Browse Topic: Reliability

Items (3,426)
In a three-phase voltage source inverter, in order to prevent the direct short circuit of the upper and lower tubes of the bridge arm and ensure the normal operation of the inverter, microsecond-level dead time needs to be added when the power devices are turned on and off. However, due to the dead-time effect, slight distortion may occur in the inverter within the modulation period, and this distortion will eventually lead to harmonic components in the output current after accumulation, thereby generating torque ripple. Against the above background, implementing dead-time compensation strategies is very important. To compensate for the voltage error caused by the dead-time effect, current polarity determination is required first. Then, the dead time is compensated, thereby indirectly compensating for the voltage error caused by the dead-time effect. Regarding the dead-time compensation time, without changing the hardware, this paper proposes a solution to turn off the dead-time
Jing, JunchaoZhang, JunzhiZuo, BotaoLiu, YiqiangYang, TianyuZhu, Lulong
This paper reviews the current situation in the terms and definitions that influence the development of testing and prediction in automotive, aerospace and other areas of engineering. The accuracy of these terms and definitions is very important for correct simulation, testing and prediction. This paper aims to define accurate terms and definitions. It also includes the author’s recommendations for improving this situation and preparing new standards.
Klyatis, Lev
Video analysis plays a major role in many forensic fields. Many articles, publications, and presentations have covered the importance and difficulty in properly establishing frame timing. In many cases, the analyst is given video files that do not contain native metadata. In other cases, the files contain video recordings of the surveillance playback monitor which eliminates all original metadata from the video recording. These “video of video” recordings prevent an analyst from determining frame timing using metadata from the original file. However, within many of these video files, timestamp information is visually imprinted onto each frame. Analyses that rely on timing of events captured in video may benefit from these imprinted timestamps, but for forensic purposes, it is important to establish the accuracy and reliability of these timestamps. The purpose of this research is to examine the accuracy of these timestamps and to establish if they can be used to determine the timing
Molnar, BenjaminTerpstra, TobyVoitel, Tilo
The trends of intelligence and connectivity are continuously driving innovation in automotive technology. With the deployment of more safety-critical applications, the demand for communication reliability in in-vehicle networks (IVNs) has increased significantly. As a result, Time-Sensitive Networking (TSN) standards have been adopted in the automotive domain to ensure highly reliable and real-time data transmission. IEEE 802.1CB is one of the TSN standards that proposes a Frame Replication and Elimination for Reliability (FRER) mechanism. With FRER, streams requiring reliable transmission are duplicated and sent over disjoint paths in the network. FRER enhances reliability without sacrificing real-time data transmission through redundancy in both temporal and spatial dimensions, in contrast to the acknowledgment and retransmission mechanisms used in traditional Ethernet. However, previous studies have demonstrated that, under specific conditions, FRER can lead to traffic bursts and
Luo, FengRen, YiZhu, YianWang, ZitongGuo, YiYang, Zhenyu
This paper examines the challenges and mechanisms for ensuring Freedom from Interference in Adaptive AUTOSAR-based platforms, with a focus on managing Memory, Timing, and Execution challenges. It explores the robust safety mechanisms in Classic AUTOSAR that ensure Freedom from Interference and the significant challenges in achieving interference-free operation in Adaptive AUTOSAR environments while adhering to ISO26262 standards. The study emphasizes strategies for managing complexities and outlines the multifaceted landscape of achieving interference-free operation. Additionally, it discusses ASIL-compliant Hypervisor, memory partitioning, and Platform Health Management as mechanisms for ensuring safety execution. The paper also raises open questions regarding real-time problems in live projects that are not solved with existing safety mechanisms. Adaptive AUTOSAR plays a crucial role in the development of autonomous and connected vehicles, where functional safety is of utmost
Jain, Yesha
This paper introduces an innovative digital solution for the categorization and analysis of fractures in Auto components, leveraging Artificial Intelligence and Machine Learning (AI/ML) technologies. The proposed system automates the fracture analysis process, enhancing speed, reliability, and accessibility for users with varying levels of expertise. The platform enables users to upload images of fractured parts, which are then processed by an AI/ML engine. The engine employs an image classification model to identify the type of fracture and a segmentation model to detect and analyze the direction of the fracture. The segmentation model accurately predicts cracks in the images, providing detailed insights into the direction and progression of the fractures. Additionally, the solution offers an intuitive interface for stakeholders to review past analyses and upload new images for examination. The AI/ML engine further examines the origin of the fracture, its progression pattern, and the
Sahoo, PriyabrataRawat, SudhanshuGarg, VipinNaidu, GarimaSharma, AmitNarula, RahulBindra, RiteshKhera, PankajGoel, PoojaMondal, Arup
The advancement of autonomous driving perception frequently necessitates the aggregation of data, its subsequent annotation, the implementation of training procedures, and other related activities. In contrast, the utilisation of synthetic data obviates the necessity for data collection, annotation, and the generation of accurate and reliable labels. Its incorporation into the development process is anticipated to streamline the entire algorithmic development process. In this study, we propose a novel approach utilising the Blender software to create a virtual representation of an underground car park and develop an automated parking dataset. The utilisation of virtual simulation technology enables the generation of diverse and high-quality training data, thereby addressing the challenge of acquiring data in the actual scene. The experimental results demonstrate that the model trained based on the synthetic dataset exhibits superior performance in the automatic parking task, thereby
Li, JiakaiLiu, YangleRong, Zheng
To improve the accuracy and reliability of short-term prediction of highway visibility level in key scenarios such as short duration and fast changing speed, this paper proposes a short-term prediction method for highway visibility level based on attention mechanism LSTM. Firstly, XGBoost and SHAP methods are used to analyze the factors affecting highway visibility, determine the importance ranking of different influencing factors, and select the factors that have a greater impact on visibility as inputs for the visibility level prediction model. Secondly, based on LSTM as the model foundation network and innovative coupling attention mechanism, a visibility level prediction model based on attention mechanism LSTM is constructed, which can dynamically update the correlation between meteorological feature information at each historical time point and the visibility level at the current prediction time, thereby dividing the importance of information and flexibly capturing important
Ding, ShanshanXiong, ZhuozhiHuang, XuLi, Yurong
This study tackles the issue of order delays in logistics using XGBoost for feature analysis and reinforcement learning for intelligent courier scheduling. Pickup order data from May 1 to October 31, 2023, in Chongqing is analyzed using spatio-temporal statistical methods. Key findings include that order placement peaks at 9:00 a.m., delays peak at 10:00 a.m., and the delay rate is 8.6%. A significant imbalance exists between the regional daily average of dispatchable couriers and order volumes.XGBoost is employed to predict order delays, revealing that pickup location is the most influential factor (27%), followed by courier pickup location (22%). These factors and their relationships are identified as key drivers of delays.To address these issues, a reinforcement learning-based courier scheduling optimization model is developed. The model defines courier location, current time, and pending orders as state variables and adopts an epsilon-greedy strategy for action selection
Wang, ManjunYu, Xinlian
Since the rapid development of the shipping and port industries in the second half of the twentieth century, the introduction of container technology has transformed cargo management systems, while simultaneously increasing the vulnerability of global shipping networks to natural disasters and international conflicts. To address this challenge, the study leverages AIS data sourced from the Vessel Traffic Data website to extract ship stop trajectories and construct a shipping network. The constructed network exhibits small-world characteristics, with most port nodes having low degree values, while a few ports possess extremely high degree values. Furthermore, the study improved the PageRank algorithm to assess the importance of port nodes and introduced reliability theory and risk assessment theory to analyze the failure risks of port nodes, providing new methods and perspectives for analyzing the reliability of the shipping network.
Li, DingCheng, ChengZhao, XingxiLi, Zengshuang
Monitoring the safety and structural condition of tunnels is crucial for maintaining critical infrastructure. Traditional inspection methods are inefficient, labor-intensive, and pose safety risks. With its non-contact, high-precision, and high-efficiency features, mobile laser scanning technology has emerged as a vital tool for tunnel monitoring. This paper presents a mobile laser scanning system for tunnel measurement and examines techniques for calculating geometric parameters and processing high-resolution imaging data. Empirical evidence demonstrates that mobile laser scanning offers a reliable solution for evaluating and maintaining tunnel safety.
Lianbi, YaoZhang, KaikunDuan, WeiSun, Haili
Currently, the application scope of fuel cell vehicles is gradually expanding. There is currently no durability testing method for the entire vehicle level in its research and development design process. In this article, a certain fuel cell passenger car is taken as the research object. The load spectrum data of its key components is collected. A ‘user goal test field’ multi-channel multi-dimensional load correlation optimization model is established. The goal is to minimize the difference in pseudo damage of special components such as the fuel cell vehicle stack structure under the user’s full life cycle target load and the test field test load. The characteristics of the multi-dimensional load of the fuel cell components corresponding to the optimized solution in the rainflow distribution and frequency domain distribution are calculated. And a durability reliability acceleration testing specification for fuel cell vehicle test fields for special components such as the stack structure
Wu, ShiyuGuo, TingWang, YupengWu, ZhenWang, Guozhuo
This paper presents a fault diagnosis strategy that integrates model-based and data-driven approaches for a 115 kW proton exchange membrane fuel cell used in vehicles. First, a stack subsystem model was developed in the MATLAB/Simulink platform based on the working principles and structure of PEMFC, and validated with experimental data. Subsequently, faults in the air and hydrogen inlet pipelines were simulated, and the resulting fault data were subjected to preprocessing steps, including cleaning, normalization, and feature extraction, to enhance the efficiency of subsequent data processing. Finally, a BP neural network optimized by particle swarm optimization was employed to achieve fault tree-based classification diagnosis. Experimental results indicate that the diagnosis accuracy of the BP neural network reached 96.04%, with an additional accuracy improvement of approximately 2.4% after PSO optimization.
Wang, ZeZhu, ShaopengChen, PingLi, CongxinZhou, Wenhua
Mechanical component failure often heralds superficial damage indicators such as color alteration due to overheating, texture degradation like rusting or false brinelling, spalling, and crack propagation. Conventional damage assessment relies heavily on visual inspections performed by technicians, a practice bogged down by time constraints and the subjective nature of human error. This research paper delves into the integration of deep learning methodologies to revolutionize surface damage evaluation, addressing significant bottlenecks in diagnostic precision and processing efficiency. We detail the end-to-end process of developing an intelligent inspection system: selecting appropriate deep learning architectures, annotating datasets, implementing data augmentation, optimizing hyperparameters, and deploying the model for widespread user accessibility. Specifically, the paper highlights the customization and assessment of state-of-the-art models, including EfficientNet B7 for
Cury, RudonielGioria, GustavoChandrasekaran, Balaji
Traditional vehicle diagnostics often rely on manual inspections and diagnostic tools, which can be time-consuming, inconsistent, and prone to human error. As vehicle technology evolves, there is a growing need for more efficient and reliable diagnostic methods. This paper introduces an innovative AI-based diagnostic system utilizing Artificial Intelligence (AI) to provide expert-level analysis and solutions for automotive issues. By inputting various details such as the vehicle’s make, model, year, mileage, problem description, and symptoms, the AI system generates comprehensive diagnostics, identifies potential causes, suggests step-by-step repair solutions, and offers maintenance tips. The proposed system aims to enhance diagnostic accuracy and efficiency, ultimately benefiting mechanics and vehicle owners. The system’s effectiveness is evaluated through various experiments and case studies, showcasing its potential to revolutionize vehicle diagnostics.
Sasikala, T.Swathi, B.Raj, J. Joshua DanielShetty, G. ShreyasDidagur, Darshan
The increase in vehicular traffic on Indian roads has led to a significant rise in the frequency of horn usage, particularly in city driving conditions and during peak traffic hours. Existing electro-mechanical horns are designed to have a mission life of 100,000 cycles according to Indian standards IS 1884 [1]. However, the intensified usage patterns have prompted a re-evaluation of the efficacy of these requirements. Studies reveal that the average horn blow frequency for normal usage vehicles is approximately three times per kilometer. When extrapolated to various usage categories, such as public transport and privately owned vehicles, observed increase in average horn blowing frequency per kilometer. When extrapolated, this corresponds to more than 4 lakhs cycles for a vehicle mission life of 2.5 lakhs kilometers. This insight drives the need to review and update validation test specifications to better align with customer usage patterns, thereby enhancing component reliability. By
Joshi, Vivek S.Jape, Akshay
Researchers have developed a new method for predicting what data wireless computing users will need before they need it, making wireless networks faster and more reliable. The new method makes use of a technique called a “digital twin,” which effectively clones the network it is supporting.
Increased use of advanced composite structural materials on aircraft has resulted in the need to address the more demanding quality and nondestructive testing procedures. Accordingly, increased utilization of solid laminate composites is driving changes to airline NDI/NDT training requirements and greater emphasis on the application of accurate NDI/NDT methods for composite structures. Teaching modules, including an introduction to composite materials, composite NDI/NDT theory and practice, special cases and lessons learned, are included in this document as well as various hands-on NDI/NDT exercises. A set of proficiency specimens containing realistic composite structures and representative damage are available to reinforce teaching points and evaluate inspector’s proficiency. Extensive details of the guidance modules, hands-on exercises, and proficiency specimens are all presented in this document. This document does not replace OEM guidance as may be specific to material, process
AMS CACRC Commercial Aircraft Composite Repair Committee
This SAE Standard for reliability-centered maintenance (RCM) is intended for use by any organization that has or makes use of physical assets or systems that it wishes to manage responsibly.
G-11M, Maintainability, Supportability and Logistics
This paper presents additive Weibull reliability model using customer complaints data and finite element fatigue (FEA) analysis data. Warranty data provides insight into the underlying customer issues. Reliability engineers prepare a prediction model based on this data to forecast the failure rate of components. However, warranty data has certain limitations with respect to prediction modeling. The warranty period covers only the infant mortality and useful life zone of a bathtub curve. Thus, predicting with solely warranty data generally cannot provide results with desired accuracy. The failure rate of wear-out components is driven by random issues initially and wear-out or usage-related issues at the end of the lifetime. For accurate prediction of failure rate, data need to be explored at wear-out zone of a bathtub curve. Higher cost always limits the testing of components until failure, but FEA fatigue analysis can provide the failure rate behavior of a part much beyond the warranty
Koulage, Dasharath BaliramMondal, KanchanManerikar, Dattatray Shriniwas
Just as a business needs an effective and reliable service to deliver its goods to customers, medications need an effective delivery system to get them to the specific area of the body where they can have an impact.
Advances in IoT and electronic technology are enabling more personalized, continuous medical care. People with medical conditions that require a high degree of monitoring and continuous medication infusion can now take advantage of wearable medicine injection devices to treat their problems. Wireless communication allows medical personnel to monitor and adjust the amount and flow rate of an individual’s medication. The small size of the injectors enables the individual to be active and not be burdened or limited by a line-powered instrument (see Figure 1).
As the U.S. military embraces vehicle electrification, high-reliability components are rising to the occasion to support their advanced electrical power systems. In recent years, electronic device designers have started using wide band-gap (WBG) materials like silicon carbide (SiC) and gallium nitride (GaN) to develop the semiconductors required for military device power supplies. These materials can operate at much higher voltages, perform switching at higher frequencies, and feature better thermal characteristics. Compared to silicon, SiC-based semiconductors provide superior performance. The growing availability of these materials, in terms of access and cost, continues to encourage electrification. With the ever-present pressure of size, weight, and power (SWaP) optimization in military applications, and a desire to keep up with the pace of innovation, there's a need for capacitors that can deliver higher power efficiency, switching frequency, and temperature resistance under harsh
American drivers have long been accustomed to quickly filling up at a gas station with plenty of fuel available, and electric vehicle drivers want their pit stops to mimic this experience. Driver uncertainty about access to charging during long trips remains a barrier to broader EV adoption, even as the U.S. strives to combat climate change by converting more drivers.
In the rapidly evolving landscape of electronic engineering, the reliability of electronic components under varying thermal conditions has emerged as a paramount concern. This paper presents an integrated approach for the reliability analysis of electronic components, emphasizing thermal impacts. Our methodology synergizes computational thermal analysis, experimental stress testing, and Failure Modes, Effects, and Diagnostic Analysis (FMEDA) to offer a comprehensive framework for assessing and enhancing component reliability, specifically focusing on a case study of motorcycle hand control switches. The approach begins with a detailed thermal simulation to identify potential hot spots and thermal gradients across electronic components under different operational scenarios. For the case study, motorcycle hand control switches a critical interface between the rider and the motorcycle's electrical system were subjected to this analysis to predict thermal behavior under varied
Mote, ShwetaJadhav, ShantaramChaudhari, VijayMhaske, Aashay
As aerospace engineers push the boundaries of new frontiers, the need for advanced materials that can withstand the rigorous demands of these advanced applications is relentless. These materials go beyond functionality; it is about ensuring reliability in the skies, where failure is not an option. Fluorosilicone can help do exactly that. In the 1960s, the U.S. Air Force noticed that conventional silicone-based sealants, coatings, and other components degraded rapidly when exposed to fuels, de-icing fluids, and other hydrocarbon-based solvents. Dimethyl-based silicones are non-polar and easily absorb hydrocarbon-based solvents, which may result in material swelling, mechanical weakening, and ultimately, failure.
For many patients waiting for a donor heart, the only way to live a decent life is with the help of a pump attached directly to their heart. This pump requires about as much power as a TV, which it draws from an external battery via a seven-millimeter-thick cable. The system is handy and reliable, but it has one big flaw: despite medical treatment, the point at which the cable exits the abdomen can be breached by bacteria.
The aerospace industry heavily relies on NASGRO as a standard method for crack propagation analysis, despite encountering challenges due to variations in stress gradients across flight missions. In response to this issue, this paper introduces a pioneering methodology that integrates stress gradients at each time point throughout a mission, computed cycle by cycle using NASGRO. The study meticulously evaluates the feasibility and efficacy of this approach against established industry-standard procedures, focusing on the critical topic of low cycle fatigue (LCF) and underscoring the significance of damage-tolerant design principles. The methodology encompasses the design of an H-sector in Ansys Workbench, the execution of stress analysis for a typical flight mission profile, and the systematic extraction of stress gradients for each cycle at the pivotal crack nucleation point. Subsequently, NASGRO is employed to estimate life cycles using both industry-standard baseline methodologies
Karandikar, Rishi SuhasKumar, Niraj
Though modal analysis is a common tool to evaluate the dynamic properties of a structure, there are still many individual decisions to be made during the process which are often based on experience and make it difficult for occasional users to gain reliable and correct results. One of those experience-based choices is the correct number and placement of reference points. This decision is especially important, because it must be made right in the beginning of the process and a wrong choice is only noticeable by chance in the very end of the process. Picking the wrong reference points could result in incomplete modal analysis outcomes, as it might make certain modes undetectable, compounded by the user's lack of awareness about these missing modes. In the paper an innovative approach will be presented to choose the minimal number of mandatory reference points and their placement. While other approaches use results of numerical simulations or rely on a visual evaluation of measurement
Kamper, TimBeljan, DenisBrücher, HaikoWegerhoff, Matthias
Traditional CACC systems utilize inter-vehicle wireless communication to maintain minimal yet safe inter-vehicle distances, thereby improving traffic efficiency. However, introducing communication delays generates system uncertainties that jeopardize string stability, a crucial requirement for robust CACC performance. To address these issues, we introduce a decentralized model predictive control (MPC) approach that incorporates Kalman filters and state predictors to counteract the uncertainties posed by noise and communication delays. We validate our approach through MATLAB/Simulink simulations, using stochastic and mathematical models to capture vehicular dynamics, Wi-Fi communication errors, and sensor noises. In addition, we explore the application of a reinforcement learning (RL)-based algorithm to compare its merits and limitations against our decentralized MPC controller, considering factors like feasibility and reliability.
Seifoddini, ArashAzad, ArefehMusa, AlessiaMisul, Daniela
The standard may have changed everything, just not how you think. On May 25, 2023, Ford made an announcement that seemed unimaginable. For those in the EV and standards industry, it caught many by surprise. Ford was partnering with Tesla to move away from the CCS (J1772/CCS) standard that's on a majority of electric vehicles and would switch to the Tesla NACS (North American Charging Standard) in the future. “When the J3400 news broke or the NACS partnerships broke, it kind of went around the regulatory ‘there's no way around that’ and it was just the worst day because I thought we were going to lose, open, collaboratively created standards,” Sarah Hipel, standards and reliability program manager for the Joint Office of Energy and Transportation told the audience at SAE's WCX 2024. Hipel was on a panel titled, “In The Wake of J3400 (NACS), Are Standards Still Needed?”
Baldwin, Roberto
In commercial aerospace, the application areas for motors are wide and varied, each with their own unique requirements. From electric vehicle take-off and landing (eVTOL) air taxis to business jets to long-haul commercial transport aircraft, DC motors must endure various environmental conditions like extreme temperatures, shock and vibration, atmospheric pressures and signal interference, to name just a few. These applications may also demand motors that provide a fast response, high power or torque density. In addition to these requirements, the aerospace industry perpetually calls for lightweight materials and smaller installation spaces. Taken together, it can be very difficult to specify and buy a reliable motor for mission-critical equipment. This article will present common commercial aerospace applications that pose performance and environmental challenges for DC motors along with a summary of the stringent aerospace industry standards that the motors must satisfy. It will also
In recent years, the automotive industry has been making efforts to develop vehicles that satisfy customers’ emotions rather than malfunctions by improving the durability of vehicles. The durability and reliability of vehicles sold in the U.S. can be determined through the VDS (Vehicle Dependability Study) published by JD Power. The VDS is index which is the number of complaints per 100 units released by J.D. POWER in every year. It investigates customers who have used it for 3 years after purchasing a new car and consists of 177 specific problems grouped into 8 categories such as PT, ACEN, FCD, Exterior. The VDS-4 has been strengthened since the introduction of the new evaluation system VDS-5 in 2015. In order to improve the VDS index, it is important to gather various customer complaints such as internet data, warranty data, Enprecis data and clarify the problem and cause. Enprecis data is survey of customer complaints by on-line in terms of VDS. In the case of warranty and Enpreics
You, Hanmin
The study and application of Topology Optimization (TO) has experienced great maturity in recent years, presenting itself as a highly influential and sought-after design tool in both the automotive and aerospace industries. TO has experienced development from single material topology optimization (SMTO) to multi-material topology optimization (MMTO), where material selection is simultaneously optimized with material existence. Today, MMTO for standard structural optimization responses are well supported. An additional and vital response in the design of structures is that of stress. Stress-driven or stress-controlled optimization techniques for SMTO are well understood and have been well-documented, evidenced by both published works and its availability in multiple commercial solvers. However, its integration into MMTO frameworks has not yet achieved reliable levels of accuracy and flexibility. The principal limitation of existing stress-constrained MMTO methodologies is the inability
Shi, YifanHuang, YuhaoMorris, ZaneTeoli, MiraTameer, DanielKim, Il Yong
This paper presents deep learning-based prognostics and health management (PHM) for predicting fractures of an electric propulsion (eP) drivetrain system using real-time CAN signals. The deep learning algorithm, based on autoencoders, resamples time-series signals and converts them into 2D images using recurrence plots (RP). Subsequently, through unsupervised learning of DeepSVDD, it detects anomalies in the converted 2D images and predicts the failure of the system in real-time. Also, reliability analysis based on fracture mechanics was performed using the detected signals and big data. In particular, the severity of the eP drivetrain system is proportional to the maximum shear stress (τmax) in terms of linear elastic fracture mechanics (LEFM) and can be calculated by summarizing the relationship between cracks (a) and the stress intensity factor (KIII). During this process, the system status can be checked by comparing the stress intensity factor and fracture toughness (KIIIc), and
Moon, ByungwooLee, SangWonNam, DongJinKim, JeonghwanBae, JaeWoongShin, JeongMin
General Motors (GM) is working towards a future world of zero crashes, zero emissions and zero congestion. It’s “Ultium” platform has revolutionized electric vehicle drive units to provide versatile yet thrilling driving experience to the customers. Three variants of traction power inverter modules (TPIMs) including a dual channel inverter configuration are designed in collaboration with LG Magna e-Powertrain (LGM). These TPIMs are integrated with other power electronics components inside Integrated power electronics (IPE) to eliminate redundant high voltage connections and increase power density. The developed power module from LGM has used state-of-the art sintering technology and double-sided cooled structure to achieve industry leading performance and reliability. All the components are engineered with high level of integration skills to utilize across TPIM variants. Each component in the design is rigorously analyzed and tested from component to system levels to ensure high
Nassiri Bavili, ArashBasher, KorobiChung, SungAlam, KhorshedLee, Jung-GiChoi, Hong GooKo, Jin-youngAnwar, Mohammad
This paper reviews the current situation in the development of accelerated testing of automotive engineering, consisting of the four following areas: 1. Field testing of the natural product. 2. Additional technology of separate testing in the laboratory on the basis of physical simulation of separate field conditions using corresponding methods and equipment separately and conducting: safety testing, special programs of testing using digital simulation, special testing with changing certain parameters of environment, corrosion testing, etc. Both of the traditional testing developments above can be found in many magazines, journals, conferences, presentations, and proceedings. 3. Testing on the basis of digital (computer) simulation of product and/or field conditions. This area of testing has been developed in the last dozen years. Many articles and presentations were published during this time. 4. Accelerated reliability and durability testing for obtaining during service-life of the
Klyatis, Lev
Global automobile manufacturers are increasingly adopting vehicle architecture development systems in the early stages of product development. This strategic move is aimed at rationalizing their product portfolios based on similar specifications and functions, with the overarching goal of simplifying design complexities and enabling the creation of scalable vehicles. Nevertheless, ensuring consistent performance in this dynamic context poses formidable challenges due to the wide range of design possibilities and potential variations at each development stage. This paper introduces an efficient reliability analysis process designed to identify and mitigate the distribution of Ride and Handling (R&H) performance. We employ a range of reliability analysis techniques, including Latin Hypercube Sampling and the enhanced Dimension Reduction (eDR) method, utilizing various types of models such as surrogate models and multi-body dynamics models. This approach is applied to predict R&H
Ji-In, Jung
Certain sports utility vehicles (SUVs) utilize dual latches and gas struts in their hood design. This is primarily driven by the larger size of the hood and specific architectural requirements. These hoods can be securely latched either by a dynamic single stroke closing method or by quasistatic two stroke closing method. In dynamic method, the hood is closed with a single, high-velocity motion for the final primary latching, whereas in quasistatic method, force is initially applied for the secondary latching and then for the final primary latching. In this study, both the dynamic and quasistatic closing methods are compared in terms of closing force and velocity and hood over travel distance. A load cell is used for measuring the closing force, velocity meter is used for velocity measurement and a rope sensor is used for measuring the hood over travel distance. It is evident from the study that the velocity required for hood closing is higher in the dynamic method, than the quasi
Selvan, VeeraSakthivel, GowthamR, BalajiAS, KevinA, SankaranarayananKamat, RohanUnadkat, SiddharthPandurangan, Venugopal
Bhutan is a small nation in the eastern Himalayas, between two of the world's largest neighbors and fastest-growing economies; China, and India. The GDP of the country is $2.707 Billion as of 2022. Bhutan’s largest renewable source is hydropower, which has a known potential of 30,000 MW. However, it has only been able to harvest only 1,480 MW (5% of the potential). The current overall electrification rate is 99% overall with 98.4% in rural areas. It exports 75.5% of total electricity generated in the country to India. However, the reliable supply of electricity remains a big challenge. The government is also pushing the use of renewable energy sources like solar and wind to diversify the energy mix and enhance the power security of the country. The share of renewable energy is very minimal at present amounting to 723 kW Solar PV and 600 kW Wind power. Bioenergy in the form of fuel wood, energy crops & crop residues, and cattle dung has great potential in the country as the country’s
Wangchuk, SingyeKumar, Naveen
The current automotive industry has a growing demand for real-time transmission to support reliable communication and for key technologies. The Time-Sensitive Networking (TSN) working group introduced standards for reliable communication in time-critical systems, including shaping mechanisms for bounded transmission latency. Among these shaping mechanisms, Cyclic Queuing and Forwarding (CQF) and frame preemption provide deterministic guarantees for frame transmission. However, despite some current studies on the performance analysis of CQF and frame preemption, they also need to consider the potential effects of their combined usage on frame transmission. Furthermore, there is a need for more research that addresses the impact of parameter configuration on frame transmission under different situations and shaping mechanisms, especially in the case of mechanism combination. Firstly, this paper comprehensively reviews the schedulability analysis of the combined usage of CQF and frame
Luo, FengWang, ZitongRen, YiWu, MingzhiZhang, Xiaoxian
Accurate and reliable localization in GNSS-denied environments is critical for autonomous driving. Nevertheless, LiDAR-based and camera-based methods are easily affected by adverse weather conditions such as rain, snow, and fog. The 4D Radar with all-weather performance and high resolution has attracted more interest. Currently, there are few localization algorithms based on 4D Radar, so there is an urgent need to develop reliable and accurate positioning solutions. This paper introduces RIO-Vehicle, a novel tightly coupled 4D Radar/IMU/vehicle dynamics within the factor graph framework. RIO-Vehicle aims to achieve reliable and accurate vehicle state estimation, encompassing position, velocity, and attitude. To enhance the accuracy of relative constraints, we introduce a new integrated IMU/Dynamics pre-integration model that combines a 2D vehicle dynamics model with a 3D kinematics model. Then, we employ a dynamic object removal process to filter out dynamic points from a single 4D
Zhu, JiaqiZhuo, GuirongXiong, Luzihang, heLeng, Bo
UC Santa Cruz Assistant Professor of Electrical and Computer Engineering Yu Zhang and his lab are leveraging tools to improve the efficiency, reliability, and resilience of power systems, and have developed an artificial intelligence (AI)-based approach for the smart control of microgrids for power restoration when outages occur.
With 40 years of experience to its name, Sunview Patio Doors Ltd. (acquired by Novatech Group in 2021), has solved one of the industry’s top challenges: meeting customers’ increased demands for faster and better services, while providing an option for product customization. Its ability to adopt digital technology allowed the company to satisfy its customers and compete globally in the marketplace.
Chris and Julie Ramsey covered more than 33,000 km (20,505 miles) across three continents in an all-electric passenger vehicle from 1823's magnetic North Pole to the South Pole in a world-first expedition. The Scottish adventurers joyfully recounted their 10-month long globetrotting feat during an interview with SAE Media at the 2024 Chicago Auto Show. The Ramseys' four-wheel transporter was a production 2022 Nissan Ariya e-4ORCE crossover SUV with no changes to the drivetrain, suspension system or 87-kWh lithium-ion battery system. “We wanted to keep the modifications minimal to prove the reliability of a standard EV,” Julie Ramsey said.
Buchholz, Kami
The process of manufacturing high-quality and reliable balloon catheters is critical to a number of advanced medical treatments for patients including balloon angioplasty, stent and drug delivery, transcatheter aortic valve implantation, atherectomy, renal denervation, and laser balloon angioplasty. These minimally invasive procedures have vastly improved quality of life, increased patient safety, decreased recovery times, and lowered treatment costs for patients around the globe.
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