wave plate with the working temperature of -196°C to -178°C is optimized. According to the analysis and design standards, the stress distribution law of the mobile liquid nitrogen tank body under the forward impact condition is analyzed by the method of numerical analysis. The results show that the stress value will gradually increase near the junction of the tank body and the support, and the parts such as the head, the pad, the angle steel ring, and the Z3848 glass steel pipe meet the requirements of the analysis and design standards. At the same time, the first six orders of the natural mode vibration frequency of the tank body are analyzed, which provides a reliable and effective data analysis for the optimization design of the low-temperature liquid nitrogen tank body wave plate.
Ding, Xuqiang, Ni, Yiwei, Gu, Chen, Yan, Dongdong, Xu, Zhiquan, Wang, Qi
Research on Fault Diagnosis Agent of Monorail Crane Based on Knowledge Graph and Lightweight Large Model2026-99-07415/15/2026
The monorail crane is important in mining operations, and its operation affects both safety and efficiency. Currently, fault diagnosis for monorail cranes has several challenges, such as heterogeneous mixing of multimodal data, poor use of knowledge, low real-time requirements, and high deployment costs for large-scale models. To solve these problems, we present an agent framework using a multimodal knowledge graph and a lightweight large model. In particular, we construct a fault knowledge graph for monorail cranes, organizing professional knowledge about components, failure modes, symptoms, and maintenance. By employing retrieval-augmented generation (RAG) technology, the knowledge graph is merged with the Qwen lightweight large model (low-rank adaptation) for fine-tuning to develop a diagnostic agent with task planning, tool invocation and memory. The experimental results show that the agent framework reduces “machine hallucination” and outperforms conventional diagnostic accuracy, response speed and resource efficiency, thus offering a safe and efficient solution for intelligent operation and maintenance of mining equipment.
Zhang, Yixuan, Xue, Shun, Bi, Xiang, Wei, Xing, Kang, Ranyu, Jue, Jie, Cheng, Liruiran
Potential Failure Mode and Effects Analysis (FMEA) Including Design FMEA, Supplemental FMEA-MSR, and Process FMEAJ1739_202605 (Current)5/8/2026
This FMEA standard describes potential failure mode and effects analysis in design (DFMEA), supplemental FMEA-MSR, and potential failure mode and effects analysis in manufacturing and assembly processes (PFMEA). It assists users in the identification and mitigation of risk by providing appropriate terms, requirements, rating charts, and worksheets. As a standard, this document contains requirements—”must”—and recommendations—”should”—to guide the user through the FMEA process. The FMEA process and documentation must comply with this standard as well as any corporate policy concerning this standard. Documented rationale and agreement with the customer are necessary for deviations in order to justify new work or changed methods during customer or third-party audit reviews.
Automotive Quality and Process Improvement Committee
Modeling Unsteady Aerodynamics and Predicting Trajectories for Small UAV in Complex Airwake EnvironmentsF-0082-2026-02625/5/2026
A new modeling and simulation approach for uncrewed aerial vehicles (UAVs) for shipboard operations, as well as other complex airwake environments, is introduced. The approach couples an aerodynamic modeling framework, expanded with a closed-loop flight controller, with a flight dynamics solver to assess UAV responses in highly complex airwakes. Using high-fidelity wall-modeled large eddy simulation airwakes, the approach has been evaluated for two traditional naval approaches on a generic destroyer. As part of this effort, a new metric to ensure accurate flight modeling is introduced, along with proposed UAV safety mapping. These predictions can support mission planning by evaluating unique prescribed approaches for nontraditional small UAV, and can aid in early controller design by highlighting specific failure modes based on the airwake environment.
Oates, Brenden, Smith, Marilyn, Sundar, Adithya
A Novel Spot Joint Finite Element for Rapid Stress Analysis of Fasteners in Automotive Structures2026-01-01824/7/2026
Due to the spot weld and mechanical fastener share the similar characteristics to join sheets together with differences in deformation behavior around joint region, a novel spot joint element (user-defined element) consists of regular Mindlin shell elements and equations for different kinematic constraints is proposed to simplify the spot joint representation in lightweight automotive structures. The novel spot joint element can not only provide accurate deformation behavior around joint region but also output mesh-insensitive structural stresses at virtual nodes with the use of traction-based structural stress method for fatigue failure analysis. In this investigation, the structural stress distributions around joint circumference in the lap-shear specimens with spot weld or fastener are first calculated to validate the accuracy of the novel spot joint element. Then, the structural stresses along different cross-sections emanating from joint are also calculated for the specimens with fasteners to investigate the potential different failure modes. Finally, the fatigue data correlation based on the novel spot joint element and traction-based structural stress method using available literature data are presented and served as example applications.
Wu, Shengjia, Zhang, Lunyu, Dong, Pingsha
Compact, Low-Cost Ultra-Low NOx Solution for 2027 US EPA, Euro VII, China VII and Off-Road2026-01-03634/7/2026
Achieving ultra-low NOx emissions remains a major challenge in diesel emission control industry worldwide, especially as increasingly stringent regulations are introduced globally. Selective Catalytic Reduction (SCR), the leading NOx reduction technology in diesel systems, performs best when “sufficient” heat and ammonia are made available to it. At the same time, any proposed solution must be both low-cost and functionally robust in an industry seeking near 100% NOx removal at the lowest feasible cost. This work presents a low-cost architecture, utilizing a small, highly compact, single heater-mixer unit along with a light-off (close-coupled) SCR for meeting most stringent NOx emission regulations worldwide. It also hinders deposit formation lowering warranty costs and mitigating failure modes. Engine studies using a fully-aged aftertreatment system demonstrate that the proposed solution enables compliance with newer heavy-duty regulations including 2027 US, Euro-VII, China-VII, and likely the upcoming Bharat-VII while also rendering a large ‘compliance margin’, providing significant margin for meeting in-use compliance.
Masoudi, Mansour, Poliakov, Nick
Development and Validation of a Self-Propelled Trailer: A Standards-Based Approach to Enhancing Compact Vehicle Towing2026-01-00554/7/2026
This paper presents a structured test plan for the development and validation of a Self-Propelled Trailer (SPT), an emerging concept designed to enhance the towing capacity of compact, fuel-efficient vehicles. Unlike conventional trailers, the proposed system integrates electric propulsion and autonomous sensing to actively assist the towing vehicle, reducing engine load and improving both safety and fuel economy. The methodology employs a Design Failure Mode and Effects Analysis (DFMEA) to systematically identify potential risks, while incorporating Society of Automotive Engineers (SAE) standards to guide environmental durability testing (dust, water ingress, gravel impact) and dynamic performance evaluations (gradeability, braking, and stability). A comprehensive set of test procedures is outlined to validate system reliability, robustness, and compliance with established towing requirements. The study demonstrates how powered trailer technology can extend the practical use of compact vehicles for heavier load applications without compromising efficiency or emissions targets. This work contributes to the advancement of autonomous trailer systems and provides a foundation for future prototype development, testing, and eventual deployment.
Reilly, Carter, Peters, Diane, Zadeh, Mehrdad
The ML FMEA in Action: Lessons from Applications of Machine Learning Safety2026-01-00794/7/2026
Introducing machine learning (ML) into safety-critical systems presents a fundamental challenge, as traditional safety analysis techniques often struggle to capture the dynamic, data-driven, and non-deterministic behavior of learning-enabled components. To address this gap, the Machine Learning Failure Mode and Effects Analysis (ML FMEA) methodology was developed as an open-source framework tailored to ML-specific risks. This paper reports on the maturation of ML FMEA from an initial conceptual framework to a proven, practice-driven methodology. We make four primary contributions. First, we extend the ML FMEA pipeline with two new stages: a “Step Zero” for problem definition and system-level hazard analysis, and a “Step 5” for constructing ground truth or reward signals. Autonomous vehicle and humanoid robot applications are presented to illustrate the practical application and safety benefits of these additions. Second, we introduce tailored Severity, Occurrence, and Detection criteria for ML risk assessment, resolving ambiguities encountered when applying traditional FMEA metrics to ML development processes. Third, we demonstrate systematic alignment between ML FMEA artifacts and requirements from ISO/PAS 8800, ISO 21448 (SOTIF), ISO/TS 5083, ISO/IEC TR 5469, and UL 4600, providing a bridge between ML development practices and safety certification expectations. Fourth, we present cross-industry perspectives spanning automotive, aerospace, industrial robotics, and defense, highlighting deployment pathways and best practices for domain-specific adaptation. Through open-source collaboration and cross-industry validation, the ML FMEA has matured into a practical toolset that enables safety-informed ML workflows, supporting auditable, repeatable, and risk-aware development of learning-enabled systems.
Schmitt, Paul, Shinde, Chaitanya, Diemert, Simon, Pennar, Krzysztof, Seifert, Bodo, Poh, Justin, Lopez, Jerry, Mannan, Fahim, Mohammed, Majed, Chalana, Akshay, Wadhvana, Neil, Wagner, Michael
Advancing Safe Battery Design through Experimental Cell Characterization of Thermal, Electrical and Mechanical Properties2026-01-04084/7/2026
Lithium-ion batteries are critical to Electric Vehicles (EV) and grid-scale energy storage. Safe design of battery systems relies on accurate simulation of thermal runaway under electrical, thermal, and mechanical abuse. A predictive battery simulation requires characterization of electrical, thermal, and mechanical properties at the full cell and cell-component levels. In this study, a commercial cell from an EV was disassembled, and tested to support both homogenized and detailed computational models. At the cell level, electrical properties were characterized using Hybrid Pulse Power Characterization (HPPC) testing to assess the cell’s power capability. Full cell compression tests were conducted to characterize mechanical behavior under deformation and used to develop a multi-physics homogenized cell model. On the other hand, detailed cell modeling that includes different component layers could help users understand localized cell integrity under mechanical deformation. At the component level, cathode and anode electrodes, separator, and cell pouch laminate were tested for their thermal properties, including heat capacity, thermal conductivity, and melting points. This data is essential to modeling heat generation and dissipation in the detailed battery cell model. Mechanical behavior of these component materials was tested to understand structural integrity and failure modes. Electrical conductivity of cell component materials was also characterized. These experimentally measured properties and derived parameters may be integrated into a representative multi-physics battery cell model. By providing detailed characterization of a commercial lithium-ion EV cell, this research provides an experimental framework for developing both macro and detailed cell computational models needed for safety design assessments of EV battery systems.
Challa, Vidyu, Rostami-Angas, Masoud, kong, Kevin, Wang, Leyu, Reichert, Rudolf, Kan, Cing-Dao
Enhanced CAE Methodology to Predict Bolt Shear Failure Using Multi-Layer Approach2026-01-04894/7/2026
Automotive seat system is one of the most complex systems in vehicle for its technical and functional requirements. Seat is designed to meet all regulatory requirements subjecting it to multiple tests with loading patterns which caters to the occupant safety. Varied loading and load path for different test requirements cause seat bolts to experience tensile, compressive, bending moments and shear loading. Shearing along bolt length is one of the common failure modes observed during design validation by physical tests. In the world of CAE, there is an industry approach to find the bolt failures at nut and head for all kind of loads. But shear failures along varied bolt lengths are not accurately predictable as multiple sheet metal parts will transfer loads unevenly onto bolt length and it becomes challenge to find which component is leading to shear failure. Hence by adding multiple rupture layers across the bolt length shear and its location could be predicted. Further, to resolve the bolt shear issues, engineers generally try to modify the component design for better energy absorption, but our research found that, only by increasing the clearance around bolt hole will resolve the bolt shear issues. During one of such failures, a new approach of adding multiple rupture layers along bolt length was used which predicted the shear failure modes and location of shear as observed in physical tests. The CAE bolt model thus updated with new procedure for all such future bolt shear failure prediction in seat structure models.
RJ, Jethendra, Chiu, Li-Ban
AI Powered Failure Mode and Effect Analysis in Safety Critical Industry2026-01-01064/7/2026
This paper presents the first systematic examination of Large Language Model (LLM) capabilities for automating the development of Failure Mode and Effects Analysis (FMEA) utilizing architectural diagrams as input. Although prior research has examined LLMs for FMEA tasks, our methodology incorporates innovative aspects, such as the direct analysis of architectural diagrams for component extraction, prediction of failure modes, causes, estimation of risk and a human-in-the-loop (Hu-IL) validation framework. We examine the capability of general-purpose LLMs to accurately automate the creation of FMEA by formulating a methodology that extracts components and signals from architectural diagrams, conducts automated component classification, and produces a comprehensive FMEA form sheet encompassing Severity, Occurrence, and Detectability (S/O/D) scoring. Our methodology is grounded in structured prompt engineering theory, utilizing scope bounding techniques to reduce hallucination while preserving extraction accuracy. Assessment against expert-validated ground truth (over 12 years of functional safety experience) across several automotive system diagrams indicates a 92% accuracy rate for signal extraction and component categorization, with S/O/D scoring obtaining an accuracy range of 70–90%. The results demonstrate substantial potential to reduce manual FMEA development processes (as compared to prior studies). Key limitations include sensitivity to diagram complexity and quality, as inadequately designed diagrams markedly affect output precision along with the inability of LLMs to create new detection measures reliably. Our Hu-IL validation process mitigates these limitations while preserving the advantages of automation. This study provides baseline performance indicators for LLM-based FMEA automation and demonstrates significant potential in transforming traditional FMEA workflows in safety-critical industries.
Diwakaruni, Sundara Sasi Koushik, Krishnamurthy, Anunay
From Algorithm to Engineering Judgment: Navigating Topology Optimization’s Limits in Crash Applications2026-01-01894/7/2026
The non-linear nature of crash scenarios has led to many designs being developed through extensive trial and error based on the intuitions of the design engineer. As such, effectively utilizing topology optimization for crash applications offers opportunities to provide major improvements in cost, weight, and passenger safety. Topology optimization is known for creating stiff, lightweight structures, however its application to crash scenarios must be handled carefully. Compliance minimization, the most common optimization objective, can yield misleading designs that prioritize undesirable qualities when developing structures for crash applications. In this paper, the design process of a passenger seat assembly subject to sequentially applied enforced displacement, and crash deceleration loads is discussed. Due to the conflicting nature of compliance minimization and enforced displacement, the design was split into two types of regions; sacrificial, which are regions manually designed to absorb the majority of the enforced displacement and crash energy, and structural, regions designed with optimization tools to maximize stiffness and reduce mass. The recognition of these regions allowed for components that failed during the crash phase to be remedied via the removal, rather than addition, of material in key sacrificial locations through alleviating stresses experienced during the enforced displacement phase. Identifying and using these design guidelines was shown to greatly improve seat performance metrics, and yielded reduced design times as failure mechanisms were clearly defined and designed, mitigating the issue of cascading failures across an assembly as individual failure modes are addressed.
Orr, Mathew, Shi, Yifan, Lee, Jake, Gray, Savannah, Park, Taeil, Wotten, Erik, LeFrancois, Richard, Huang, Yuhao, Patel, Anuj, Kim, Hansu, Burns, Nicholas, Jalayer, Shayan, Grant, Robert, Kok, Leo, Hansen, Eric, Kim, Il Yong
Real-Time Fault Diagnosis and Reliability Analysis in Lithium-Ion BESS via Bayesian Fault Propagation Networks2026-01-70232/27/2026
The rapid integration of intermittent renewable energy sources (RES) poses significant operational challenges for modern power systems. Lithium-ion battery (LIB)–based battery energy storage systems (BESS) have become vital for grid stability and energy management. However, large-scale deployment of BESS has led to increasing incidents such as fires and explosions, raising serious concerns regarding their safety and reliability. To overcome the limitations of traditional reliability assessment methods—such as reliability block diagrams (RBD), fault tree analysis (FTA), and Markov models—this study proposes an integrated fault detection and reliability analysis framework that combines FTA, failure mode and effects analysis (FMEA), and a Bayesian Fault Propagation Network (BFPN). The framework systematically models fault propagation across component, subsystem, and system levels, dynamically updating the prior probabilities of basic failure events using a Gaussian Mixture Model (GMM) and Expectation–Maximization (EM) algorithm. Conditional Probability Tables (CPTs) are recalculated through Maximum Likelihood Estimation (MLE) with logical relationships to achieve accurate and adaptive fault probability estimation. A multi-feature fusion indicator, the State Severity Indicator (SSI), is further introduced to evaluate system health in real time. A qualitative comparison with representative fault modeling and detection approaches—including Bayesian Network, FTA-DBN, and various machine learning methods—shows that the proposed BFPN offers a well-balanced trade-off between interpretability and real-time performance. Simulation experiments under both single- and multiple-fault scenarios demonstrate that the proposed framework accurately detects typical fault events and provides early warnings before fault escalation. Under complex coupled fault conditions, it effectively captures fault interactions and predicts cascading failures across subsystems and the overall BESS, showing strong robustness and diagnostic capability for real-time reliability assessment in modern energy storage systems.
Yang, Zhan, Chen, Xiaobo, Zheng, Ruixiang, Li, Mian
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 include: • Holistic reliability across design, manufacturing, supply chain, and marketing. • Advanced experimental designs, including split-plot and fractional factorial methods. • Fault tree analysis (FTA) and FMEA for failure prediction and prevention. • Supply chain optimization through multivariate process control. • Production and field reliability using design for testability and diagnostics. • Electric vehicle system and battery reliability analysis. • Marketing reliability driven by voice of customer and data-based value analysis. This book is an essential resource for engineers, operations leaders, and technical managers who want to build resilient systems, unlock innovation, and achieve long-term competitive advantage through disciplined, data-driven reliability.
Chiang, Young J.
Modelling and Analysis of Complex Shaped Cracks2026-28-00482/12/2026
This study provides an extensive analysis through finite element analysis (FEA) on the effects of fatigue crack growth in three different materials: Structural steel, Titanium alloy (Ti Grade 2), and printed circuit board (PCB) laminates based on epoxy/aramid. A simulation of the materials was created using ANSYS Workbench with static and cyclic loading to examine how the materials were expected to fail. The method was based on LEFM and made use of the Maximum Circumferential Stress Criterion to predict where cracks would happen and how they would progress. Normalizing SIFs while a crack was under mixed loading conditions was achieved using the EDI method [84]. We used Paris Law to model fatigue crack growth using constants (C and m) for the materials from previous studies and/or tests. For example, in the case of titanium Grade 2, we found Paris Law constants with C values from 1.8 × 10-10 to 7.9 × 10-12 m/cycle and m values from 2.4 to 4.3, which illustrate differing effects of their manufacture processes and microstructure. Detailed Paris Law constants are limited for the epoxy/aramid laminates, but other similar composite materials, for example, VARTM composites, have shown that under certain conditions the Paris Law could be applicable. In determining the performance of the materials, we assessed various mechanical responses (total deformation, directional stiffness) and all were also noted with respect to the likely progression of these fatigue cracks given the long-term nature of the study.
T, Lokesh, Bhaskara Rao, Lokavarapu
A Study on the Thermal Degradation of Chlorinated Polyethylene Rubber2026-26-02761/16/2026
Elastomeric materials are essential in advanced automotive engineering for mobility, isolation, damping, fluid transfer (cooling, steering, fuel, and brake), and sealing because of their unique physio mechanical properties. Elastomers are commonly used in both static and dynamic components, such as hoses, mounts, bushes, and tires. Engine emission standards and weight optimization have caused higher temperature exposure conditions for automotive components. The steering system uses special purpose elastomers like Chlorinated Polyethylene that can deteriorate under abnormal conditions during vehicle operation or manufacturing process due to the high temperature exposure. Therefore, it is crucial to understand the causes and consequences of thermal degradation of elastomers. Thermal degradation is a significant phenomenon that changes the physiochemical properties of elastomers, which results in a product not meeting functional requirements. This study investigates the thermal degradation behavior of chlorinated polyethylene (CPE) polymer subjected to accelerated thermal ageing conditions. Comprehensive material analyses were conducted, including FTIR, TGA, DSC and Microscopical study to evaluate chemical, thermal, and morphological changes. Ageing replication experiments were designed to simulate field-induced thermal hardening and surface cracking, aiming to establish correlation between service or process induced failures and lab-based degradation mechanisms. The results show that prolonged thermal exposure leads to dehydrochlorination, crosslinking, and embrittlement, resulting in hardening, crack initiation and propagation. This experimental study provides comprehensive understanding of ageing kinetics and failure modes of CPE materials under thermal stress, supporting more robust material selection and life prediction in high-temperature applications.
Thiruppathi, Anandhi, Mishra, Nitish, Krishnamoorthy, Kunju
Ensuring Functional Safety in Electric Vehicle Inverters: A Case Study on ISO 26262 Implementation2026-26-01581/16/2026
The transition to electric vehicles (EVs) has brought about significant advancements in automotive technology, with inverters playing a crucial role in converting DC power from the battery to AC power for the electric motor. Ensuring the functional safety of these inverters is paramount, as any failure can have severe implications for vehicle performance and passenger safety. This case study explores the successful implementation of ISO 26262 standards in the development and validation of EV traction inverters. This paper begins by outlining the functional requirements and safety goals specific to EV inverters, followed by a detailed analysis of the potential hazards and risks associated with their operation. Using ISO 26262 as a framework, we describe the systematic approach taken to identify, assess, and mitigate these risks. Key methodologies such as Hazard Analysis and Risk Assessment (HARA), Failure Mode and Effects Analysis (FMEA), and Fault Tree Analysis (FTA) are employed to ensure comprehensive safety coverage. This case study showcases the integration of key safety mechanisms—such as redundancy, fault tolerance, and real-time monitoring—to significantly enhance the reliability and robustness of the inverter system. It also explores the challenges encountered during implementation, including the complexity of managing safety critical high-voltage systems and the need to stay aligned with evolving safety standards.
Ramachandra, Shwetha, V, Sushmitha
Numerical Investigation of Cowl Water Drainage in Automotive Design2026-26-03931/16/2026
Rainwater accumulation in the cowl region, located at the base of the windshield, can lead to serious HVAC performance degradation, corrosion, and passenger discomfort if not effectively drained. Traditional physical validation methods are often time-consuming, costly, and limited in diagnostic insight. This study presents a simulation-driven methodology for evaluating and optimizing HVAC cowl box drainage performance during the early design phase. Using STAR-CCM+, a multiphase Volume of Fluid (VOF) approach was implemented to visualize water flow behavior under static and dynamic conditions. Design variants were assessed by modifying drain tube geometry (shape, size, and placement) and cowl surface features, such as baffle positioning. Results showed that inadequate drainages were primarily due to stagnation zones, shallow slopes, and drain locations prone to clogging. Water film accumulation near the HVAC inlet was accurately predicted, highlighting potential ingress paths under high water load scenarios. The optimized configuration demonstrated improved drainage performance and reduced risk of water ingress. This methodology enables proactive identification of failure zones, supports robust design iteration, and reduces dependency on late-stage physical testing. Overall, the proposed simulation framework contributes to improved vehicle water management and long-term HVAC system reliability.
Mathew, Ronnie, Ibrahim, Sayyaf, Nikumbh, Nayan
Coupled Thermo-Mechanical Simulation Framework for Structural Evaluation of Battery Pack2026-26-04141/16/2026
With the rapid adoption of electric vehicles (EVs), ensuring the structural integrity and thermal safety of lithium-ion battery has become a critical priority. Battery failures resulting from mechanical abuse, thermal stress, internal pressure build up or electrical faults may lead to structural failure. To address these challenges, it is essential to understand the coupled thermal and mechanical responses of battery structure under extreme conditions. Thermo-mechanical simulation serves as a powerful tool for predictive safety assessment and design optimization, particularly in addressing thermal propagation and pressure-induced failure events. This study presents a comprehensive coupled thermo-mechanical simulation framework designed to evaluate the structural performance of EV battery enclosures under worst-case thermal and overpressure conditions. The methodology involves high-fidelity three-dimensional modeling of the battery pack enclosure, incorporating realistic material properties, pressure profiles, and temperature data derived from computational fluid dynamics (CFD) analyses. Boundary conditions are carefully applied, and post-processing techniques are used to extract meaningful insights into stress distribution, deformation, sealing behavior, and structural failure modes. The simulation results also identify critical stress concentrations, sealing opening/closing, plastic strain, and potential rupture, offering a detailed understanding of how battery enclosures respond to thermal and mechanical loading. By performing analytical calculations to validate the initial design, the need for a simulation framework became evident to ensure predictive accuracy and support iterative refinement of design parameters. This approach enables early identification of design vulnerabilities, reduces dependence on extensive physical testing, and helps accelerate the overall development cycle. In conclusion, the integration of coupled thermal and mechanical simulation not only enhances design robustness and safety but also supports regulatory compliance and cost-effective development. This study highlights the vital role of virtual validation in the advancement of battery technologies, enabling the creation of safer, more efficient, and more sustainable energy storage systems for next-generation electric mobility and beyond.
Bhat, Sadashiv C, Sugumar, Mohanraj
Next Gen Automotive EDS Architecture Design Verification using Real-Time Function Mode Simulation & Failure Condition Analysis2026-26-04541/16/2026
In the current automotive design and development of the Electrical Distribution System (EDS), at an earlier stage, before the physical prototyping is largely absent. Traditional methods for verification and validation of EDS are performed with HIL, SIL, MIL, prototype testing or physical vehicle trials reveal design errors at later stages in the development cycle, which may lead to redesign, prolonged timelines and increased failure rates at vehicle integration. Hence, there is a critical need for an early-stage simulation methodology that ensures robustness and reliability of E/E architecture with first-time-right readiness at the design stage itself. In this paper, a digital EDS architecture simulation introduces a mode-based structural behavioural approach where specific vehicle functions, failure conditions and malfunction scenarios are set up in a simulation environment with their corresponding electrical circuits for simulation. A function-specific truth table-based analysis model enabling the controller to control the electrical paths for different electrical loads dynamically. This methodology ensures digital verification of electrical loads behaviour at different operating conditions, power distribution and switching logics are accurately validated during the design stage, reducing production time issues and ensuring seamless transition to series production.
Jaisankar, Gokulnath, Warke, Umakant, Chakra, Pipun, Borole, Akash
Challenges in Compliance Testing of Off-Board Electric Vehicle Chargers: Analysis of Typical Failures and Remedial Measures2026-26-05821/16/2026
As India accelerates the adoption of electric vehicles (EVs) the development of a scalable, reliable and efficient charging infrastructure becomes critical to ensuring the success of EV adoption. During type testing, the off board AC/DC EV chargers undergo a comprehensive assessment to ensure they meet safety and performance standards required by regulations. The tests examine crucial factors like electrical safety, EMC (electromagnetic compatibility), interoperability, environmental endurance and mechanical strength. This paper provides information of the India mandatory compliance requirements and highlights typical failure modes observed during the validation process of off-board chargers. Emphasis is placed on challenges associated with electrical safety, EMC performance and interoperability. The objective is to support charger manufacturers to identify potential issues during design and development.
Murumkar, Aditya, Mulay, Abhijit B
Hydrogen Embrittlement in Galvanized High Carbon Steel Components of Automotive Seat Slider Assembly2026-26-03021/16/2026
This research paper investigates the failure of an isolator clip used in the seat slider assembly, which guides and restricts the sliding motion of the tooth bracket within the seat. The component is made of C80 high-carbon spring steel, known for its high strength. According to the manufacturing process details, zinc plating was applied to the component for corrosion protection, as confirmed by EDS analysis. A fractographic examination of the failed part revealed a brittle, intergranular fracture morphology with visible cracks. Certain areas also exhibited micro-void coalescence, indicating a dimpled fracture surface. The primary failure mode was intergranular (IG) fracture. The delayed fracture was attributed to intergranular fracture mechanisms, micro-void coalescence, and the high strength of the steel, which made the component susceptible to hydrogen embrittlement. Hydrogen embrittlement occurs when hydrogen atoms become trapped along the grain boundaries, where they form hydrogen molecules, leading to crack initiation. Hydrogen embrittlement also impacts on mechanical properties by reducing ductility and increasing brittleness. This suggests that hydrogen absorption likely took place either during the pickling process before galvanization or during the galvanizing process itself. During zinc plating, the electrochemical reaction (H₂ → 2H+ + 2e-) generates cathodic hydrogen on the surface, ultimately causing hydrogen embrittlement and leading to the sudden and unexpected isolator clip failure under stress. To prevent such failures, a post-fabrication heat treatment (baking) at 200-300°C for a few hours was recommended to remove absorbed hydrogen from the material. Following the implementation of this measure, no further failures of the isolator clip have been reported.
Saindane, Mehul Kishor, Bali, Shirish
Multiphysics Simulation Approach for Evaluating Thermo-Structural Performance of Electric Motors Using Spatial Electromagnetic Loss Mapping2026-26-03871/16/2026
High power and torque density electric motor is finding increasing demands in modern-day electric and hybrid vehicles because of compact and light-weight designs. These high-performance requirements are achieved by increasing the current flow, strengthening the magnetic field as well as downsizing the motor dimensions and hence can lead to multiple failure modes if not designed properly. Higher current flow results in increased magnitude of losses within the motor components such as ohmic loss, iron loss, hysteresis loss and mechanical losses. All these localized losses contribute to higher operating temperature and temperature gradient that can act as a catalyst to several modes of failure. Hence, accurate prediction of temperature distribution across the motor components is very crucial to come up with a robust and durable motor design. A common approach of predicting component temperature is by assuming bulk losses for lamination stack, hairpin and magnets. This approach might be beneficial for comparison between different design suggestions but from lifetime durability point of view, appropriate spatial distribution of losses and its transient history must be analyzed. This study focuses on a coupled electromagnetic and thermo-structural simulation approach to predict the overall temperature distribution in motor components by considering spatially distributed losses. The electro-magnetic (eMag) analysis highlights the impact of magnetic saturation and the non-linear behavior of core materials on loss distribution while the thermo-structural analysis highlights the impact of orthotropic thermal and structural behavior of the core materials during motor operation. A special mapping technique using K-Nearest neighbor algorithm is also highlighted in this paper to seamlessly propagate the loss distribution from electromagnetic solver to the thermo-structural solver leveraging dissimilar finite element (FE) mesh. The difference in temperature distribution from this approach is also compared with that using traditional bulk-loss approach. The predicted temperature distribution is also utilized to understand the motor durability against different failure modes and hence this overall multi-physics analysis approach can be used as a decision-making tool in the initial design phases of high-end electric motors.
Munshi, Irshad Ahmed, Elango, Gokul, Karmakar, Nilankan, Prasad, Praveen
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 manufactured in future at initial stage of the vehicle design) and demonstrated the same though live case performed on Tata Motors bus project. It is further suggested to include the DVA approach in the system level DFMEA for the detection against failure modes related to bus body PQ assessment.
Singh, Vinay Kumar, Dewangan, Ved Prakash, Kumar, Rahul, Deep, Amar
Powering the Future: Addressing Power Architecture Bottlenecks in Next Gen Automotive Platforms2026-26-06881/16/2026
As the automotive industry moves from conventional function oriented embedded ECU-based systems to Code-driven system, the core electrical and electronic (E&E) architecture is also being redesigned to support more software-driven functionality. Modern and centralized architectures promise scalability and software-driven flexibility, but they also introduce significant challenges in power distribution—an area that remains underexplored despite its critical role in overall vehicle safety and performance. Our paper aims at the adoption of the traditional power distribution approach for Next Gen vehicle architecture. It requires a fresh look at how power is distributed. In a novel E&E architecture, a single power harness supplies battery voltage to each zone. If there's a failure or voltage drop, it can affect multiple functions within that zone at once, and management of voltage regulation, thermal dissipation, and EMI/EMC compliance becomes crucial. Adding to the complexity, safety-critical systems need power redundancy and isolation to meet Functional Safety standards. Mixed-criticality designs further complicate power management, as they demand strict segregation between critical and non-critical power loads to preserve functionality under fault conditions. The integration of software-controlled power switching and dynamic power management introduces additional failure modes previously unrecognized. Consequently, real-time monitoring and power fault detection are becoming vital for maintaining the health of a vehicle’s power distribution network. Traditional diagnostics, such as On-Board Diagnostics, offer limited checks and periodic alerts, primarily for engine and transmission faults. Advanced capabilities are essential. Through an investigative lens, this paper identifies the key bottlenecks in power distribution and proposes areas for further research and innovation aimed at ensuring resilience, safety, and performance in next-generation vehicles.
Borole, Akash, Warke, Umakant, Chakra, Pipun, Jaisankar, Gokulnath
Bearing Creep Prevention in EV Transmission2026-26-05981/16/2026
As the trend shifts from Internal Combustion Engine (ICE) vehicles to Electric Vehicles (EVs), the operating speeds of prime movers have significantly increased. Commercial EV manufacturers prefer high-speed, low-torque motors coupled with transmissions over low-speed, high-torque motors due to higher efficiency and power density. This combination of high-speed, low-torque motors coupled with transmission is essential for achieving the required gradeability and enhances operational efficiency. However, the increased operating speeds of these EV transmissions have inherently increased the risk of ‘bearing creep’ [8]. The “bearing creep” is the phenomenon where unintended relative motion occurs between bearing races and their mounting surfaces, leading to premature wear of mounting surfaces [3]. This issue can lead to a series of failure modes such as increased gear mesh misalignment, bearing damage, seal damage, etc. These problems result into elevated transmission vibrations eventually leading to premature transmission system failure. Notably, bearing creep tends to be more severe in aluminum enclosures compared to those made of cast iron or steel, owing to greater difference in the coefficient of thermal expansion of aluminum and bearing steel. This paper presents a comprehensive methodology to mitigate the bearing creep. This paper comprises of concept trade-off, design of experiments (DOE), parameter optimization, and design validation. Initially, the paper explores various potential solutions through concept trade-offs to identify the most effective solution to mitigate the bearing creep. A systematic DOE is then conducted to comprehend influence of different parameters on bearing creep resistance. A transfer function is generated to model the relationship between key design parameters and bearing creep resistance. Subsequently, parameter optimization techniques are applied to fine-tune the design, ensuring maximum resistance to creep. Finally, the optimized design is validated through testing for its performance. This study aims to demonstrate O-ring utilization as an effective anti-rotation feature for high-speed bearings in EV transmissions.
Bagad, Sachin Sunil, Kanase, Ashish, Hiremath, Satalingayya, Nevarekar, Sandip
Comparative Study of ADC12, A356, and AlSi10Mg Alloys in Sand Casting of EV Battery Housing2026-26-02961/16/2026
This research investigates the applicability of ADC12 aluminum alloy in sand casting processes and compares its casting behavior and performance with that of conventionally sand-cast alloys such as A356 and AlSi10Mg. ADC12 is primarily utilized in high-pressure die casting (HPDC) and low-pressure die casting (LPDC) due to its excellent castability, pressure tightness, and favorable mechanical properties in thin-walled components. However, its use in sand casting is minimal globally, primarily due to the alloy’s high silicon and iron content, which can lead to poor feeding characteristics, increased porosity, and structural non-uniformity in non-pressurized molds. In this study, 3 mm thick test castings were produced using conventional sand casting methods, with particular attention to mold and core design to simulate challenging flow and solidification conditions. Comparative castings of A356 and AlSi10Mg were also produced under identical conditions to establish performance baselines. The objective was to evaluate the filling behavior, solidification characteristics, and final casting quality of ADC12 in sand molds, and to determine its potential for use in applications where die casting is not viable. A comprehensive evaluation was conducted covering key casting parameters: Fluidity and mold filling behavior (evaluated through flow pattern simulations and casting trials) Casting defects and internal integrity (analyzed using real-time X-ray radiography and defect quantification techniques). Density Index (DI) to assess gas entrapment and hydrogen porosity. Mechanical properties, including tensile strength, yield strength, elongation, and hardness (tested according to ASTM standards). Microstructural characterization via optical microscopy and SEM/EDS to examine grain structure, silicon morphology, and intermetallic phases. Fractography of failed tensile specimens to understand failure modes and defect influence. Preliminary results indicate that although ADC12 exhibits higher susceptibility to porosity and reduced ductility in sand cast form compared to A356 and AlSi10Mg, it is still capable of producing structurally acceptable components with optimized gating and venting designs. The study contributes new insights into the adaptability of ADC12 for sand casting, expands the material selection range for low-volume or prototype production scenarios, and provides a technical basis for further optimization of casting parameters to enhance the performance of ADC12 in sand mold applications.
Subramani, Rajesh, Singh, Gajendra, Doddamani, Mrityunjay
Reliability of Rubber Grommets by Stochastic Analysis of Geometric Tolerances2026-26-05011/16/2026
Manufacturing tolerances play a critical role in the quality and functionality of components, particularly those made from rubber. Even slight deviations in dimensions can cause significant issues such as improper fit and reduced performance, leading to increased costs and project delays. This is especially true for rubber grommets, which are nonlinear elastic components commonly used as sealants, gaskets, and insulation covers in automotive and industrial applications. Typically manufactured from EPDM rubber with varying Shore hardness, grommets must maintain precise geometry to ensure sealing integrity and protect adjacent parts. Dimensional inaccuracies can result in failures such as buckling or misalignment, compromising both functionality and durability. This study proposes a digital simulation methodology for early-stage evaluation of grommet robustness, reducing reliance on physical prototypes. Using a stochastic design of experiments (DOE) approach, the influence of critical geometric parameters on grommet performance is assessed under variable manufacturing conditions. Buckling, identified as the primary failure mode, along with other functional metrics, is analyzed across a spectrum of dimensional tolerances. These insights support more efficient design workflows and enhance the robustness of rubber grommets in real-world applications.
Beesetti, Siva, Hattarke, Mallikarjun, James Aricatt, John, Pathan, Eram
Test Method and Set Up Development for Electric Parking Brake Performance and Durability Validation in Vehicle Level as Per RWUP2026-26-05051/16/2026
The Objective is to develop a testing load case which can assess vehicle electric parking brake (EPB) performance and durability at vehicle level in different project development phases. In current scenario the EPB become one of a primary feature available in many passenger vehicles helps customers to apply this secondary braking system to hold the vehicle when parked. So, it is particularly important to evaluate this feature close to RWUP for the vehicle service life and studying the result before vehicle launch. The test method should be capable of capturing failures related to physical concerns, electrical characteristics, actuation time, gradient vehicle hold, effectiveness during vehicle running and durability. The most important challenge in this test method development is it should simulate the actual sequence followed by user in field on vehicle. A completely automated test set up integrating PLC and COBOT with closed loop feedback developed and discussed in this paper. During the test, measurement of electric parking brake operating voltage and current, brake motor & caliper mounting fasteners torque, switch operating efforts, brake motor mounting deflection and electrical harness temperature are recorded which are the key parameters affects the system. Any deviation in these parameters will have a significant impact on the braking in the vehicle. During the test execution, instrumentation and data logging were used to measure the operational parameters of electric parking brake system in performance and durability. The electric parking brake operational method derived from RWUP (Real world usage pattern), and this pattern used to set the operational sequence and derive the durability cycles. The paper discusses results and measured parameters. By this test method, premature failure modes shall get capture in the initial phase of development itself thereby improving product competency in the market.
Dhanapal, M R, Vijayakumar, Narayanan, Mahesh, B, B, Venkatasubramanian, Arthanathan, Sankaranarayanan
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 understand these parameters in real life vehicle driving conditions. This revealed the root causes of the cracks and established a dependable match between simulation and actual testing. The redesigned manifold included many key changes: increased wall thickness to enhance structural strength, a reshaped geometry to optimize flow and reduce stress points, and the addition of webbing in the port area to improve heat distribution and provide extra support. Furthermore, testing protocols were refined to replicate real-world driving conditions, including more precise temperature cycling. These refined protocols enabled the identification of design flaws and facilitated the validation of improvements. The final design successfully passed tough accelerated thermal fatigue bench testing, showing significantly improved durability. This research highlights the importance of accurate simulation modelling, targeted design improvements, and refined testing to replicate real world driving conditions in overcoming thermal challenges within tight engine spaces, leading to strong and durable exhaust systems.
Krishnan, K.S.Gopala, Mishra, Ashutosh, Yadav, Sanjay Kumar, Kumar, Deepak, Tripathi, Manas, Kumar, Prabhakar
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