Browse Topic: Design processes

Items (4,487)
The introduction of renewable energy systems offers the opportunity to achieve energy self-sufficiency or autarky in addition to contributing towards carbon neutrality by reducing the dependency on energy logistics. Amidst growing geo-political conflicts and natural calamities, the scenario of energy shortage or disruption of energy logistics is a major threat, especially for Europe due to the significant reliance on import of primary energy. Achieving autarky, however, requires a distinction between energy consumers that need uninterrupted energy supply and consumers that could potentially be cut-off during energy shortages to avoid prohibitive costs resulting from oversizing the system. Critical infrastructure such as hospitals, communication systems, emergency services and key mobility nodes like fuelling stations and charging points needed to sustain the services provided by them, always need continuous energy supply. The architecture in current tools for optimising the design and
Vijay, ArjunThaler, BernhardKöcheler, ValentinOppl, ThomasTrapp, Christian
The winding configuration of an electric machine has a decisive influence on the properties of a traction drive. When designing the electric drive, the optimum compromise must be found between maximum torque, maximum power and high efficiency over a wide operating range. A decisive factor in this design conflict is the choice of the winding configuration. The concept of winding switching offers a way of solving the design conflict and improving the characteristics of the drive through the additional degree of freedom of the variable winding configuration. Switching the number of parallel winding branches in a serial and parallel configuration is a promising approach to overcome the challenge of a high spread between maximum power and high efficiency in customer related driving scenarios of an electric vehicle. The aim of this study is to identify factors influencing the efficiency improvement potential of the winding switching topology under consideration compared to a reference drive
Oestreicher, RaphaelKoenen, ChristianKulzer, André Casal
The first step in designing or analyzing any structure is to understand “right” set of loads. Typically, off-road vehicles have many access doors for service or getting into cab etc. Design of these doors and their latches involve a knowledge of the loads arising when the door is shut which usually involves an impact of varying magnitudes. In scenarios of these impact events, where there is sudden change of velocity within few milliseconds, produces high magnitude of loads on structures. One common way of estimating these loads using hand calculations involves evaluating the rate-of-change-of-momentum. However, this calculation needs “duration of impact”, and it is seldom known/difficult to estimate. Failing to capture duration of impact event will change load magnitudes drastically, e.g. load gets doubled if time-of-impact gets reduced from 0.2 to 0.1 seconds and subsequently fatigue life of the components in “Door-closing-event” gets reduce by ~7 times. For these problems, structures
Valkunde, SangramGhate, AmitGagare, Kiran
Modern vehicle integration has become exponentially more difficult due to the complicated structure of designing wiring harnesses for multiple variants that have diverse design iterations and requirements. This paper proposes an AI-driven solution for addressing variant complexity. By using Convolutional Networks and Deep Neural Networks (CNN & DNN) to generate harness routing using defined specifications and constraints, the proposed solution uses minimal human intervention, substantially less time, and enables less complexity in designing. AI trained modelled systems can generally even predict failures in production methods which also reduces downtime and increases productivity. The new AI system automatically converts design specifications to manufacturable design specifications to avoid confusion with design parameters, by optimizing concepts with connector placements, grommet fittings, clip alignments, and other tasks. The solution coping with the inherent dynamic complexity of
N, Rishi KumaarPatil R, BharathRajavelu, VivekRamachandran, VigneshMohanty, LalitPadmarajan, Vishnu
Weight and cost are pivotal factors in new product development, significantly impacting areas such as regulatory compliance and overall efficiency. Traditionally, monitoring these parameters across various stages involves manual processes that are often time-intensive and prone to delays, thereby affecting the productivity of design teams. In current workflows, designers must manually extract weight and center of gravity (CG) data for each component from disparate sources such as CAD models or supplier documents. This data is then consolidated into reports typically using spreadsheets before being analyzed at the module level. The process requires careful organization, unit consistency, and manual calculations to assess the impact of each component on overall system performance. These steps are not only laborious but also susceptible to human error, limiting agility in design iterations. To address these challenges, there is a conceptual opportunity to develop a system that could
Patil, VivekSahoo, AbhilashBallewar, SachinChidanandappa, BasavarajChundru, Satyanarayana
Enhancing the performance of naturally aspirated 4-stroke engines relies heavily on improving trapping efficiency, increasing maximum engine speed, and reducing friction losses. In this regard, the valvetrain plays a critical role. Achieving high volumetric efficiency at higher engine speeds necessitates very steep valve opening and closing ramps, making this aspect pivotal in the design process. At high engine speeds, significant dynamic phenomena arise, including valve float during the lift phase and valve bounce during the closing phase. These effects not only induce substantial modifications to the valve lift curve but also increase the mechanical stress on critical components such as the valve and the rocker arm, thereby elevating the risk of failure. Moreover, the timing system substantially contributes to overall engine losses due to frictional energy dissipation, which results from the numerous interactions between moving components. The present work aims to develop a numerical
Tarchiani, MarcoPizzicori, AlessioRaspanti, SandroRomani, LucaMeli, EnricoFerrara, GiovanniTrassi, Paolo
The growing demand for lightweight, durable, and high-performance materials in industries such as aerospace, automotive, and energy has driven the development and evaluation of thermoset and thermoplastic composites. Within this framework the static and fatigue mechanical behavior of one thermoset material and two thermoplastic composites are investigated in the (-30° +120°C) temperature range, to simulate extreme environmental conditions. The results from the tensile tests show the different mechanical behavior of the investigated materials, while the cyclic test results highlight the significant impact of temperature on structural properties, offering useful insights for their application in temperature-sensitive environments. This research is partially funded by the Italian Ministry of Enterprises and Made in Italy (MIMIT) within the project ”New Generation of Modular Intelligent Oleo-dynamic Pumps with Axial Flux Electric Motors,” submitted under the ”Accordi per l’Innovazione
Chiocca, AndreaSgamma, MicheleFranceschini, AlessandroVestri, Alessiomancini, SimoneBucchi, FrancescoFrendo, FrancescoSquarcini, Raffaele
Thermal Management System (TMS) for Battery Electric Vehicles (BEV) incorporates maintaining optimum temperature for cabin, battery and e-powertrain subsystems under different charging and discharging conditions at various ambient temperatures. Current methods of thermal management are inefficient, complex and lead to wastage of energy and battery capacity loss due to inability of energy transfer between subsystems. In this paper, the energy consumption of an electric vehicle's thermal management system is reduced by a novel approach for integration of various subsystems. Integrated Thermal Management System (ITMS) integrates air conditioning system, battery thermal management and e-powertrain system. Characteristics of existing integration strategies are studied, compared, and classified based on their energy efficiency for different operating conditions. A new integrated system is proposed with a heat pump system for cabin and waste heat recovery from e-powertrain. Various cooling
K, MuthukrishnanS, SaikrishnaMahobia, TanmayVijayaraj, Jayanth Murali
In both internal combustion engine (ICE) and electric vehicles, Heating, Ventilation, and Air Conditioning (HVAC) systems have become significant contributors to in-cabin noise. Although significant efforts have been made across the industry to reduce noise from airflow handling systems, especially blower noise. Nowadays, original equipment manufacture’s (OEMs) are increasingly focusing on mitigating noise generated by refrigeration handling systems. Since the integration of refrigeration components is vital for the overall Noise Vibrations and Harshness (NVH) refinement of a vehicle, analysing the impact of each HVAC component during vehicle-level integration is essential. This study focused on optimizing the NVH performance of key refrigeration components, including the AC compressor, thermal expansion valve (TXV), suction pipe, and discharge line. The research began with a theoretical investigation of the primary noise and vibration sources, particularly the compressor and TXV
Titave, Uttam VasantKalsule, ShrikantNaidu, Sudhakara
In view of the contradiction between the best engine monomer performance and the poor vehicle performance existing energy management strategies, the objective of this study is to leverage deep reinforcement learning to incorporate the thermal characteristics of the engine into the optimization process of energy management strategies, thereby enhancing fuel economy under real-world vehicle operating conditions. Combining the real-time road condition information provided by the vehicle network system, the state space and action space are formulated based on the Soft Actor-Critic (SAC) reinforcement learning algorithm, taking into account energy power and engine cooling constraints, while a generalized reward function design methodology is proposed. Based on bench test data, this paper establishes a series hybrid electric vehicle model with integrated engine thermal characteristics, and validates the effectiveness of the algorithm under actual road conditions by using the engine bench
Fu, WeiqiLei, NuoZhang, Hao
The development of urban rail transit has diversified communication infrastructure needs, and the design of Communication-Based Train Control(CBTC) system is critical to improving passenger service quality. To ensure that all requirements are accurately communicated and traceable during the model design process, this paper conducts CBTC system modeling work based on model system engineering concepts. Requirements extraction, as a key step in system design and development, directly affects system performance, but traditional requirements extraction methods rely on manual analysis, which is time-consuming and error-prone. In this regard, this paper proposes a requirement extraction framework based on Named Entity Recognition (NER) technology, including requirement document preprocessing, key requirement extraction by BERT-BiLSTM-CRF and automated generation of requirement entries, and two sets of comparative experiments were conducted, and the results show that the model realizes the
Wan, KeyanWang, BaominWang, QingyongZhou, LujieGuan, Lin
This research is dedicated to exploring the application of large language models in the Beijing Subway scientific research project management platform. It conducts a thorough analysis of many key elements, including the application background, technical support, practical achievements, and future development paths. With the continuous development of the Beijing Subway construction scale, the number and complexity of scientific research projects have been gradually increasing. Traditional management models are getting more and more insufficient in dealing large amounts of data, complicated processes, and precise decision-making requirements. By using natural language processing, machine learning, knowledge graph pedigreestechnological and technical model related technologies, which are very different from the one of the most inventive ones, are presented. The objective of intelligence is to solve this model by automatically analyzing papers with a logical and scientific approach and
Pang, YuqiRen, LaihongLiu, Jing
A solid, reduced-weight drivetrain system with improved maneuverability was developed and tested by the Desert Hare Off-road Team from South Dakota State University (SDSU) for the 2024 Baja SAE Competition. Based on an analysis of previous competition results, driver feedback, and competition requirements, the designed drivetrain system should enable the Baja vehicle to achieve a top speed of 40 mph (64.37 kph) on a 40° slope and cover 150 ft in 4.5 s from a standing start. Following the systems engineering design approach, the drivetrain system was decomposed into six components. While every team had to use the same engine provided by SAE, the transfer case was designed, and the remaining components—including the transmission, differentials, axles, half shafts, and tires—were selected from the available options. The designed drivetrain was then installed on the team’s 2024 Baja vehicle for testing and validation. Test results indicated that the vehicle with the new drivetrain system
Spilde, RileyLiu, Yucheng
The force of the solid contact (Fsc ) between the bearing surface and the shaft surface and the friction force (Ffri ) generated in the crankpin bearing have a great influence on the lubrication performance of the crankpin bearing in the engine. Therefore, the micro-circular texture (MCT) has been proposed and designed on the bearing surface of the crankpin bearing for ameliorating its lubrication performance. To evaluate the effectiveness of MCT in detail, based on the lubricating model of the crankpin bearing under the impaction of external load F 0, the influence of the density, depth (hMCT ), and radius (rMCT ) of MCT on the characteristics of the pressure (p) of oil film, thickness of oil film (h), force of solid contacts, and force of the friction in the crankpin bearing are also investigated, respectively. An algorithmic program written in a MATLAB environment is then applied to simulate the lubrication equations of the crankpin bearing and MCT. Some outstanding results of the
Jiao, RenqiangNguyen, Vanliem
The light-duty transportation sector is experiencing a worldwide push towards reduced carbon intensity. One pathway that has been developed focuses on replacing internal combustion engine (ICE)-based vehicles with full-electric battery electric vehicles (BEV), which offer local carbon dioxide (CO2)-free mobility. However, batteries offer a limited mobility range and can require long recharging times, leading to a limited range perception among some vehicle operators. A range-extended electric vehicle (REEV) utilizes a small ICE to mitigate the range concerns of BEVs, while also enabling a battery size reduction with its associated improvements in cost, weight, and manufacturing-related CO2 intensity. A previous study by the authors discussed evaluation criteria for range extender engines (REx) and compared additive technology options to enable cost-, efficiency, or power-optimized REEV applications using a modular approach. This study contrasts the dedicated REx with associated modular
Hoth, AlexanderMarion, JoshuaSilvano, PeterPeters, NathanPothuraju Subramanyam, Sai KrishnaBunce, Mike
System-level design decisions in Formula SAE (FSAE) vehicles drive all downstream subsystem designs, yet these decisions are often based on historical precedent or anecdotal evidence rather than rigorous analysis. This work presents a simulation-driven methodology to support data-informed decisions early in the design process, specifically examining how overall vehicle parameters—such as engine power, vehicle mass, aerodynamic drag and lift, wheelbase, and track width—influence performance in a representative FSAE endurance scenario. Two types of lap-time simulation tools were used in this study: OpenLAP, a point-mass simulator, and ChassisSim, a transient 3D vehicle dynamics simulator that incorporates suspension geometry, yaw response, weight transfer, and steering effects. Initial simulations with OpenLAP were used to rapidly identify trends and guide early design decisions, while ChassisSim was used for detailed sensitivity analyses and to validate system-level trade-offs in a more
Hernandez, Andy JoseBachman, John Christopher
Ground vehicle software continues to increase in cost and complexity, in part driven by tightly integrated systems and vendor lock-in. One method of reducing costs is reuse and portability, encouraged by the Modular Open Systems Approach and the Future Airborne Capability Environment (FACE) architecture. While FACE provides a Conformance Testing Suite to ensure portability between compliant systems, it does not verify that components correctly implement standard interfaces and desired functionality. This paper presents a layered test methodology designed to ensure that a FACE component correctly implements working communication interfaces, correctly handles the full range of data the component is expected to manage, and correctly performs all of the functionality the component is required to perform. This testing methodology includes unit testing of individual components, integration testing across multiple units, and full hardware in the loop system integration testing, offering a
Lingg, MichaelPaul, HowardSullivan, KyleVanSolkema, William
In the ever-evolving landscape of ground vehicle development, the integration of Artificial Intelligence (AI), Machine Learning (ML), and Software Production Factory (SPF) technologies offers unprecedented opportunities to accelerate rapid prototyping processes. This whitepaper explores the synergistic potential of these cutting-edge technologies, detailing their transformative impact on the design, development, and deployment of advanced ground vehicle systems. By leveraging AI and ML algorithms, engineers can automate complex design tasks, predict performance outcomes, and optimize configurations with unparalleled precision. Enhanced modeling and simulation capabilities driven by AI and ML, combined with Digital Engineering threads and twin, allow for more accurate virtual testing environments, reducing the need for physical prototypes and accelerating the iterative design process. This whitepaper serves as a crucial guide for stakeholders seeking to harness the full potential of
Griffin, KevinKanon, RobertRinaldo, AnthonyKouba, Russ
The Ground Vehicle Systems Center (GVSC) has an ongoing effort to use Industrial Design to explore the toughest problems faced by the Army modernization community. That effort takes several steps from the Design thinking discipline and seeks to understand Soldier perspectives, define problems and propose conceptual solutions. This paper summarizes the employment of Industrial Design at GVSC as well as outputs from two key Design projects. It concludes by presenting the combined learned outcomes from several Design efforts at GVSC and proposes ways in which Industrial Design and Design Thinking can better drive Army modernization, by understanding user’s needs, and committing to Innovation.
Nyanankpe, Guenter
This paper presents a model-based systems engineering (MBSE) and digital twin approach for a military 6T battery tester. A digital twin architecture (encompassing product, process, and equipment twins) is integrated with AI-driven analytics to enhance battery defect detection, provide predictive diagnostics, and improve testing efficiency. The 6T battery tester’s MBSE design employs comprehensive SysML models to ensure traceability and robust system integration. Initial key contributions include early identification of battery faults via impedance-based sensing and machine learning, real-time state-of-health tracking through a synchronized virtual battery model, and streamlined test automation. Results indicate the proposed MBSE/digital twin solution can detect degradation indicators (e.g. capacity fade, rising internal impedance) earlier than traditional methods, enabling proactive maintenance and improved operational readiness. This approach offers a reliable, efficient testing
Sandoval, Roman
Tire and road wear particles (TRWP) have emerged as air quality hazardous matters and significant sources of airborne microplastic pollution, contributing to environmental and human health concerns. Regulatory initiatives, such as the Euro 7 standards, emphasize the urgent need for standardized methodologies to quantify TRWP emissions accurately. Despite advancements in measuring tire abrasion rates, critical gaps persist in the characterization of airborne TRWP, particularly regarding the influence of collection system design and influencing parameters on measurement accuracy and repeatability. This study addresses these challenges by designing a controlled methodological framework that aims to minimize the influencing effects and ensure comparability in TRWP emission quantification results. At the German Aerospace Center (DLR) dynamometer testbench in Stuttgart, Germany, a methodical framework was established to ensure the repeatability and comparability of TRWP measurements
Celenlioglu, Melis SerenEpple, FabiusReijrink, NinaLöber, ManuelReiland, SvenVecchi, RobertaPhilipps, Franz
As electric mobility spreads and evolves, non-exhaust Particulate Matter (PM) sources are gaining more attention for total vehicular emissions. A holistic approach for studying the involved phenomena is necessary to identify the parameters that have the greatest impact on this portion of emissions. To achieve this, it is necessary to develop a new platform capable of both creating testing methodologies for future regulations and enabling the parallel development of advanced tyres and brakes that meet these standards, by correlating vehicle dynamics, driving style, tyre and brake characteristics, and the resulting emissions. Here the authors present the Sustainable Integrated System for Total non-Exhaust Reduction (S.I.S.T.E.R.) project, funded by the Italian Centro Nazionale per la Mobilità Sostenibile (MOST), that aims to develop an integrated approach to study tyre/brake-related emissions from the initial stages of compound development to outdoor vehicle tests, allowing actions to be
Genovese, AndreaDe Robbio, RobertaLenzi, EmanueleCaiazza, AntonioLippiello, FeliceCostagliola, Maria AntoniettaMarchitto, LucaSerra, AntonioArimondi, MarcoBardini, Perla
The rapid development of electric mobility leads to improve the performance of all the powertrain components. There is still a high need to maximize their efficiency for autonomy reasons, but weight and volume are critical parameters for automotive, aeronautic or train applications. This paper focuses on electrical machines, especially the permanent magnet synchronous axial flux motors (PMSAFM) which offer advantages in terms of power density and volumetric electromagnetic torque. The paper proposes a panorama of solutions for designing such a motor, with an application case to 100 kW – 10000 rpm, and an objective of 12 kW/kg at steady state. Obtaining such a power density can be obtained by optimizing the design, by boosting the current, using a high DC voltage, choosing a high-performance electrical steel and adapted permanent magnets, etc). For the PMSAFM topologies several configurations can be considered, and the authors show that a double rotor PMSAFM surface-mounted magnets
Lecointe, Jean-PhilippeHebri, MohamedBauw, GrégoryFawaz, SaraDuchesne, StéphaneZito, GianlucaABDELLI, AbdenourARSLANE, Idir
A design is presented for an electro-mechanical switchgear, intended for reconfiguring the windings of an electric machine whilst in operation. Specifically, the design is developed for integration onto an in-wheel automotive motor. The motor features 6 phase fractions, which can be reconfigured by the switchgear between series-star or parallel-star arrangements, thereby doubling the torque or speed range of the electric machine. The switchgear has a mass of only 1.8kg – around one tenth of the equivalent 2-speed transmission which might otherwise be employed to achieve a similar effect. As well as the extended operating envelope, the reconfigurable winding motor offers benefits in efficiency and power density. The mechanical solution presented is expected to achieve efficiency and cost advantages over equivalent semiconductor-based solutions, which are practical barriers to adoption in automotive applications. The design uses only mechanical contacts and a single actuator, thereby
Vagg, ChristopherThomas, LukePickering, SimonHerzog, MaticTrinchuk, DanyloRomih, Jaka
Combustion engines operating on a hydrogen-argon power cycle (H-APC) offer potential for superior thermal efficiency with true zero exhaust emissions. The high specific heat ratio of argon allows extrapolation of the theoretical efficiency of the Otto cycle to almost 90%. However, this potential is significantly constrained by challenges in combustion control, excessive thermal loading, and system integration, particularly regarding argon recovery. This study investigates these trade-offs, within the context of real-world engine-based peaking power plants. An experimentally validated 1D-simulation model of a prototype Wärtsilä 20 DF engine serves as reference for analysis of a retrofit incorporating a closed-loop argon cycle, with dedicated H₂ and O2 injectors, a water condenser and water separator. Engine performance is evaluated at reference operating point of 75% load, considering pre-ignition, peak pressure and exhaust temperature constraints, condenser limitations, and impurity
Ahammed, SajidAhmad, ZeeshanMahmoudzadeh Andwari, AminKakoee, AlirezaHyvonen, JariMikulski, Maciej
Additive manufacturing (AM) is no longer just an alternative to traditional manufacturing methods; it's a transformative shift in how parts are designed, built, and qualified. With AM, engineers can create complex internal geometries, lattice structures, and multi-functional components that simply were not possible with traditional manufacturing methods. The design freedom unlocked by AM is advantageous in the next generation of naval innovation, particularly as shipbuilding programs push to meet ambitious construction goals and improve warship readiness. For suppliers, embracing AM isn't just about swapping out tools; it's about rethinking the entire design process. Working to understand and prepare for AM-driven design and qualification changes is necessary to remain competitive in future U.S. Navy shipbuilding programs. This article will explain how new standards are driving qualification, supporting U.S. Navy construction goals and fleet readiness.
The multinational EPIIC programme, involving Airbus Defence and Space, is exploring multiple exciting innovations to strengthen Europe's defense capabilities and technological sovereignty. Airbus, Toulouse, France Imagine Tony Stark soaring through the skies in his iconic Iron Man suit, each command answered with a seamless blend of futuristic technology. Now imagine the cockpit of tomorrow's fighter jet.
Imagine being handed a device that’s meant to help you — but instead feels intimidating, confusing, or painful to use. For millions of patients around the world, that’s the reality of managing treatment at home. Across ailments, the burden of self-administered care is growing, and with it, the importance of designing drug-delivery systems designed with the patient experience at their core.
The transportation and mobility industry trend toward electrification is rapidly evolving and in this specific scenario, wind noise aeroacoustics becomes one of the major concerns for OEMs, as new propulsion systems are notably quieter than traditional ones. There is, however, very limited references available in the literature regarding validation of computational fluid dynamics (CFD) simulations applied to the prediction of aeroacoustics contribution to the noise generated by large commercial trucks. Thus, in this work, high-fidelity CFD simulations are performed using lattice Boltzmann method (LBM), which uses very large eddy simulation (VLES) turbulence model and compared to on-road physical tests of a heavy-duty truck to validate the approach. Furthermore, the effect of realistic wind conditions is also analyzed. Two different truck configurations are considered: one with side mirror (Case A) and the other without (Case B) side mirrors. The main focus of this work is to assess the
Guleria, AbhishekNovacek, JustinIhi, RafaelFougere, NicolasDasarathan, Devaraj
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