Browse Topic: Reliability

Items (3,493)
The growing global adoption of electric vehicles (EVs) has resulted in a spike in the number of EV charging stations. As EVs have become more and more popular worldwide, a large number of EV charging stations are opening up to accommodate their demands. During grid failures, an EV charging station can also serve as a flexible load connected to the grid to balance out voltage fluctuations. An EV charging station when powered using a separate source, such as solar or wind, can function as a powerhouse, bringing electricity to the grid when it's needed. Therefore, instead of installing more equipment to sustain voltage, the current EV charging station can be efficiently used to meet the grid's needs during failures. These stations have the potential to be dynamic, grid-connected assets for sustainable cities and communities in addition to their core function of vehicle charging (SDG 11). Because of their dual purpose, they can serve as adaptable loads that reduce voltage variations during
R, UthraRangarajan, RaviD, SuchitraD, Anitha
The landing gear, as a crucial component of an aircraft, is pivotal for maintaining the safety and reliability of air travel. This study introduces a data-driven structural optimization method aimed at mitigating the peak strain on the landing gear’s rocker arm. The initial phase involves selecting nine design variables for parametric modeling to generate an initial dataset. Subsequently, the Maximum Information Coefficient (MIC) technique is used to conduct a parameter sensitivity analysis, enabling the identification and elimination of variables with minimal influence. A comparative analysis between the Genetic Algorithm–Backpropagation Neural Network (GA-BPNN) and BPNN reveals that GA-BPNN has a superior fitting capability on the enhanced dataset. By applying Particle Swarm Optimization (PSO), the optimal solution for GA-BPNN is identified. The implementation of this optimized method results in a 38.16% reduction in peak strain, validating its feasibility and reliability in
Chen, HuShi, ShiWang, MengFang, XingboWei, XiaohuiNie, Hong
How engineers can ensure safety, reliability and quality in aerospace systems. Courbevoie, Île-de-France In an industry where failure is not an option and precision is paramount, aerospace manufacturers and suppliers are constantly seeking components and system solutions that deliver trusted reliability, performance, and compliance. Industry standards are a key part of achieving these high expectations, bringing together global leaders in the mobility industries to create defined, repeatable methods and consistent processes. One of these aerospace standards is AS1895 developed by SAE International - a critical standard due to the need for durable components that can withstand extreme conditions and offer high performance: high-temperature resistance, pressure sealing, and long service life with a cost-effective installation method. Leading aerospace companies such as Eaton and Honeywell have been manufacturing components that meet this standard for a long period of time.
Traction motors technology has, driving the EV industry forward with more efficient, lightweight, and durable solutions. However, despite these advancements, noise testing at the end of the production line remains a critical stage for identifying manufacturing defects in traction motors. Hence early fault detection in traction motors is crucial to ensure safety and reliability of EV. This research contributes a solution that predicts early-fault detection, supporting improved reliability, reduced material cost and minimizing process time in the series production line. To identify the root cause of this problem, historical quality data has been acquired from manufacturing plants to enable efficient analysis. Feature selection was then carried out using embedded and wrapper methods to identify the most important features. These selected features were subsequently used as input for ML models. The best accuracy was achieved using SVC model for early-stage motor failure prediction.
Gaikwad, PoojaNangare, KapilrajSuryawanshi, Chaitanya
The proliferation of wireless charging technology in electric vehicles (EVs) introduces novel cybersecurity challenges that require comprehensive threat analysis and resilient design strategies. This paper presents a proactive framework for assessing and mitigating cybersecurity risks in wireless charger Electronic Control Units (ECUs), addressing the unique vulnerabilities inherent in electromagnetic power transfer systems. Through systematic threat modeling, vulnerability assessment, and the development of defense-in-depth strategies, this research establishes design principles for creating robust wireless charging ecosystems resistant to cyber threats. The proposed framework integrates hardware security modules, encrypted communication protocols, and adaptive threat detection mechanisms to ensure operational integrity while maintaining charging efficiency. Experimental validation demonstrates the effectiveness of the proposed security measures in preventing unauthorized access, data
Uthaman, SreekumarMulay, Abhijit BGadekar, Pundlik
Accurate trajectory prediction of traffic agents is critical for enabling safer and more reliable autonomous driving, particularly in urban driving scenarios where close-range interactions are most safety critical. High-definition (HD) and standard-definition (SD) maps play a vital role in this process by providing lane topology and directional cues for forecasting agent movements. However, HD maps are expensive and resource-intensive to create, often requiring specialized sensors, while SD maps lack the precision needed for reliable autonomous navigation. To address this, we propose a novel framework for trajectory prediction that leverages online reconstruction of HD maps using vehicle-mounted cameras, offering a scalable and cost-effective alternative. Our method achieves improvements in predicting accuracy, particularly in close-range scenarios, the most crucial for urban driving, while also performing robustly in settings without pre-built maps. Furthermore, we introduce a new
Upreti, MinaliGirijal, RahulB A, NaveenKumarThontepu, PhaniGhosh, ShankhanilChakraborty, Bodhisattwa
As electric trucks become more central to modern logistics, the need for smarter, more adaptive route planning is growing rapidly. This paper presents a key navigation feature for analyzing and recalibrating such optimized routes in real time. Integrating map features into the navigation mode improves user experience by offering real-time navigation and dynamic route adjustments based on traffic updates, road closures, vehicle coordinates and deviation in expected energy consumption. This study compares the performance of Server sent events (SSE), web sockets, and Application programming interface (API) polling methodologies, focusing on metrics such as data transmission efficiency, latency, resource utilization, scalability, and reliability. Our results demonstrate the advantages and limitations of each method, providing insights into their suitability for real-time route optimization in electric truck logistics. The results highlight the potential of SSE in achieving efficient and
Bhandari, MehulKaur, PrabhjotDadoo, VishalMahendrakar, ShrinidhiRamanaiah, Rachala
This paper elucidates the implementation of software-controlled synchronous rectification and dead time configuration for bi-directional controlled DC motors. These motors are extensively utilized in applications such as robotics and automotive systems to prolong their operational lifespan. Synchronous rectification mitigates large current spikes in the H-bridge, reducing conduction losses and improving efficiency [1]. Dead time configuration prevents shoot-through conditions, enhancing motor efficiency and longevity. Experimental results demonstrate significant improvements in motor performance, including reduced thermal stress, decreased power consumption, and increased reliability [2]. The reduction in power consumption helps to minimize thermal stress, thereby enhancing the overall efficiency and longevity of the motor.
Patil, VinodKulkarni, MalharSoni, Asheesh Kumar
In today’s market, faster product development without compromising durability is essential. Durability assessment ensures a vehicle maintains structural integrity under normal and extreme conditions. Achieving this requires effective Road Load Data Acquisition, integrated with robust design practices and efficient validation processes. However, physical RLDA is time-consuming and costly, as it depends on prototype vehicles that are often available only in the later development stages. Failures identified during these late-stage tests can delay the product launch significantly. This study presents a full digital methodology of fatigue life estimation for suspension aggregates. A study has been demonstrated on Rear Twist Beam component of rear suspension. The approach integrates the digital RLDA methodology presented in literature and finite element analysis simulation process, enabling durability assessments entirely within the virtual domain. This approach demonstrates how digital RLDA
Kokare, SanjayDwivedi, SushilSiddiqui, ArshadIqbal, Shoaib
The durability of wheel bearings is assessed in terms of raceway life and flange life. Raceway life focuses on the performance and damage tolerance of rolling elements, while flange life evaluates the structural integrity of wheel flanges under operational stresses. Traditionally, durability predictions relied on conventional design methods and analytic formulas for raceway spalling, as well as static load assumptions for flange fatigue analysis. Recently, integrating design of experiments (DOE) with traditional approaches has enhanced these methods, enabling systematic evaluation of design variables and loading conditions. This paper introduces a methodology for analyzing raceway life and damage in automotive wheel bearings using RLDA (Road Load Data Acquisition) data. The process involves acquiring raw deterministic load data, filtering it to preserve high-peaked signals, and transforming the filtered data into block cycles derived from load time histories. Each block cycle contains
Narendra, VishwanathMane, YogirajPaua, KetanSingh, Ram KrishnanVellandi, Vikraman
Automotive systems are increasingly adopting data-driven and intelligent functionality in the areas of predictive maintenance, virtual sensors and diagnostics. This has led to a need for the AI models to be directly run on vehicle ECUs. However, most of these ECUs – especially those in cost-sensitive or legacy platforms lack the computational capacity and parallel processing support required for standard AI implementations. Given the stringent real-time and reliability requirements in automotive environments, deploying such models presents a unique challenge. This paper proposes a practical methodology to optimize both the training and deployment phases of AI models for low-computation ECUs that operate without parallelism. Designing lightweight model architectures, using pruning and quantization techniques to minimize resource utilization, and putting in place a strategy appropriate for single-threaded execution are the three main objectives of the developed approach. The goal is to
Sharma, SahilMathew, Melvin John
Durability validation of full vehicle structures is crucial to ensure long-term performance and structural integrity under real-world loading conditions. Physical test strain and finite element (FE) strain correlation is vital for accurate fatigue damage predictions. During torture track testing of the prototype vehicle, wheel center loads were measured using wheel force transducers (WFTs). In same prototype strain time histories were recorded at critical structural locations using strain gauges. Preliminary FE analysis was carried out to find out critical stress locations, which provided the basis for placement of strain gauges. Measured loads at wheel centers were then used in Multi Body Dynamics (MBD) simulations to calculate the loads at all suspension mount points on BIW. Using the loads at hard points transient analyses were performed to find out structural stress response. Strain outputs from the FE model were compared with physical measurements. Insights gained from these
Jaju, MayurDokhale, SandeepGadre, NileshPatil, Sanjay
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
Beesetti, SivaHattarke, MallikarjunJames Aricatt, JohnPathan, Eram
Without reliability and signal integrity, aerospace communications risk severe signal degradation and reduced security, posing risks to both personnel and mission-critical data. These challenges are particularly critical for applications that depend on military aircraft, satellite communications, and unmanned aerial vehicles (UAVs). As global demand for real-time data continues to surge, communication infrastructure requires regular maintenance and upgrades to maintain secure and reliable performance.
FMEA is a systematic approach aimed at identifying and mitigating potential risks in the design, manufacture, and maintenance of a product. Implementing FMEA provides a range of benefits, such as: Preventing potential failures early in the life cycle. Identifying risk - establishing clear linkages ensures that no potential failure mode is overlooked across the life cycle of the product. Improving product safety, reliability, performance, and supportability. Enhancing collaboration - the framework fosters cross-functional communication, enabling design, manufacturing, and maintenance teams to work in harmony. Achieving effectiveness - by integrating analyses and plans, organizations can streamline workflows and reduce redundancies. Reducing costs associated with product failures. Enhancing customer satisfaction through consistent quality and reliability. Improving product quality - comprehensive linkage reduces errors and ensures a robust design and manufacturing process. Providing the
G-41 Reliability
Reliability and performance are critical for product success in engineering. With this aim, the Focus Matrix is a strategic tool designed to enhance the development process by effectively managing technical requirements and prioritizing resources. This paper outlines the application of the Focus Matrix in product development to organize technical packages based on complexity and the technical expertise of the project team. The methodology will be illustrated through a case study on the second-generation Flex Fuel (EVO) fuel pump developed by Bosch. The Fuel pump is responsible for delivering fuel to the engine while maintaining optimal pressure and flow rate. Transitioning to a second generation of a fuel pump focuses on optimizing performance to keep the product relevant in the market, necessitating a thorough analysis of lessons learned and current technological trends. Throughout the development phase, the Focus Matrix provided a structured approach for identifying and mitigating
de Souza, Ana Laura Limade Oliveira Melo, Lazaro BeneditoAguiar, Rayssa Moreno SilvaAzevedo Fernandes, Luiz Eduardo deBoa, Nathan Barroso Fonte
Building a green and ecological railway transportation system that incorporates the “Dual-Carbon” Strategy is a central focus and challenge in current industry research. In the western mountainous regions with complex engineering geological conditions and fragile ecosystems, it is particularly important to explore the optimal railway route under the framework of the “Dual-Carbon” strategy. By analyzing the characteristics of the geographic environment of the western mountainous areas and the trend of low-carbon railroad construction, and referring to the relevant principles of railroad line selection, the method of quantifying the carbon emissions during the construction phase of the railroad and the carbon sequestration capacity of the land lost as a result of the railroad project’s land occupation is proposed by selecting 23 indicators from the five aspects of engineering adaptability, low-carbon adaptability, economic adaptability, environmental adaptability, and social adaptability
Wang, Yibo
In order to ensure the construction safety of tunnels in water-rich sections near reservoir areas, it is very important to adopt comprehensive and reliable advanced geological prediction technology combined with on-site monitoring and measurement. Taking the Chenlingding tunnel as an example, through the comprehensive geological prediction of the broken rock section near the reservoir, the numerical model of the broken rock section was established, and compared with the field measurement data. The results show that the comprehensive advanced geological prediction system combining short, medium and long distances, such as geological radar, seismic wave reflection method and advanced horizontal drilling, has high accuracy in adverse geology, rock fragmentation and water rich conditions in the tunnel; The rich water condition, fault information and rock engineering geology provided by the advanced geological prediction can provide reliable guarantee for the tunnel excavation scheme, the
Dai, YunfeiFeng, MeijieLiu, DachengTang, Xianyuan
Heavy-haul railways are a critical component of China’s dedicated freight rail network, serving as the primary land transport channel for energy and resource intermodal transportation. Their safe operation and transportation is essential for ensuring the reliable delivery of energy and raw materials. Taking the Shuohuang Heavy-haul Railway as a case study, based on the hazards identified across its entire operational chain, an ontology model structured as "professional module–task–process–hazard–risk attribute–management object" is constructed in this paper. Based on this model, a knowledge graph for heavy-haul railway operational emergencies is established. The study analyzes the connectivity between different nodes (e.g., work processes and hazards) in the knowledge graph and their potential relationships with risk values. Using directed graph-based degree centrality analysis, a risk assessment method incorporating node centrality is proposed. Risk values are computed at both the
Fu, LiqiangRen, XiaolinRong, Lifan
To delay the formation and development of local periodic fluctuations on the surface of rail structures and improve the durability of rail facilities, the dynamic response and wheel-rail interaction of rail structures were studied in depth based on frequency-modulated rail dampers (TRDs). A fully-coupled 3-D FE framework of the wheel–rail assembly, integrating frequency-modulated rail dampers (TRDs), was developed to quantify vibration energy dissipation. Simulated decay curves revealed a marked rise (> 50 %) in lateral damping efficiency within 600–1 000 Hz, confirming TRD’s targeted suppression of rail transverse motion. Then, the suppression effect of rail corrugation after TRD installation was tested, and the data collection was carried out in the test section to calculate the frequency of rail corrugation. It was found that the possibility of corrugation deterioration of the rail structure was greatly reduced after the installation of the rail damper, and the suppression effect of
Li, ChengshunLei, Zhenyu
Traffic flow prediction is the core challenge of transportation, and its key lies in effectively capturing the spatio-temporal dynamic dependencies. Aiming at the deficiencies of existing methods in modeling global temporal relations and dynamic spatial heterogeneity, this paper proposes a dynamic graph convolutional recurrent network (DGCRN) based on interactive progressive learning. First, the interactive progressive learning module (IPL) is designed to segment the input sequences through a tree structure, synchronize the extraction of spatiotemporal features using the interactive learning of parity subsequences, and adaptively capture the dynamic associations among nodes by combining with the dynamic graph convolutional recursive module (DGCRM). Secondly, a spatio-temporal embedding generator (STEG) is constructed to fuse temporal and spatial embedding to generate dynamic graph structures. Experiments validate the effectiveness of DGCRN on the PEMS04 and PEMS08 datasets with MAE
Su, JiangfengXie, ZilongLiu, ChunyaHe, LanKou, YujiaoXue, Xue
With the continuous development of avionics systems towards greater integration and modularization, traditional aircraft buses such as ARINC 429 and MIL-STD-1553B are increasingly facing challenges in meeting the demanding requirements of next-generation avionics systems. These traditional buses struggle to provide sufficient bandwidth efficiency, real-time performance, and scalability for modern avionics applications. In response to these limitations, AFDX (Avionics Full-Duplex Switched Ethernet), a deterministic network architecture based on the ARINC 664 standard, has emerged as a critical solution for enabling high-speed data communication in avionics systems. The AFDX architecture offers several advantages, including a dual-redundant network topology, a Virtual Link (VL) isolation mechanism, and well-defined bandwidth allocation strategies, all of which contribute to its robustness and reliability. However, with the increasing complexity of onboard networks and multi-tasking
Yang, LeiYang, YouzhiWang, ZhaoyiChang, AnZhang, XinLin, Zi
In today’s medical equipment market, reliability is not a luxury — it is a necessity. Every adjustment, every movement, and every interaction with the equipment must be performed flawlessly to ensure patient safety, caregiver efficiency, and long-term service life. Behind this design and precision are highly engineered motion control components, such as gas springs, electric linear actuators, and dampers, that ensure safe, ergonomic operation of medical equipment across a wide range of healthcare applications.
The reliability and durability of vehicles are crucial for the acceptance of new technologies by customers. Realistic test methods are necessary to validate or ensure the lifespan of vehicles and their components, particularly regarding specific conditions such as freeze start. This article provides an overview of the current state of research on the effects of freeze starts on the degradation of fuel cells. With this knowledge, relevant operating and boundary conditions for potential damage of the fuel cell are identified (e.g. start temperature, duration in subzero operation, dehydration). The field data from the BMW demonstrator fleet of iX5 Hydrogen Next were analyzed to gain insights into realistic freeze start related stress to the fuel cells. The dynamics of heating rates and the influence of the operating strategy are best represented on a Fuel Cell System (FCS). An experimental setup for a stack centered test on a FCS was developed including a climatic chamber and a subzero
Schwarz, MarkusAlbert, AlbertEichel, Rüdiger-A.
With the rapid development of e-commerce, the logistics industry also presents new features such as multi-level, integrated upstream-downstream operations, increasingly perfect service quality and low logistics costs. The exponential growth in online transactions and consumer expectations for faster, more reliable deliveries intensifies the pressure on logistics systems. The last-mile service network refers to the logistics nodes that have direct contact with consumers, and its geographical location and quantity will directly affect the service level, cost and customer service mode of the distribution network. However, with the rapid growth in the number of online shoppers and their imbalance on the Internet, these factors have gradually become an important basis for influencing the layout of terminal outlets. This imbalance, coupled with dynamic urban traffic conditions, renders traditional distribution planning methods inadequate. Therefore, in the e-commerce environment, how to
Tong, TongGu, XuefeiLi, Lingxiao
In today’s competitive landscape, industries are relying heavily on the use of warranty data analytics techniques to manage and improve warranty performance. Warranty analytics is important since it provides valuable insights into product quality and reliability. It must be noted here that by systematically looking into warranty claims and related information, industries can identify patterns and trends that indicate potential issues with the products. This analysis helps in early detection of defects, enabling timely corrective actions that improve product performance and customer satisfaction. This paper introduces a comprehensive framework that combines conventional methods with advanced machine learning techniques to provide a multifaceted perspective on warranty data. The methodology leverages historical warranty claims and product usage data to predict failure patterns & identify root causes. By integrating these diverse methods, the framework offers a more accurate and holistic
Quadri, Danishuddin S.F.Soma, Nagaraju
The reliability of vehicle steering systems is extremely important to ensure safety, vehicle performance and gain customer satisfaction. Life data analysis conducted to analyze how the steering systems are performing in the field and assess whether the steering systems can meet the reliability target when deployed in the field. This article discusses about the systematic process to conduct the field data analysis of Hydraulic Powered Steering System (HPS) from the warranty claim data, usage of Weibull distribution to derive the life characteristic parameters. Based on the process described in this article, the statistical analysis of the warranty claim data performed and identified that, “the Hydraulic Power Steering Gears demonstrated more than 99% reliability in the field with statistical confidence of 90% and able meet the ZF’s Internal target for the HPS Systems”.
Ravindran, MohanSugumar, Ganesh
The reliability and durability of off-highway vehicles are crucial for industries like construction, mining, and agriculture. Failures in such machines not only disrupt operations but can also lead to significant economic losses and safety concerns. Effective failure and warranty analysis processes are essential to improve customer support, minimize downtime, and enhance equipment life cycle. This paper outlines a comprehensive 7-step failure analysis methodology tailored for off-highway vehicles, accompanied by warranty analysis using Weibull, 6MIS, and 12MIS IPTV. It details the process from problem identification through permanent solution implementation, emphasizing tools and techniques necessary for sustainable improvements. The structured approach provides an actionable blueprint for OEMs and service teams to enhance customer satisfaction, support sustainable development goals, and maintain regulatory compliance.
Mulla, TosifThakur, AnilTripathi, Ashish
In view of the complexity of railway engineering structure, the systematicness of professional collaboration and the high reliability of operation safety, this paper studied the spatial-temporal information data organization model with all elements in whole domain for Shuozhou-Huanghua Railway from the aspect of Shuozhou-Huanghua Railway spatial-temporal information security. Taking the unique spatial-temporal benchmark as the main line, the paper associated different spatial-temporal information to form an efficient organization model of Shuozhou-Huanghua Railway spatial-temporal information with all elements in the whole domain, so as to implement the effective organization of massive spatial-temporal information in various specialties and fields of Shuozhou-Huanghua Railway; By using GIS (Geographic Information System) visualization technology, spatial analysis technology and big data real-time dynamic rendering technology, it was realized the real-time dynamic visualization display
Liu, KunYu, HongshengZhu, PanfengLiu, WenbinWang, Yaoyao
Reliability engineering is a science and technology to fight against product failure, which includes reliability requirements and allocation, reliability analysis, reliability modeling and prediction, reliability design, reliability test, reliability testing, operational reliability and other activities. The important condition for the high-quality development of rail traffic is the stable operation of equipment, and the electronic equipment of rail traffic vehicles is mostly the “brain” of the key system. At present, the contradiction between performance optimization and structural complexity is increasingly prominent. In order to cope with the variable operating conditions and harsh environment of vehicles, the requirements for reliability are getting higher and higher. It is of great significance to carry out reliability engineering for its high-quality development. This paper introduces the construction of the reliability system of the electronic equipment of rail traffic vehicles
Song, XiaozhongSong, MengsiWang, Lei
Reliable seed germination and plant production requires an environment that is neither too dry nor too wet. PONDS was developed to improve water and nutrient delivery for plants grown on the International Space Station (ISS). The technology uses an innovative wicking material to passively link a water/nutrient reservoir to a growth cylinder where seeds are germinated and plants are produced. PONDS addresses limitations with existing ISS plant-production technology by providing consistent delivery of water/nutrients, improving oxygen transfer to plants, and allowing users to determine how much water is being applied.
Our research focuses on developing a novel loss function that significantly improves object matching accuracy in multi-robot systems, a critical capability for Safety, Security, and Rescue Robotics (SSRR) applications. By enhancing the consistency and reliability of object identification across multiple viewpoints, our approach ensures a comprehensive understanding of environments with complex layouts and interlinked infrastructure components. We utilize ZED 2i cameras to capture diverse scenarios, demonstrating that our proposed loss function, inspired by the DETR framework, outperforms traditional methods in both accuracy and efficiency. The function’s ability to adapt to dynamic and high-risk environments, such as disaster response and critical infrastructure inspection, is further validated through extensive experiments, showing superior performance in real-time decision-making and operational effectiveness. This work not only advances the state of the art in SSRR but also
Brown, Taylor J.Vincent, GraceNakamoto, KyleBhattacharya, Sambit
Time-Sensitive Networking (TSN) enhances Ethernet with features such as time synchronization, scheduled traffic, policing, and redundancy to enable highly deterministic and reliable communications in mission-critical systems. This paper presents a comprehensive approach to the configuration, analysis, and verification of TSN for critical systems, with a focus on time-sensitive applications such as tank barrel stabilization. The impact of different types of topologies, traffic types, and application requirements on the configuration complexity are presented along with various mathematical techniques to generate network solutions and verify against the system requirements. Detailed modeling, configuration, and analysis of TSN is demonstrated using a representative mixed criticality converged network. Lastly, configuration techniques to minimize the latency, jitter, and frame loss while maximizing the network utilization are presented.
Bush, Stephen F.Jabbar, Abdul
This article presents a novel mechanical model for simulating the behavior of pavement deflection measuring systems (PDMS). The accuracy of the model was validated by comparing the acceleration of the new model with the data achieved through experimental tests fusing a deflection measurement system mounted on a Ford F-150 truck. The experimental test for the PDMS is carried out on a random road profile, generated by an inertial profiler, over a 7.4-mile (12 km) loop around a lake near Austin, Texas. Integrating a reliability-based optimization (RBO) algorithm in a PDMS aims to optimize system parameters and reduce vibrations effectively. The PDMS noises and uncertainties make it crucial to use a robust system to ensure the stability of the system. This article presents a robust algorithm for considering the uncertainties of PDMS parameters, including the damping coefficients and spring stiffness of the supporting brackets. Moreover, it considers the variation of system parameters, such
Yarmohammadisatri, SadeghSandu, CorinaClaudel, Christian
Researchers in the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) and Vienna University of Technology (TU Wien) have invented a new type of tunable semiconductor laser that combines the best attributes of today’s most advanced laser products, demonstrating smooth, reliable, wide-range wavelength tuning in a simple, chip-sized design.
This article presents a path planning and control method for a cost-effective autonomous sweeping vehicle operating in enclosed campus. First, to address the challenges from perception, an effective obstacle filtering algorithm is proposed, considering the elimination of false detection and correction of object position. Based on it, the adaptive sampling–based path planner and pure pursuit controller are developed. Not only an adaptive cost-weighting mechanism is introduced by TOPSIS algorithm to determine the desired trajectory as a multi-objective optimization problem, but also the adaptive preview distance is designed according to the trajectory curvature and vehicle state. The real-vehicle tests are implemented in typical scenario. The results show that the 87.8% effective edge-following rate is achieved in curved paths, and 22.93% cleaning coverage is improved for cleaning coverage. Therefore, the proposed method is effective and reliable for cost-effective autonomous sweeping
Lei, WuKunYang, BoPei, XiaofeiZhang, YangZhou, HongLong
How to strike a balance between cable performance and resilience. In aerospace and defense applications, cables hold vast mechanical responsibility. Quietly operating in the background, they are expected to successfully transmit signals and data in some of Earth's harshest conditions, needing to withstand extreme winds, temperatures and vibrations. The main challenge lies in achieving the optimal balance between cable performance and rugged resilience. Here, Jeff Wood, from mil-spec cable specialist WireMasters, explains the importance of both performance and resilience in wiring solutions for aviation and military, and how to find a middle ground that best fits the application. Often, a successful cable design is associated with its speed or bandwidth. While both qualities contribute towards high cable performance, durability can consequently be overlooked. However, a resilient cable provides longevity, ruggedness and reliability, which are crucial to aerospace and military
ACT Expo 2025 had a fleet of new commercial vehicle launches as well as displays for models already on the market. One such existing chassis was the Workhorse W56, an electric step van designed for Class 5/6 last-mile delivery. Unlike many of its competitors, Workhorse did not set out to be a technological leader with the W56. Rather, the company took the approach of leveraging the best of the currently available and applicable technologies to produce a durable, reliable and producible product that just happened to be powered by electrons.
Wolfe, Matt
The exhaust front pipe is a critical structural component in commercial vehicles, ensuring the leak-proof flow of exhaust gases into the exhaust after-treatment system while withstanding engine and frame vibrations. To isolate these vibrations, the front pipe is equipped with a flex connector capable of enduring various displacements at frequencies between 8-25 Hz. The position of the flex connector relative to the engine crank axis significantly impacts its structural reliability over its service life. This paper compares the existing design, which features a horizontally positioned flex connector, with a modified design that positions the flex connector vertically and changes the material from SS-304 to SS-321. Finite element analysis was conducted using Nastran software. The fatigue life of the existing flex connector design is approximately 1015 cycles. In contrast, the improved design demonstrates a fatigue life of 1727 cycles, representing a 70% increase in durability compared to
Chandel, KushalParoche, SonuNamdev, AkhileshJain, ShailendraPatil, Keyur
The reliability and performance of steering systems in commercial vehicles are paramount, given their direct impact on reducing hazardous driving and improving operational efficiency. The torque overlay system is designed to enhance driver control, feedback, and reduce driver fatigue. However, vulnerabilities such as water ingress under certain environmental conditions have raised significant reliability requirements. This article discusses the systematic investigation into how radial bearing sideloading led to the input shaft seal failing to contact the input shaft. Water was allowed a path to enter the TOS module, affecting the electronic sensor, and faulting out the ADAS functionality. Improvement to the bearing support and sealing design culminated to an enhanced TOS module package able to withstand testing procedures that mimic the environmental and use case situation which caused the ingress.
Bari, Praful RajendraKintner, Jason
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