Browse Topic: Collaboration and partnering

Items (2,042)
The automotive industry is evolving from a reactive, independently self-determined approach to cybersecurity, complicated by a complex supply chain. Over time, this has resulted in a fragmented industry comprised of any number of proprietary solutions verses a standardized, regulated paradigm to facilitate a platform-oriented approach. This document, an update on collaborative work from the SAE Vehicle Electrical Hardware Security Task Force (TEVEES18B) and GlobalPlatform Automotive Task Force, outlines this transition strategy. An extensible number of additional examples of use cases of Global Platform Technologies are explored in this document.
Mazzara, BillRawlings, Craig
This paper builds on last year’s paper presenting DevOps automation in the context of model-based development. Following that paper, we interviewed Simulink users in passenger automotive, motorsports, commercial vehicles, aviation, rocketry, and industrial automation. We discovered that much of the benefit of DevOps platforms to reduce product development cycle time relies on their interactive features. We prototyped new tools to bridge interactive DevOps Git-based platforms with model-based development workflows, and then gathered reactions from another round of interviews. Here we present these interactive DevOps workflows with the feedback from these interviews to contextualize how engineering teams could adopt them to accelerate their own model-based workflows.
Mathews, JonFerrero, SergioTamrawi, AhmedSauceda, Jeremias
The tire model is a crucial component in the design of the K-characteristic of FSAE racing car suspensions, and directly influences the achievement of maximum cornering lateral force. Not only do the slip angle, vertical load, tire pressure, and camber angle affect the mechanical characteristics of the tire, but temperature is also an important influencing factor when FSAE vehicle tires operate at high speeds. However, the modeling process of traditional tire models based on temperature characteristics is often very complex. The FSAE tire test code (FSAE TTC) already has a large amount of official sample data, which provides a basis for data-driven neural network models. This study implemented a hybrid modeling methodology, constructing two cascaded feedforward neural networks that combine the physical interpretability of the Magic Formula tire model with the nonlinear approximation capabilities of neural networks. The first network model uses slip angle, vertical load, tire pressure
Liu, XiyuanWang, ShenyaoLi, MingyuanHuang, Jiayu
The shared autonomy framework has become an option with great potential in the field of autonomous vehicles. Human and machine control decisions typically demonstrate strengths in different scenarios. As a result, the robustness of systems can be enhanced by the collaboration between humans and autonomy. A shared autonomy architecture that takes into account both human and environmental factors was proposed in this work. The authority distribution between the human operator and the autonomy algorithm was determined by the Shared Autonomy Arbiter (SAB). Designed with a two-tier structure, the SAB incorporated a policy-level decision module, as well as a numerical-level arbitration tuning module. A fuzzy inference system (FIS) was incorporated to enhance the noise tolerance of the policy selection module. Furthermore, the human factor was taken into account by applying a projection to the users’ control input. The human operator’s control decision was projected by the Adaptive
Sang, I-ChenNorris, WilliamPatterson, AlbertSreenivas, Ramavarapu S.Soylemezoglu PhD, AhmetNottage, Dustin S.
With the rise of software-defined vehicles and the emergence of cyber threats to vehicular systems, developing teams are compelled to conduct extensive testing on both virtual and physical prototypes at an accelerated pace. This new development landscape necessitates diagnostic tools that are both precise and adaptable. However, proprietary systems dominate this field, often hindering accessibility for students and researchers due to high costs and restrictive licensing. This paper presents the design and implementation of an open-source, low-cost remote testing system tailored for automotive development and diagnostics. The proposed system utilizes Arduino and Raspberry Pi processing units, along with relay-based switching modules, to provide secure remote control of vehicle components through a web-based dashboard equipped with authentication, scheduling, and real-time synchronization capabilities. The tested prototype showcased robust scalability, secure session handling, and
Pries, AndrewMohammad, Utayba
A suspension system was designed, fabricated, and tested following a systems design approach by an SAE Off-road Team from a North Midwest university. Compared to previous suspensions, the new suspension system is more reparable and contains a minimal number of custom parts, while still maintaining sufficient strength to withstand dynamic loads experienced when operating the vehicle. Modifications were also made to fit the newly designed vehicle body frame. As an integral part of the team’s 2025 Baja vehicle, the redesigned suspension system contributed to the vehicle’s improved performance during the 2025 SAE (Society of Automotive Engineers) Baja Competition. This paper presents a detailed account of the design, development, and fabrication process of the suspension system. The final design was tested and evaluated via both computer simulations and physical tests, whose efficiency and reliability were finally demonstrated by the team’s improved ranking in the 2025 Baja SAE Competition
Liu, YuchengAnderson, MatthewLarson, CodyRodgers, JoshuaSeberger, AaronLetcher, Todd
The multi-body dynamics (MBD) model and the MATLAB Simulink model can be integrated to create a control-integration model. Using a high-fidelity MBD model to represent the vehicle as the plant, this integrated model can be used to analyze vehicle system physics and develop control strategies. For hybrid vehicles, this process is more complex because the powertrain and other vehicle systems are often built as separate MBD models. This paper describes a method for integrating a powertrain model developed in AMESIM, a vehicle model developed in SIMPACK, and a control model developed in MATLAB Simulink. The resulting integrated model was then used to perform frequency sweep analysis to identify driveline system properties. In particular, the driveline frequency and the amplitude of the transfer function between motor speed and motor torque are critical parameters. By applying active damping control to the driveline system, the peak amplitude and driveline vibrations can be reduced. The
Xing, XingMathew, Vino
Many academic institutions are turning to free and accessible gaming platforms such as Unreal Engine and Unity for research and educational purposes. In the Human Factors Group at the University of Michigan Transportation Research Institute (UMTRI), a multidisciplinary team of 19 students is developing an Unreal Engine-based driving simulator as a research tool to investigate the difficulty of driving roads, among other purposes. For those unfamiliar, Unreal Engine is a real-time 3D development platform that provides visual programming via its Blueprint system. Development on Unreal Engine can be done with C++ as well, but that was not commonly the case for this team. Throughout the course of the project, five significant documentation-related pain points were identified: (1) a lack of consistent documentation formatting and guidelines, (2) a lack of structure to keep information searchable and accessible, (3) code fragmentation and redundant logic, (4) a steep learning curve for new
Erturk, SelayStimec, LukaXin, Jared HongyiTasmaan, AshleyMitani, KateZhang, LuyaGreen, Paul
The evolution toward software-defined vehicles (SDVs) is causing disruption to the traditional automotive supply chain and breaking down the common hierarchical OEM, tier 1 supplier, and tier 2 supplier relationships. With demands for faster software release cycles, more advanced software projects involving multi-party development, and considerations for end-to-end embedded and cloud integrations, new cybersecurity challenges are introduced that no single organization can address alone. Thus, this disruption creates new trust dependencies and requires new models for collaboration, transparency, and joint responsibility in cybersecurity. This paper presents a collaborative cybersecurity model, emphasizing shared responsibility during multi-party development between OEMs, tier 1 and 2 suppliers, engineering services organizations, and technology and services providers. As such, we explore collaborative approaches for each stage in the development lifecycle including design, development
Oka, Dennis KengoVinzenz, Nico
The automotive industry is subject to major transformation initiated by societal and economical pull (reducing emissions, zero fatalities, European competitiveness) and accelerated by technology push (electrification, Cooperative, Connected and Automated Mobility (CCAM), and Cooperative Intelligent Transport Systems (C-ITS)). Following this trend, the Software-Defined Vehicle (SDV) targets the integration of software (SW) development methodologies for vehicle development as well as the value delivery shift toward customers along the entire lifecycle. It promises to create benefits for the car manufacturers in terms of faster time to market, easier update – as well as for the car users (private persons, fleet operators) in terms of personalized user experience, upgradability. At the same time, SDV requires a much more integrated and continuous development framework to enable different experts to efficiently develop and validate concurrently the different parts of the vehicles, to gather
Armengaud, EricPermann, RobertJoergler, SabrinaBarcelona, Miguel AngelGarcía, LauraRodriguez, José ManuelIvanov, ValentinLi, ZhenqianNguyen Quoc, TrieuRodrigues, SandyKowalczyk, BogdanAvdić Čaušević, Amra
This paper presents the collaborative efforts of the USCAR GPF OBD Working Group to evaluate and recommend On-Board Diagnostic (OBD) monitoring requirements for Gasoline Particulate Filters (GPFs). The group, comprising representatives from major OEMs, aims to establish a unified understanding of GPF monitoring capabilities and propose regulatory recommendations to CARB. The paper outlines the physics of soot generation and oxidation, regulatory interpretations, and diagnostic strategies, culminating in a proposed framework for GPF OBD compliance. The material in this paper was previously presented at the 2024 SAE OBD Symposium [1].
Van Nieuwstadt, MichielRamappan, VijayJohnson, LonnyWendling, Timothy
Trust calibration is vital for safe human–automation interaction but remains largely qualitative. This study develops multiple quantitative frameworks modeling trust as a function of automation reliability. Four progressive models of binary, linear, triangular, and logistic formalize the calibrated trust zone, defining where human reliance aligns with system performance. The framework corrects major misconceptions: that trust is purely qualitative, that low trust–low reliability states are acceptable, and that overtrust and distrust pose equal risk. It establishes a minimum reliability threshold for meaningful trust and identifies distrust as the safer default in high-risk contexts. A case study on an empirical observation of 32 AI applications plotted in the trust–reliability space confirms the analysis, revealing a consistent distrust tendency where reliability exceeds user confidence and other observations. By quantifying trust through reliability, the study reframes it as a
Wen, HeMounir, Adil
Reliable component libraries are the foundation of the engineering process and the starting point for all intelligence within CAD tools. In practice, however, libraries created and maintained by librarians often contain incomplete, inconsistent, or outdated data. This paper introduces the component data consistency and relationship inference AI system, developed within Amoeba software, which addresses these challenges by improving component library quality. The system uses AI to infer component attributes such as component type, gender, color, material, etc. Moreover, it can identify relationships such as the family a connector is associated with based on its attributes and geometry. The system improves data consistency in areas such as resolving mismatched wire size constraints imposed by the connector and cavity components. It also utilizes computer vision to identify common connector footprints, cavity sizes, and 2D symbol geometries. Deployed within Amoeba software, the system has
Phan, DungHorvat, Bryan
As automotive aerodynamic testing facilities evolve to capture more real-world behavior, updating the correlation between old and new technologies is essential. Recently, the three-member consortium of the United States Council for Automotive Research (USCAR) - General Motors, Ford Motor Company, and FCA US LLC - transitioned from full-size static ground plane facilities to 5-belt moving ground plane wind tunnel facilities. The primary objective of this study was to update the correlation data sets to maintain consistent and robust data sharing among companies, which is the cornerstone of USCAR efforts. To achieve this, a set of updated correlation data sets were calculated to replace the original correlation study results from 2008. Additionally, the methodology for applying correlation equations was revised from using averaged wind tunnel data to employing direct wind tunnel-to-wind tunnel correlation equations. In a two-phase correlation effort conducted in 2022 and 2025, the three
Nastov, AlexanderLounsberry, ToddMadin, TrevorLangmeyer, GregoryFadler, GregorySkinner, ShaunHorton, Damien
Mechatronic and cyber-physical systems emerge from interdisciplinary design efforts, integrating software (SW), electronics, and mechanical components. Developing such systems places high demands on organizations and processes, particularly regarding efficient collaboration across domains. A key challenge lies in establishing organizational structures and workflows which allow cross-discipline work and at the same time ensure compliance with regulations and adherence to standards such as Automotive Software Process Improvement and Capability Determination (ASPICE). In response, the authors have developed an Engineering Process Framework (EPF) grounded in International Council on Systems Engineering (INCOSE) systems engineering principles. The EPF provides a structured approach for system development and therefore defines company-wide processes and methods. This paper presents the development of the EPF’s functional logic and its implementation within a tool landscape. Furthermore, a
Gehrt, Jan-JöranGranrath, ChristianCaglayan, EbruReckeweg, ThomasRichert, Felix
A research team developed a smart strake system that dynamically adapts to flight conditions, showing a promising drag reduction in the wind tunnel with respect to passive strakes. This approach has the potential to save airlines hundreds of kilograms of fuel per flight. University of Washington Department of Aeronautics & Astronautics (A&A), Seattle, WA For decades, aircraft have carried a fundamental compromise between their engines and wing flow interactions by using strakes. These are small fins attached at the sides of engine nacelles that generate helpful vortices during takeoff and landing that boost lift and avoid stall, but create unwanted drag during cruise flight. Now, seven William E. Boeing Department of Aeronautics & Astronautics (A&A) undergraduates have advanced a solution that improves this trade-off, achieving up to 33 percent drag reduction, on the limited tested conditions, during cruise while maintaining critical safety benefits at high angles of attack. The team
Dassault Systèmes and NVIDIA have announced a long-term strategic partnership to establish a shared industrial architecture for mission-critical artificial intelligence across industries. Combining Dassault Systèmes' Virtual Twin technologies with NVIDIA AI infrastructure, open models and accelerated software libraries will establish science-validated industry World Models, and new ways of working through skilled virtual companions on the agentic 3DEXPERIENCE platform, that empower professionals with new expertise.
During the 2025 Association of the United States Army (AUSA) annual meeting and exhibition, Forterra announced several major defense industry vehicle partnerships and introduced four new integrated modules designed to enable autonomy for military vehicles, communications, and more. Headquartered in Clarksburg, Maryland, Forterra develops autonomous mission systems for specific defense applications, including robotics and self-driving vehicles. The company has a new partnership with BAE Systems that will rapidly prototype an autonomous Armored Multi-Purpose Vehicle (AMPV). Separately, Forterra has also collaborated with Oshkosh Defense and Raytheon to develop the “DeepFires” autonomous vehicle launcher technology.
Recent geopolitical events in Venezuela, Ukraine and other hot spots are a stark reminder that the long-term planning environment is fraught with challenges and opportunities that suppliers cannot control. The initiation of U.S. tariffs on its trading partners and various embargos also underscored that we have to be flexible in how we dole out capital and the risk we are assuming. The supply base is at the end of that chain. Any issues upstream will reverberate exponentially. It is obvious that the automotive world is re-regionalizing, and quickly. Why the concern? Some context. Until the '70s, every region essentially rowed its own boat. While there were some exports from one major region to another, there were regional OEMs that were sponsored by national governments due to job creation, tax base considerations and bragging rights. The U.S, France, Italy, Germany, Japan, South Korea and a host of others wanted to build national OEMs that could drive scale and become a global force.
The advanced construction equipment packing the convention center halls and surrounding lots will understandably be the stars of the triennial CONEXPO trade show, taking place March 3-7 in Las Vegas. But the latest technologies in fluid power and motion control that help those machines operate efficiently will also command attention from showgoers. The Bosch Rexroth mobile hydraulics team will be on-site in a joint booth with partner HydraForce (Booth S80245), showcasing their current product portfolio. Rafael Cardoso, Bosch Rexroth engineering manager, mobile systems and software, expects to have conversations about advanced control and automation, “focused on the demand for smarter, software-driven control strategies that enhance precision, productivity, downtime reduction and operator assistance features.”
Gehm, Ryan
Rolls-Royce has successfully tested the world's first high-speed marine engine powered exclusively by methanol on its test bench in Friedrichshafen, Germany. The company began this engine-development journey six years ago when it gathered experts to determine what the future fuel of the maritime industry should be, according to Denise Kurtulus, senior vice president of global marine at Rolls-Royce. “For us, it's clear. It's methanol,” she said. Rolls-Royce worked with industry partners as part of the joint project meOHmare, which is funded by the German Federal Ministry for Economic Affairs and Energy. Injection system specialist Woodward L'Orange and the WTZ Roßlau technology and research center contributed their expertise. Their goal was to not only develop a comprehensive concept for a CO2-neutral marine engine based on green methanol, but also to run it on the test bench by the end of 2025.
Gehm, Ryan
Dr. Mustafa Akbulut, Professor of Chemical engineering, has teamed up with Horticultural Science Professor Luis Cisneros-Zevallos to engineer longer-lasting, bacteria-free produce.
India has emerged as the world’s largest market for motorized two-wheelers (M2Ws) in 2024, reflecting their deep integration into the country’s transportation fabric. However, M2Ws are also a highly vulnerable road user category as according to the Ministry of Road Transport and Highways (MoRTH), the fatality share of M2W riders rose alarmingly from 27% in 2011 to 44% in 2022, underlining the urgency of understanding the circumstances that lead to such crashes. This study aims to investigate the pre-crash behavior and crash-phase characteristics of M2Ws using data from the Road Accident Sampling System – India (RASSI), the country’s only in-depth crash investigation database. The analysis covers 3,632 M2Ws involved in 3,307 crash samples from 2011 to 2022, representing approximately 5 million M2Ws nationally. Key variables examined include crash configuration, collision partner, road type, pre-event movement, travel speed, and human contributing factors. The study finds that straight
Govardhan, RohanPadmanaban, JeyaJethwa, Vaishnav
The exponential growth of connected and autonomous vehicles has significantly escalated cybersecurity threats, compelling automotive Original Equipment Manufacturers (OEMs) to adopt robust and structured Cybersecurity Incident Response (CSIR) capabilities. Current automotive cybersecurity regulations, such as AIS 189 in India and UNECE WP.29 globally, mandate precise frameworks for proactive threat detection, timely response, and comprehensive incident documentation. This research presents an innovative, comprehensive CSIR framework specifically tailored to integrate seamlessly into OEM cybersecurity management processes. Leveraging a combination of real-time monitoring systems, structured threat categorization methodologies, and integrated escalation and communication protocols, the proposed CSIR framework ensures efficient incident handling aligned with stringent regulatory compliance. The framework encompasses advanced methodologies including Vehicle Security Operations Center (VSOC
Chaudhary lng, VikashDesai, ManojChatterjee, AvikChatterjee lng, Avik
Simulation-driven product development involves numerous computer aided engineering (CAE) model iterations, where each version represents a critical difference. Usually, these multiple model versions are generated by hundreds of simulation engineers working in teams distributed across the globe, making functional collaboration a key to effective product development. To manage vast amounts of CAE data generated by engineers working simultaneously on a project, it is imperative to have a robust version management system to track changes in the CAE data. A robust version management is the backbone of an effective simulation data management (SDM) system. It involves capturing and documenting model changes at every design iteration. Accurate documentation of the model changes is crucial as it helps in understanding the model evolution and collaboration among engineers. However, documenting is usually considered a boring and tedious task by many engineers. This often leads to bad change
Thiele, MarkoSharma, Harsh
This article describes an enhanced, more efficient way to build and test wire harnesses. The wire harness is a complex, organized bundle of wire found in virtually every motorized vehicle, machinery and equipment. Manual work is usually performed in assembling such harnesses, which is time-consuming and error-prone. Workers usually rely on printed diagrams and basic tools, which can be tiring and tricky to follow, especially when the designs change often. The new system solves many of these issues by combining a smart testing machine called Quad 64 with a large digital display workbench. Instead of looking at paper drawings, workers can now see the full wire layout directly on a screen, life-sized and clear. This makes it easier to understand where each wire goes and what to do next. What’s really helpful is that the system can spot mistakes right away. If a connector is omitted or a wire is placed wrongly, the system will report the error immediately and show it and the remedy. It
Sancheti, Rahul Madanlal
The article is devoted to a comprehensive analysis of the digital transformation of education using the example of a project to train engineering personnel for the innovative transport industry in Russia. Special attention is paid to the introduction of hybrid formats, digital platforms, inclusivity, issues of digital inequality, as well as the experience of the National Research Center of the Russian Federation FSUE NAMI and interaction with leading universities in the country. A comparative analysis with foreign initiatives, including modern AI solutions for inclusive education, is presented, as well as the impact of the project to create educational and methodological centers on the professional motivation of teachers.
Shishanov, SergeiKurmaev, RinatRevenok, Svetlana
The automotive regulatory landscape in India is evolving rapidly, driven by a dynamic policy intervention by GOI, striking push for sustainable mobility, safety, technological advancements, dEnvironmentally soundeeper localization, energy self-reliance, product quality control and simplified registration process. Key regulations cover areas like vehicle safety norms, emission norms, fuel economy norms, BIS QCO, the promotion of EVs and alternative fuel vehicles, R & D roadmaps, ELVs, incentive policies and vehicle registration reforms. India has been keeping a close eye on the automotive regulatory progress in the Europe as well as other developed countries as a cornerstone for technical harmonization, cross learning, gauge benefits and economic implications. India is progressively aligning its automotive regulations with global standards, particularly with UN Regulations and GTRs, while also considering unique Indian driving and environmental conditions. This alignment is crucial for
Patil, Dharmarayagouda
In recent years many automotive cybersecurity relevant regulations have been released and some have already started to come into effect. Moreover, some other regulations will come into effect in the next few years. These regulations provide requirements and guidance to automotive organizations with different degree of specifics. In this paper, we review a number of different cybersecurity relevant regulations such as UNR 155, UNR 156, AIS 189, AIS 190, GB 44495, GB 44496, EU Cyber Resilience Act, and BIS Final Rule. We break down and categorize these regulations based on their scope and highlight key areas relevant to different teams within the organizations. These key areas include Cybersecurity Management System (CSMS), Software Update Management System (SUMS), secure software development and software supply chain security, continuous cybersecurity activities (monitoring, incident response), and vulnerability disclosure and management. We then map responsibilities from the
Oka, Dennis KengoVadamalu, Raja Sangili
Accurate power and energy assessment in Battery Electric Vehicles (BEVs) requires high-fidelity simulation models that reflect real-world performance. This study presents a power rating correlation of the BEV model in compliance with the GTR 21[1] standard, validating the simulation’s accuracy against physical test data. Simulations were conducted using Matlab and Simulink based Simulation tool to estimate Electric Drive Module (EDM) power at the motor output and gearbox input under standardized conditions. The operating parameters were shared with the testing team to ensure consistency; however, the initial test results deviated by approximately 4% to 5% from the simulation target. To address this delta, EDM speed and vehicle speed were optimized, achieving a close alignment with the simulation and meeting the power rating targets. The results demonstrate a strong correlation between the simulation and test data, confirming the model’s accuracy and reliability. This study underscores
Mahajan, PrasadKesarkar, SidheshAli, Shoaib
The automotive industry is currently undergoing a profound transformation, driven not only by the shift toward renewable propulsion systems but also by the increasing emphasis on the software-defined vehicle (SDV), which is particularly in the domain of ADAS and the qualification of vehicles towards higher levels of autonomy important. In combination with accelerating project timelines, this shift creates challenges in integrating electrical and electronic systems throughout the complete vehicle. Magna faces these challenges by intensifying the use of virtual development, a strategy that spans the entire vehicle development process and necessitates global collaboration among engineering teams. This publication presents a real-world example of how the automotive sector can transition from a traditional on-premises-environment (OPE) simulation setup to a Simulation-as-a-Service (SIMaaS) model. Our primary focus is on operational and collaborative dimensions, illustrating the significant
Wellershaus, ChristophWakharde, SagarBernsteiner, Stefan
The BioMap system represents a groundbreaking approach to collaborative mapping for autonomous vehicles, drawing inspiration from ant colony behavior and swarm intelligence. It implements a fully decentralized protocol where vehicles use virtual pheromone trails to mark areas of uncertainty, change, or importance, enabling efficient map consensus without centralized coordination. Key innovations include novel pheromone-based compression algorithms and bio-inspired consensus mechanisms that allow real-time adaptation to dynamic environments. In a simulated urban scenario (Town10HD), three vehicles achieved balanced load distribution (±1.8% variance) and comprehensive coverage of a 253.2m × 217.9m × 22.4m area. The final fused map contained 311 chunks with 72,785 particles and required only 10.4 MB of storage. Approximately 49.2% of map particles exceeded the pheromone significance threshold, indicating active importance marking, while no high-uncertainty regions remained. These results
Bhargav, Anirudh SSubbarao, Chitrashree
Cornell researchers and collaborators have developed a neural implant so small that it can rest on a grain of salt, yet it can wirelessly transmit brain activity data in a living animal for more than a year.
Bioelectronics, such as implantable health monitors or devices that stimulate brain cells, are not as soft as the surrounding tissues due to their metal electronic circuits. A team of scientists has developed a soft polymer hydrogel that can conduct electricity as well as metal can. As the material is both flexible and soft, it is more compatible with sensitive tissues. This finding has the potential for a large number of applications, for example, in biocompatible sensors and in wound healing.
Researchers from Harbin Institute of Technology and their collaborators have developed a multifunctional polyelectrolyte hydrogel reinforced with aramid nanofibers (ANFs) and MXene nanosheets, achieving outstanding performance in absorption-dominated electromagnetic interference (EMI) shielding and wearable sensing. This innovative hydrogel addresses the long-standing challenge of balancing electrical conductivity and effective EMI absorption in flexible electronic materials. The research was published in the journal Nano-Micro Letters. 1
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
In this article we will discuss the development and implementation of a computer vision system to be used in decision-making and control of an electro-hydraulic mechanism in order to guarantee correct functioning and efficiency during the logistics project. To achieve this, we have brought together a team of engineering students with knowledge in the area of Artificial Intelligence, Front End and mechanical, electrical and hydraulic devices. The project consists of installing a system on a forklift that moves packaged household appliances that can identify and differentiate the different types of products moved in factories and distribution centers. Therefore, the objective will be to process this identification and control an electro-hydraulic pressure control valve (normally controlled in PWM) so that it releases only the hydraulic pressure configured for each type of packaging/product, and thus correctly squeezing (compressing) the specific volume, without damaging it due to
Furquim, Bruno BuenoPivetta, Italo MeneguelloIbusuki, Ugo
In this study, an intelligent monitoring system for electric vehicle seats based on flexible pressure sensor array is proposed. Through the design of multi-layer composite film structure and the collaborative development of STM32 embedded platform, high-precision sensing (error<5%) and rapid response (<200ms) of pressure distribution are realized. The experimental results show that the linearity of the sensor array is ± 1.5% FS in the range of 0-100kpa, and the dynamic response time is 3.6 times higher than that of the traditional sensor; By establishing a three-level adjustment algorithm (fuzzy PID+LSTM prediction+genetic optimization), the seat comfort is improved by 20.5%, and the system energy consumption is reduced by 33.5%. The research provides theoretical and technical support for the transformation of intelligent seats from “passive support” to “active interaction”.
Huang, YifengRong, DaozhiLin, GuoyongHuang, ZhenguiWang, RuliangTao, Chengxi
In the development of virtual prototyping for rail vehicles, industrial design plays a bridging role between art and engineering. In the present industrial design process, on account of problems such as too many types of software were used and difficulties in model conversion, the research proposes a collaborative design method for industrial design based on the 3DE platform, aiming to establish a unified “3D data mainline” to achieve continuous development of industrial design and engineering design. Taking a certain urban rail vehicle as an example, the industrial design procedure is analyzed, including demand input, rapid modeling, real-time rendering, curve modeling, etc. It is hoped that this method can reduce development costs, shorten the time cycle, and improve work efficiency in the development process of virtual prototyping for rail vehicles.
Ji, XiranHuang, ShuoWang, ChuweiSun, Bowen
In the future battlefield, logistics UAVs will play an increasingly important role. The development of logistics UAVs abroad is rapid. Sort out the current development status of logistics UAVs in countries such as the United States, Russia, Israel, and Ukraine, including mission tasks, functional characteristics, and main performance indicators. In addition, the future technological trends of logistics UAVs are studied and predicted. Firstly, diversification of functions, which logistics UAVs will achieve diversified functions in the future, such as material transportation, aerial refueling, unmanned mother aircraft, and transfer of wounded personnel; Secondly, intelligent commendation and control, which logistics UAVs pursue the optimal efficiency in the four steps of ordering, dispatching, delivering, and evaluating in the “food delivery” mode; Finally, resource collaboration. In the collaborative logistics mode of “free riding”, logistics UAVs over a wide area are interconnected
Zhai, JundaLiu, DaweiBai, QiangqiangHua, JinxingWang, XiaoyueYang, JianZou, XiaoyingGao, Yuxuan
In order to reduce conflicts between vehicles at intersections and improve safety, an optimization model of traffic sequence allocation is studied and established for the heterogeneous traffic scenario of connected autonomous vehicles and manual vehicles. With the minimum safe traffic time as constraint, the right of way is allocated to vehicles according to the microscopic traffic characteristics of heterogeneous traffic flow fleet movement and the phase of signal lights, and the optimal trajectory planning control of each vehicle and evaluation indicators are established. A jointly simulation running environment is built using VISSIM and MATLAB. The simulation results indicate that at the micro level, collaborative control slows down the waiting time for manually driven vehicles and improves the utilization of green light travel time. At the macro level, as the penetration rate of connected autonomous vehicles increases, the sum of squares of vehicle acceleration gradually decreases
Yuan, ShoutongLi, ZhiqiangLiu, TianyuYu, Zhengyang
Pavement maintenance decision-making is the key to determining the maintenance program and ensuring the maintenance effect. Still, the existing pavement maintenance decision-making methods have problems, such as incomplete and inaccurate data. Based on this, this study develops an intelligent decision-making system for pavement maintenance on highways in Gansu Province by combining DeepSeek artificial intelligence technology with dynamic capability theory. The proposed framework integrates multi-source data fusion, predictive analytics, and organizational collaboration mechanisms to address the systematic challenges of resource allocation and decentralized decision-making. A spatio-temporal graph convolutional network enables accurate pavement performance modelling, while a redesigned decision-making process enhances cross-departmental coordination through game-theoretic optimization and blockchain-based traceability. The results show significant improvements in operational efficiency
Xie, ZilongLiu, ChunyaHuang, TaoKou, YujiaoXie, BingleiXue, Xue
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