Browse Topic: Tools and equipment

Items (7,258)
Collaborative manufacturing networks enhance production efficiency but are increasingly vulnerable to cascading failures due to their complex interdependencies, particularly in critical processes like gear manufacturing. This study addresses this challenge by proposing a dynamic modelling framework based on Cellular Automata. Utilizing manufacturing resource and task scheduling data, a material flow-driven Directed Acyclic Graph (DAG) is constructed to capture the network’s hierarchical topology. Key innovations include state transition rules with memory effects, where dynamic failure probability integrates neighbouring node states and historical failure records, governing normal node failure, recovery, and re-failure (with an attenuation factor reflecting enhanced resilience). The case study focusing on the gear manufacturing industry, through simulations on a 100-node gear production network, reveals spatiotemporal failure propagation patterns. By implementing resource redundancy configuration and material flow optimization, iterations generally converge around 35 steps, demonstrating significant self-recovery potential and strong network robustness in collaborative manufacturing networks. This approach provides a scientifically grounded tool for identifying cascading risks in collaborative manufacturing networks.
Bai, HaoKou, ZhidaLiang, JingyaZhang, Cheng
In the process of replacing the rollers of the fabric cart of the tobacco storage cabinet, in order to solve the problems of low replacement efficiency and high safety risk.This article proposes a specialized lifting tool for fabric cart rollers with a self-locking and adopts the screw lifting structure, which facilitates roller maintenance operations, and conducts SolidWorks Simulation calculations and dynamic simulation methods. Jinan Cigarette Factory fine cigarettes special line leaf silk temporary storage cabinet fabric car roller replacement, for example, the results show that: the average operating personnel reduced by 50%, the replacement time from 6.7h to 1.2h, efficiency increased by 458%, This innovation significantly reduces the labor intensity of maintenance personnel and ensures a safe and reliable replacement process.
Zhang, LeiXue, YifeiZhang, GeSun, YanzhaoWang, HongbinCheng, Linfeng
The cutting machine is a critical component in the cigarette processing line, and its cutting quality depends on the operational condition of the copper bar chain. The grooves on the surface of the copper bar chain accumulate dust during the operation of the machine, which often causes unstable conveyance of raw materials, significant width variations, and a high defect rate. To address this issue, this study developed a linear reciprocating automatic cleaning system for copper bar chains to remove dust from the groove surface and hinge joints. Experiments have verified that the system improved the cutting qualification rate, increased the operational stability of the cutting machine, reduced manual cleaning workloads, and reached higher cleaning efficiency. This innovative system is also expected to provide a valuable reference for similar equipment manufacturers and advance technological innovation in the cigarette processing industry.
Li, HaitaoZhang, ChunyuanFang, JunqingSu, LinChen, PengGuo, ZhiweiXing, Dongdong
During root canal treatment, dentists must use endodontic access cavity preparation dental handpieces and root canal preparation handpieces separately for endodontic access cavity preparation and root canal preparation. To reduce the use of surgical tools, an integrated instrument for endodontic access cavity preparation and root canal preparation was designed. Driven by an air impeller and equipped with a quick tool disassembly unit, the instrument realizes forward or reverse rotation of the end tool via an STM32-controlled electromagnetic directional valve. The flow characteristics of the air impeller system were analyzed using ANSYS CFX, and the results showed that the impeller output torque met the design requirements. To minimize torque fluctuations during rotation, a double-layer offset impeller structure with an offset angle of 14° was designed based on the flow characteristics of the impeller system. The instrument was applied in simulated endodontic access cavity preparation and root canal preparation experiments. Preliminary experimental results demonstrate the feasibility of using this integrated instrument for both endodontic access cavity preparation and root canal preparation.
Chen, GuoliangXu, Kunlang
With the increasing demand for material microimaging analysis, there is a growing need for advanced precision grinding and polishing equipment, especially for metals, ceramics, and composites. Existing automated systems struggle with handling complex material challenges. This paper presents a fully automated adaptive grinding and polishing machine based on an STM32 microcontroller that handles multi-material samples. The system includes modules for sample access, cleaning, pad replacement, human-computer interaction, and equipment communication. The STM32 microcontroller executes grinding and polishing tasks based on instructions from the host computer while dynamically adjusting PID control parameters using an improved weighted average optimization algorithm. This approach enhances control accuracy, stability, and overall surface treatment quality compared to traditional PID control methods.
Zhang, LongqingKong, XiangyuZhao, XiuyangLi, Xingbei
The geometric error (GE) accounts for a significant factor affecting the machine tool’s machining accuracy, and in most cases, large GEs will result in a substantial deviation from the required shape of the machined workpiece. GEs are often observed in five-axis machine tools, and identifying and measuring these errors turns out to be challenging. In the present work, we proposed a novel GE identification approach based on simulations and tests conducted on a BC-type dual-rotary five-axis machine tool. Specifically, a machine tool volumetric error model (VEM), incorporating 41 GEs (the complete model), was constructed using the homogeneous coordinate transformation approach. Then, Sobol sensitivity analysis in conjunction with quasi-Monte Carlo estimation was introduced to the VEM to measure how much each GE contributed to the total volumetric error. The subsequent analysis identified 21 key geometric errors (KGEs). We also compared the simplified VEM and the complete model, and it was revealed that there was little difference between the two, which confirmed the effectiveness of our method. The present work is intended to provide a reference for simplifying VEMs, error element identification, and error compensation.
Zhang, JinlongShi, ZhaoyaoYang, Hongtao
This device belongs to the field of aviation materials technology and discloses a high-efficiency drilling equipment for manufacturing aviation materials, which includes a bottom plate. The top of the bottom plate is provided with a clamping structure and a positioning structure. The clamping structure includes a second moving plate, a third sliding groove, a second bi-directional screw, a fourth screw block, a clamping plate, and a rubber block. This device can hold materials through a clamping structure and effectively and quickly locate and drill holes through a positioning structure. By rotating the first threaded rod, it can drive the first screw block to move the U-shaped column. During the movement of the U-shaped column, it will drive the second threaded rod to move together. By rotating the second threaded rod, it will drive the second screw block to adjust the height of the connecting plate for drilling holes. By rotating the third threaded rod, it will drive the first moving plate to move, which will facilitate the multi-directional movement of the drill bit, improve the efficiency of drilling, avoid multiple position changes, and be beneficial for practical applications and operations.
Li, ZuxianLi, Ling
Desulfurization equipment in electric power industry is in a multi-field coupled corrosion environment with high temperature, high humidity, strong acid and solid-containing slurry. The annual direct economic loss of corrosion exceeds 5 billion yuan, and the equipment replacement cycle is only 1.5-2 years. Traditional protective coatings are difficult to meet the needs. The concept of “bionic barrier-intelligent response-in-situ purification” is proposed to construct multifunctional protective coatings: The Langmuir-Blodgett technique was used to alternately assemble MXene nanosheets and polysilazane. Ti-O-Si covalent bonds enhanced the interface bonding, resulting in a coating hardness of 4H and an elongation of 200%. After 1500 hours of extreme environment test, the coating has low weight loss rate, high self-repair and antibacterial rate, and its service life is extended by 8 times. The engineering application makes the maintenance period of desulfurization tower of a 660MW unit extended from 8 months to 6 years, saving 1.2 million yuan annually, and increasing 200,000 yuan annually by recovering H ˇ SO 2. It provides a cross-scale scheme for electric power corrosion protection.
Nie, PengfeiGao, JiangyuChen, Wei
Reliability evaluation aims to quantify the reliability level of equipment and to verify its compliance with reliability requirements. Existing reliability evaluation methods primarily rely on operational phase data, which means reliability evaluation may lag behind actual needs. In practice, both users and design teams are more concerned with how to estimate CNC machine tools’ reliability before they are put into operation. Moreover, current reliability evaluation methods usually ignore the design team’s influence on CNC machine tool reliability. To overcome these limitations, this study proposes a novel reliability evaluation method that accounts for the influence of the design team on the reliability of CNC machine tools. By analyzing the impact of the design team’s technical capabilities and reliability capabilities on CNC machine tool reliability, a set of quantifiable evaluation indicators was established. Then, the weight coefficients of all indicators were determined using the expert scoring method. Finally, all data were integrated using the vector projection method, which enabled a quantitative reliability evaluation of CNC machine tools from different design teams within the same category. Additionally, the proposed method was applied to conduct practical case studies on multiple CNC external cylindrical grinding machine tools designed by different design teams, thereby validating the feasibility of the proposed method. The reliability evaluation results not only determine the reliability level of each CNC machine tool but also identify the weak points in the technical capabilities and reliability competencies of each design team. This study concludes by discussing the significance of this approach for enhancing the reliability capabilities of design teams and its practical implications for end users.
Sun, DongyangZheng, WeixuChu, HongyanXu, JingjingCheng, Qiang
Crepe paper has extensive applications in the electrical field and significantly influences the operation of power equipment. The creping process and microstructure play a crucial role in determining its performance. However, optimizing them to improve the performance of crepe paper remains a challenge. Therefore, in this study, univariate and multi - factor interaction experiments were set up to explore the impact of the creping process on crepe paper. X - ray diffraction (XRD) and Fourier - transform infrared spectroscopy (FTIR) techniques were used to analyze the microstructure of crepe paper. The results show that smaller scraper angles and moderate pressures can increase the paper density, and the use of different creping aids can improve the paper’s performance. Higher crystallinity enables crepe paper to have better mechanical and thermal stability. Moreover, based on the experimental results, a scheme for optimizing process parameters was proposed to help improve the quality of domestic crepe paper and provide support for the development of domestic electrical crepe paper production technology.
Meng, GaoRan, ZhuoYuan, LaZengchao, WangBin, Zhang
With the continuous development of large precision equipment, the reliability requirement for long-distance transportation is also constantly increasing. Large packaging box with sealing and vibration reduction performance is crucial during transportation. This article introduces the sealing measures for large-sized packaging box, as well as the sealing structure design methods for key parts, vibration reduction measures and the selection and design of vibration dampers. The designed packaging box has been used for long-distance transportation of various types of equipment and the reliability of sealing and vibration reduction performance has been verified in practical applications, providing reference for the design of similar packaging boxes.
Zhang, RuoyuJiang, Shouli
The static-dynamic behaviors of ultra-precision five-axis machine tools are the core factors to ensure sub-micron-level machining accuracy. This study establishes a detailed finite element model of an entire machine based on the ANSYS Workbench platform and conducts in-depth research on the static-dynamic characteristics of the entire machine of the ultra-precision five-axis machining center by using the finite element analysis(FEM) method and combining the principles of statics and dynamics. By constructing an accurate finite element model, the stress distribution, deformation, and modal vibration characteristics of the entire machine, especially the key parts, such as spindle box, crossbeam, column, and guide rails, under complex loads such as gravity and cutting force are simulated. The static analysis reveals a maximum deformation of 0.17 mm in the spindle box and the column, and the maximum stress is 58 MPa (at the Z-direction guide rail contact point), which is lower than the allowable stress of Q215 steel (195.5 MPa). The modal analysis extracts the first six natural frequencies (50.683 - 175.91 Hz), and the low-order vibration modes are mainly the Y/X-direction swing of the column, revealing the weak stiffness links. Based on the analysis results, a parametric optimization method was further adopted to optimize the structure of the weak components: the base, the column and the spindle box. This significantly enhanced the overall stiffness, reducing the maximum deformation to 0.039 mm and the maximum stress to 45MPa. The first six natural frequencies were all greatly increased (the first one reaching 85.548Hz). These findings provide valuable insights for machine tool structural enhancement and performance optimization.
Li, ShanSohi, Seyed Hamed Hashemi
The desulfurization and denitrification tower is the core equipment of the carbon-based catalytic multi-pollutant synergistic control technology. Its design strength ensures the system’s pollutant removal efficiency and stable operation. This study utilized ANSYS finite element analysis software to establish a three-dimensional model of the tower and divide high-precision grids. Combined with the load analysis, calculation and work condition analysis under actual conditions, the deformation and stress distribution of the tower body, as well as the film stress and bending stress of each component, were calculated, and strength verification and stress assessment were conducted. When ignoring the calculation error, the overall design strength of the tower body meets the requirements, but the local reinforced beam stress exceeds the limit, so it is recommended to replace the steel with a material with a higher allowable stress value.
Gu, JiangongWu, LinlinShi, LinaHu, YifanCheng, WenyuLiu, YiningSun, LeiWu, JiayuLuo, ZhengJiao, Lingyu
This study carefully designed and successfully developed a mechanical voltage stabilizing control device. The device uses silicone oil as the key component material of the liquid spring and 1Cr13 as the main material of the pressure control unit, enhancing its high-pressure resistance (up to 35 MPa), oxidation resistance, and acid-alkali corrosion resistance. By optimizing the transmission mechanism and simplifying the pressure regulation module, the device achieves a pressure regulation range of 0.1–21 MPa with an accuracy of ±0.01 MPa, significantly broader and more precise than traditional devices. To address manufacturing challenges, advanced CNC machine tools, ceramic cutting tools, and optimized heat treatment processes (e.g., quenching and tempering) were adopted, ensuring component machining accuracy within ±0.02 mm. Field applications in 13 oil wells demonstrated a 15.6% increase in daily oil production (from 25.5 t/d to 29.5 t/d) and a 17.9% increase in daily gas production (from 2800 m^3/d to 3300 m^3/d), with stable casing pressure control at 5.3 MPa. The device has created 1.225 million yuan in economic benefits while eliminating safety hazards, providing critical technical support for efficient and environmentally friendly oil and gas production.
Wang, GangLiu, CuicuiTong, DeshuiCao, JianMu, TaijiHan, Baidong
Lunar dust consists of extremely fine particles and exhibits electrostatic charging properties and electrostatic adhesion. These characteristics cause lunar dust to be highly susceptible to mobilization during lander touchdowns, rover traversals, and human activities, forming widely distributed dust clouds. Lunar dust contamination not only abrades spacecraft and equipment to impair their performance but also poses a threat to astronauts’ safety. To verify the impact of the lunar dust environment on exploration equipment components, a simulation mechanism adaptable to the thermal vacuum test environment was designed. This mechanism is integrated into the lunar environment simulation system and uses a vacuum stepper motor to drive a ratchet mechanism, enabling precise vibrational injection of simulated lunar dust. It mainly consists of a pretreatment mechanism, a particle sedimentation mechanism, a shielding mechanism, and an ultraviolet (UV) irradiation system. Considering the vacuum operating environment, alternating high and low temperature conditions, as well as the strict requirements for the mechanism’s compact size and high reliability, this paper analyzes in detail a series of problems encountered during the development of the mechanism and their corresponding solutions. Stainless steel and polytetrafluoroethylene (PTFE) were selected as the main materials for the mechanism. Meanwhile, active temperature control measures were adopted to actively regulate the temperature of components such as the motor. Ultimately, the mechanism can withstand alternating high and low temperatures ranging from -150°C to 150°C and a vacuum environment of 5 × 10^–6 Pa. Under this environment, the mechanism can achieve vibration frequency adjustment within the range of 1-5 Hz, and realize the sedimentation of simulated lunar dust particles with a particle size of less than 200 μm over an area of 150 mm × 150 mm. After sedimentation, the simulated lunar dust particles can be charged through the photoelectric effect.
Xu, MenglongLv, ShizengLi, GuohuaGong, Jie
In port construction, high-pile wharves—a primary structural form—are constantly exposed to marine environmental erosion, making corrosion a particularly prominent issue. Traditional anode installation typically relies on underwater diving operations, which suffer from low efficiency, high risks, and significant costs. To address these challenges, a novel installation technique requiring no divers has been developed. Through specialized equipment design and optimized construction processes, this technology enables remote, efficient, and safe anode installation. Research focuses on the design of non-diver anode support installation equipment, safety validation, and construction methodologies. Through theoretical analysis, numerical simulation, and field construction trials, this technology significantly enhances construction efficiency while reducing operational risks and costs. It provides a reliable solution for corrosion protection in high-pile wharves and holds significant importance for advancing port construction technology.
Lan, JinpingZhang, Shoulong
Precisely detecting multi-stage degradation (MD) in rolling bearings is crucial for keeping equipment in good shape. Yet, health indicator (HI) crafted with current single-method strategies often can't balance degradation sensitivity and monotonicity across different operating conditions. Also, common MD detection methods struggle to spotransitional samples between degradation stages in cross-condition settings. To tackle these challenges, this paper introduces a new cross-condition MD detection approach for bearings, which relies on a health indicator matrix (HIM) and a transition sample enhanced network with multi-branch encoding (TSEN-MBE). First, a degradation-sensitive health indicator (DSHI) is constructed by integrating the least absolute shrinkage and selection operator (LASSO) algorithm — with comprehensive fault frequency energy (CFFE) as the regression target — and the grey wolf optimizer (GWO), capturing intrinsic degradation characteristics of bearings. Meanwhile, to enhance the monotonicity of unsupervised HIs, a time-weighted Wasserstein distance (TWWD) metric is proposed by incorporating temporal degradation features into the Wasserstein distance-based HI construction. The DSHI and TWWD are subsequently combined to generate the HIM. This HIM serves as the driving force for the Gath-Geva (GG) fuzzy clustering algorithm, enabling it to adaptively allocate MD labels according to varying operating conditions. Ultimately, the TSEN-MBE model is constructed, employing multi-branch Transformer encoders integrated with multi-head attention mechanisms to encode and combine heterogeneous features. A joint loss (JL) function — comprising transition sample enhancement (TSE), local maximum mean discrepancy (LMMD), and cross-entropy (CE) losses — is designed to enhance the recognition of transitional samples and improve cross-condition MD identification accuracy. Experimental results on the XJTU-SY dataset validate the effectiveness and superiority of the proposed method, showing that DSHI achieves the highest average degradation angles, TWWD obtains optimal monotonicity, and TSEN-MBE outperforms comparative methods in cross-condition recognition tasks.
Ma, JinghuaWei, LaiHu, GuangqiaoYu, Xiaoxia
Drill string whirl and buckling cause impact-rub contact against the casing inner wall, which induces casing wear and threatens wellbore integrity. This study incorporates both whirl and buckling to analyze the wear mechanism. Finite-element dynamic models are established for three drill string states: stable unbuckled, sinusoidally buckled, and helically buckled. Transient dynamic simulations are performed in the ANSYS Workbench Transient Structural module to obtain whirl trajectories, contact pressures, and contact characteristics at multiple sections along the string. A casing-wear volume calculation based on the Kumar–Samuel formulation with time-varying contact pressure is then used to quantify wear at the lower drill collar, the upper stabilizer, the upper drill collar, the heavyweight drill string, and the buckled segment. Results show that once buckling occurs, whirl concentrates in the bottom-hole assembly and decays progressively from the bottom of the well toward the wellhead. Casing wear increases across all locations, with the largest increments at the lower drill-collar interval and within the buckled segment. Helical buckling produces greater casing wear than sinusoidal buckling. Neglecting drill string buckling, especially helical buckling, leads to underestimation of casing wear and thus underestimation of wellbore-integrity risk.
Liu, JunlinCao, GenpeiWan, ZhiguoYang, ZhengLi, LongDou, YihuaGu, Runpeng
In order to achieve precise control of refueling volume, improve oil change efficiency, reduce oil pollution and waste, a new oil change device for the reducer of the range hood equipment is studied. We design a new oil change device that integrates oil discharge and refueling functions based on the operating characteristics of the reducer in the range hood equipment. Using the rotational speed of the power pump and the flow rate of the oil pipeline as variables, we determine the refueling flow rate using a one-dimensional quadratic formula. Based on direct control theory, we optimize the relative position parameters of each component of the device, establish a control matrix, and achieve precise control. The experimental results show that the new oil change device exhibits good performance during both one-time oil discharge and refueling processes, meeting the precise control standards for refueling volume. The design and application of a new oil change device can effectively improve the efficiency and accuracy of oil change in the reducer of the range hood equipment, and have practical application value.
He, PengtaoWei, BoLiang, ZhiyuanDeng, WeirenLiang, WenbinXing, Yuquan
Civil aircraft, as typical complex product systems, exhibit characteristics such as a high concentration of high-tech technologies, strong interdisciplinarity, a high level of system integration, long development cycles, substantial project investments, and complex management. During the R&D process of civil aircraft projects, there are often high risks in performance, cost, and schedule. Delays in the schedule can lead to losses in project manpower and material resources, as well as project failure. A mature objective criteria system for maturity assessment provides a reference basis for determining whether the project has reached its optimal state at a specific stage, thereby reducing project management risks and increasing the probability of project success. This research will adopt a research approach combining theoretical studies with practical case analysis. First, it will conduct extensive and in-depth investigations into various maturity models and their applications across the entire product lifecycle within relevant fields. A requirement maturity model and requirement maturity KPI (Key Performance Indicator) indicators will be established to clarify the maturity status of requirements at different development stages, enabling judgment of whether the project is ready to proceed to the next development phase. Concurrently, by developing a KPI statistical system platform integrating application servers and data processing tools, a scientific and quantitative inspection mechanism will be implemented to visualize project development progress, status, and risk data. This will provide actionable insights for project decision-making and achieve effective project management and control.
Wang, YiHuang, JunkaiZhang, Xinyu
This work aims to investigate how disturbance-aware, robustness-embedding reference trajectories translate into actual driving performance when executed by professional drivers in a dynamic driving simulator. The study compares three planned reference trajectories against a free-driving baseline (NO-REF) to assess the trade-offs between lap time (LT) performance and steering effort: NOM, the nominal time-optimal trajectory; TLC, a track-limit-robust, time-optimal trajectory obtained by tightening margins to the track edges; and FLC, a friction-limit-robust, time-optimal trajectory obtained by tightening against axle/tire saturation. All reference trajectories share the same minimum LT objective with a small steering-smoothness regularizer, and are evaluated with two professional drivers driving a high-performance car on a virtual track. The reference trajectories stem from a disturbance-aware minimum-LT framework recently proposed by some of the authors, where worst-case disturbance growth is propagated over a finite horizon and used to tighten tire-friction and track-limit constraints, preserving performance while delivering probabilistic safety margins. LT and steering energy (SE) are evaluated as indicators of driving performance and steering effort, respectively, while RMS values of lateral deviation, speed error, and drift angle are used to characterize driving style. The results reveal a Pareto-like trade-off between LT and SE: NOM achieves the shortest LT, but with the highest SE, TLC minimizes SE at the expense of longer LT, while FLC lies near the efficient frontier, markedly reducing SE relative to NOM with only a minor LT increase. Removing reference trajectories (NO-REF) leads to both higher SE and longer LT, confirming that trajectory guidance improves pace and control efficiency. Overall, the findings highlight reference-based and disturbance-aware planning, particularly the FLC variant, as effective tools for training and for achieving fast yet stable trajectories.
Masoni, MatteoPalermo, VincenzoGabiccini, MarcoGulisano, MartinoPreviati, GiorgioGobbi, MassimilianoComolli, FrancescoMastinu, GianpieroGuiggiani, Massimo
The gearbox is a key component of the mechanical transmission system, and its fault diagnosis is essential to the reliability of the equipment. However, obtaining fault samples under actual working conditions for gearbox fault diagnosis is challenging. In this paper, the rigid-flexible coupling dynamic simulation model of the gearbox is established, and the co-simulation of gear normal, crack, and breakage is carried out in the ADAMS and MATLAB environments. The comparison between the simulated and measured signals shows that the simulation method can accurately reflect the key characteristics, such as rotation frequency and meshing frequency, and verify its reliability and accuracy. The research results can provide effective data support for gearbox fault diagnosis and improve the operational safety of mechanical systems.
Li, DongxiaoZhang, QianqiZhang, ZhongzhengLi, Yongbo
Electrification using battery systems is one of the most relevant solutions regarding ecological challenges within multiple application cases such as mobility, power tools or stationary power supply. Nonetheless besides recent achievements in some cases battery systems are still lacking behind operational requirements compared to conventional propulsion systems, therefore limiting the potential of electrification. Especially when purpose design possibilities are limited. Besides improving properties of cell materials, better usage of the available installation space offers potential for optimization of the battery system. The development of battery systems is complex, as it involves multiple system levels and domains, along with a wide range of design options and architectures. Battery cells that can be manufactured in flexible formats enable possibilities to make more efficient use of available installation spaces. At the same time, these additional degrees of freedom increase design complexity and significantly expand the solution space. For example, numerous options for sizing and positioning of the cells are available that are interacting with the cooling system and housing design. Also, additional challenges regarding electrical and thermal load distribution occur using format flexible cells. To support developers, new methods and tools are necessary to handle this complexity. Therefore, the authors present a methodology that includes an installation space optimization using format-flexibly produced pouch cells that generates different possible layouts of cells and modules, an approach for electrical and thermal modeling of the battery system that is applicable for varying cell arrangements as well as possibilities for a fast criteria-based evaluation of different cell and module arrangements that can be used for an overall optimization of the battery system. Finally, the authors are discussing benefits and disadvantages of the presented methodology as well as the usage of format flexibly produced pouch cells using an illustrative case study.
Müller-Welt, PhilipBause, KatharinaSpohn, HannesAlbers, Albert
Current lithium-ion batteries should generally only be charged above 0 °C, as charging below this temperature can promote lithium plating and irreversible degradation. However, conventional pack-level heating elements increase system mass and design complexity. In addition, heat is transferred from outside into the cell, causing the temperature inside the cell to rise slowly. This study evaluates internal Joule heating of cylindrical Li-ion cells using a zero-mean square-wave current excitation and quantifies the associated aging impact. LG INR21700-M50L cells were tested at 0 °C, −10 °C, and −20 °C with three excitation frequencies (50 Hz, 1 Hz, 10 mHz) at 5 A amplitude. Each cycle consisted of 30 min heating followed by 60 min cooling; reference capacity-based state of health (SOH) was assessed every 50 cycles up to 400 cycles. A maximum surface temperature rise of 14.3 K was achieved, with larger temperature rise at lower ambient temperature and lower excitation frequency. Capacity fade remained below approximately 1% for most conditions; however, at −20 °C and 10 mHz a pronounced SOH decrease to 87% was observed, indicating a critical operating regime. The results provide practical guidance for pulse-heating parameter selection and highlight the need for safeguards and further diagnostics in extreme low-frequency excitation at very low temperatures. This heating approach is particularly suitable for simpler battery-electric applications without thermal management, such as e-bikes or power tools. However, it may also be relevant for applications with existing thermal management systems, as it simplifies battery pack design.
Raiber, StefanAllmendinger, FrankDegler, DavidParschau, Anke
This work presents the development of a user-oriented software tool for the cradle-to-grave Life Cycle Assessment (LCA) of passenger cars, enabling robust comparisons of greenhouse gas emissions across heterogeneous vehicle configurations. The tool supports informed decision-making by quantifying and visualizing environmental impacts associated with alternative mobility choices over the full vehicle life cycle, including production, use, maintenance, and end-of-life stages. The proposed framework allows key parameters describing both the vehicle and its usage to be explicitly defined, including powertrain type, dimensions and weight, ownership profile (new or second-hand vehicles, partial ownership periods, leasing scenarios), annual mileage, vehicle lifetime assumptions, and the carbon intensity of fuels or electricity sources. Country-specific energy mixes are incorporated, enabling the same vehicle to be assessed under different geographic contexts and highlighting the strong dependence of use-phase emissions on local energy systems. Results are reported both as total life-cycle emissions and as a phase-resolved breakdown, improving transparency and supporting a clear interpretation of trade-offs between production, operation, maintenance, and end-of-life stages. Representative scenarios demonstrate that, under a standard European context, battery electric vehicles (BEVs) achieve a reduction of approximately 32% in yearly greenhouse gas emissions compared to a baseline Euro 5 gasoline vehicle. However, this trend reverses for low-mileage users relying on second-hand vehicles, for which emissions can increase by about 15%, emphasizing the critical role of usage patterns and ownership strategies in determining environmental benefits. The tool is designed to accommodate updated datasets, emission factors, and evolving energy scenarios, ensuring long-term applicability and enabling forward-looking analyses. Its capabilities are demonstrated across scenarios covering short- and long-term usage, multiple national contexts, and different powertrain technologies. The result is a robust and transparent assessment platform that enables users and policymakers to evaluate vehicle replacement strategies, providing quantitative insights into the interplay between technology, usage, and sustainability in mobility transitions.
Gastaldi, ChiaraCibrario, Luca
This novel method deals with emulation of Strain of a Structural Measurement System which includes software validation, acceptance tests and training. Current methods for simulating strain and force data for developing and verifying data acquisition (DAQ) software typically rely on costly electronic simulators or specialized hardware, making it challenging and expensive for developers, researchers, and small organizations to test their solutions under realistic conditions. To verify DAQ software, multiple specialized hardware solutions are deployed, that include Electronic Simulators, Commercial DAQ Modules and Hydraulic/Pneumatic test rigs. These technologies pose a challenge with limited flexibility and scalability options for small-scale prototyping, especially in budget-constrained scenarios. The sensors on these equipment may or may not be company approved inducing acceptance challenges. Our invention is an inexpensive, scalable, and mechanically simple alternative. Using a 3D-printed structure combined with standard cantilever load cells and easily accessible weights, it enables realistic and customizable strain simulations without the need for expensive electronic simulation equipment. All platforms namely NI based, Dewesoft, VTI and others can be integrated into a unified test framework in this method which otherwise needs to be simulated on suitable equipment individually.
Murthy, HarshaBhat Venkatesh, AditiK Padmanabhan, RahulMadhu, SheetalGarag, Naveen
As aerospace platforms adopt increasingly interconnected architectures for avionics, telemetry, and predictive diagnostics, lightweight publish–subscribe protocols have become integral to communication efficiency. The Message Queuing Telemetry Transport (MQTT) protocol is widely employed due to its small footprint and low network overhead. The release of MQTT 5.0 introduces new control features—reason codes, session expiry, user properties, topic aliasing, shared subscriptions, and improved error feedback—aimed at enhancing scalability and diagnostic reliability. However, these benefits come with trade-offs in complexity and potential overhead, particularly in real-time and resource-constrained environments typical in aerospace. This paper evaluates MQTT 3.1 and MQTT 5.0 within aerospace IoT contexts using a Raspberry Pi–based experimental framework. The analysis is done using practical throughput benchmarks implemented via popular open-source tools like Eclipse Mosquitto Clients. Realistic aerospace communication scenarios are modeled for inter-module messaging, under varying QoS levels and payload conditions. Comparative throughput, latency, and broker resource utilization benchmarks were conducted under multiple QoS levels and payload sizes to quantify the trade-offs between functionality and efficiency. This research aims to empirically validate the theoretical improvements of MQTT 5.0 on realistic embedded hardware and under controlled network constraints, replicating operational aerospace environments. Results show that MQTT 5.0 provides measurable advantages in complex, multi-tenant environments but introduces moderate processing overhead. Recommendations are proposed for selecting the optimal MQTT version for aerospace deployments and strategies for seamless migration from legacy systems [8].
Bhuyar, PrabhudevM, MeghanaKaniraja, ChristinaThomas, Tinto
Researchers discover texts, phone calls, military communication, internal corporate networks all easily eavesdropped on using off-the-shelf equipment. University of California San Diego, La Jolla, CA With $800 of off-the-shelf equipment and months' worth of patience, a team of U.S. computer scientists set out to find out how well geostationary satellite communications are encrypted. And what they found was shocking. Close to half of the communications beamed from satellites to the ground that the researchers were able to listen in on were not encrypted. This included sensitive data including cellular text messages, voice calls, as well as sensitive military information, data from internal corporate and bank networks, and the in-flight online activity of airline passengers.
To enhance the economic efficiency and operational security of distribution grids, this paper develops a reactive power optimization model that incorporates distributed power sources. The model aims to minimize the costs of reactive-load compensation equipment, reduce voltage deviations, and lower network losses while satisfying operational constraints. To overcome the common drawbacks of the standard genetic algorithm—such as limited optimization precision and a tendency to converge to local optima—four improvement strategies are introduced. These include an enhanced encoding scheme, an initial population generated via opposition-based learning, an elite retention strategy, and the adaptive adjustment of crossover and mutation rates. Together, these modifications strengthen the algorithm’s global search capability. The proposed approach is validated using the IEEE30 node system. Compared with both the conventional genetic algorithm (GA) and an adaptive genetic algorithm, the improved method demonstrates faster convergence and a more robust ability to escape local optima. Simulation results indicate that the suggested algorithm effectively reduces voltage fluctuations and power losses in the network while improving the overall cost-efficiency of grid operation.
Wang, MaozeXiao, WenyuLiu, YujiaXu, ZhengweiXia, Yinyong
Causal discovery within time series is crucial for revealing the actual causal mechanisms in dynamic systems, and it has major impacts in various fields like economics, healthcare, and climate science. Even though it’s important, accurately figuring out causal relationships from observational temporal data is still quite a difficult task. Traditional Granger causality based methods are often limited by noise sensitivity, large amount of data, and the inability to distinguish between real causality and false correlation caused by hidden factors. In order to solve these problems, this paper presents CausalAugVeri, which is a new algorithm that cleverly mixes data augmentation with causal verification to make causal discovery more solid and precise. This work has three main points: First, we carefully check that using convolutional data augmentation techniques can greatly improve how well time series predictions work, giving a steadier base for detecting Granger causality. Second, the suggested method rebuilds cause variables using specific intervention ways and adds a causal verification part that strictly removes wrong findings, keeping only real causal connections. Third, we do thorough experiments on both made-up and real-world time series datasets, showing that CausalAugVeri always does better than current top methods, particularly when there’s little data and lots of noise. The results prove that our way gives a dependable and expandable answer for causal discovery in complicated time-related situations, connecting the gap between augmentation based on deep learning and traditional causality analysis. This study not only gives a methodologically strong structure but also offers practical tools for real-world uses that need sturdy causal understanding.
Yang, JingChen, XiaotaoQin, XuanliXu, XianjunHu, Zhangxiang
This article focuses on the problem of high labor cost, low processing efficiency and poor automation of the existing equipment in the postharvest processing of Chinese cabbage. It will design and produce an automated Chinese cabbage processing method called Smart Fresh Pack. Root removal, leaf removal, washing, loading, weighing, packaging and labeling functions were integrated, and smart dexterous intelligence was applied to core concepts and this can be used in the bulk production scenario of supermarkets in the city and countryside Compared with traditional assembly line equipment, obvious advantages in terms of structure, function and processing capacity: Key innovations include: Low-pressure air jet cleaning replaces water washing, which prevents a second contamination and weighing error due to surface moisture; pneumatic gripper and multi-DOF robotic arms combine to package and dynamically weigh simultaneously, streamlining these tasks; machine vision relies on an SSD-MobileNetV2 visual model with Sobel edge detection to locate and identify wilted leaves; and pairing with a multi-threaded control structure for millisecond level closed-loop response. I used Fischertechnik models to build and simulate, checking whether the motion logic of this design is reasonable, whether the stresses are safe, and whether the airflow cleaning is effective. This machine finishes the complete processing of one cabbage just within one minute, its modular and its maintainance and scalability aspects are also there, it gives small and medium size agricultural entities a low cost but also very effective clean vegetable processing route, this is truly good for making progress with the auto, standard and green developments within agric prd processing.
Chen, YuhuiZhang, YixuanRuan, JiaZhu, HuayunHe, LianzhengZhao, Ping
When simulating spray atomization process involving VOF method, a core problem is the conflict between high grid detail and limited computer power. Although VOF and DPM methods have recently been coupled to reduce computational cost, their application in practical engineering calculations still imposes a considerable computational burden. To solve this, a better adaptive mesh refinement (AMR) plan is put forward. This plan uses a 0.2 mm initial grid (twice the usual 0.1mm) and allows refinement up to four levels. This improved technique makes high computational efficiency for large-scale simulations. Two types of nozzles are employed to evaluate the proposed method. However, for circular nozzles, the new method does not increase calculation speed, while lowers the accuracy of the simulation.In contrast, for square nozzles, it greatly boosts computation speed and keeping high accuracy. This makes the technique a useful tool for modeling transverse jet atomization in industry. Overall, the work gives clear advice for better mesh refinement in multiphase flow research. It is particularly advantageous for large-scale simulation domains where conventional methods become computationally prohibitive.
Zhou, TaotaoMa, MingZhang, HaitaoZhang, FenganChen, XianhuiChen, QiXia, Hongwei
Causal inference from observational data, particularly the estimation of a treatment’s causal effect on an outcome, has long been challenging, primarily because it hinges on correctly identifying confounders. This is typically accomplished in two main ways within causal inference frameworks: either by using causal discovery algorithms to recover the underlying causal structure through a causal graph, or by assuming that the relevant confounders are already known. Both approaches have been shown to be unreliable or simply infeasible in practical applications. Although large language models (LLMs) are advancing rapidly, their emerging capabilities in causal inference have only recently begun to receive significant attention. Nevertheless, LLMs currently lack the ability to directly interpret structured tabular data, which is widely used in causal inference. To address this limitation, we introduce a novel framework, CauExecutor, for causal inference. Our framework enables a novel combination of the semantic reasoning strength of LLM with the accurate estimation capacity of off-the-shelf statistical tools to more accurately estimate the causal effect from observational structured data. The CauExecutor first uses the semantic understanding and the reasoning power of LLMs to help find potential mediators and separate them from the confounders. It subsequently leverages off-the-shelf tools to programmatically handle tabular data and estimate causal effects by the optimized adjustment set. On several benchmark datasets, we observe CauExecutor outperforms all other LLM-based methods by correctly identifying more mediators and producing more accurate causal effect estimates. Additional experiments show that CauExecutor’s decision to disqualify mediators from the adjustment set, rather than qualifying any variable that meets the backdoor criterion, is beneficial to successfully minimizing mediator-induced bias and attaining improved estimation performance.
Yang, JiaoyunChen, JinxiYin, YueLiu, LiLi, LianAn, Ning
Metal-elastomer bonded components can suffer from manufacturing defects such as porosity and bond-line voids. Nondestructive evaluation (NDE) methods can replace or supplement existing destructive tests; however, implementation can be challenging for manufacturers due to the initial equipment cost, time required per test, and imaging quality. These criteria were used to evaluate shearography, high-resolution ultrasound testing (UT), 2D projection X-ray, computed tomography (CT), and acoustic emission (AE) testing, culminating in trade studies for different sample part types. Experimental work was performed on three samples of varying geometries and sizes with seeded defects, applying feasible NDE methods to each. Shearography succeeded in detecting void defects and flow fronts. X-ray and CT failed to detect flaws in 2 out of 3 part types due to energy and time constraints. UT could not reliably detect defects in parts with complex geometries because of scatter. Acoustic emission reliably detected a seeded knit-line defect.
Mullin, HollyGodinez-Azcuaga, ValeryHobart, AndersonPearson, JohnVadella, RobbieMoose, ClarkSmith, Edward
The impact of ship airwake on helicopter operations to rear flight decks has been a topic of much research over the past three decades. While generic ships have been developed over the years to enable analysis tool and knowledge development, actual ships can vary significantly, resulting in different airwake features. The study of variations in ship geometry is important both to understand how differences may impact operations, but also to understand the level of geometrical fidelity that is required on ship models undergoing analysis. In Canada, the newly launched (2018) Harry DeWolf-class Arctic Offshore Patrol Ships (AOPS) have unique features that have been studied for their impact on airwake characteristics. This paper explores different geometrical characteristics from the perspective of their operational impacts and also considering their importance for inclusion in simulation. The paper shows that turbulence level is the parameter most affected by the minor variations that were examined, and helps guide the inclusion or exclusion of details in future ship models.
Wall, AlannaLee, RichardSideroff, ChrisYuan, Weixing
Meta-wheels—non-pneumatic wheels whose performance is governed by structural geometry rather than internal pressure—offer new opportunities for directional stiffness control. Yet achieving independent tuning of longitudinal, lateral, and vertical stiffness within a single wheel architecture has remained challenging due to the inherent coupling in conventional radial and planar curved spokes. In this study, we introduce a three-dimensional (3D) discrete curved-spoke design that provides explicit geometric control through two independent parameters: the in-plane curvature angle (α) and the out-of-plane inclination angle (β). Using spoke-level and full-wheel finite-element (FE) simulations, supported by a simplified cantilever-beam analytical model, we show that these two geometric parameters govern stiffness in fundamentally different ways. The curvature angle α serves primarily as a geometric softener, reducing stiffness in all directions while maintaining a high top-loading ratio (TLR) (>92%). In contrast, the inclination angle β enables true directional stiffness decoupling: increasing β substantially raises longitudinal stiffness and decreases lateral stiffness, while leaving vertical stiffness nearly unchanged (≈1.4% variation). Compared with conventional two-dimensional (2D) spoke designs, the proposed 3D architecture achieves stiffness characteristics approaching those of pneumatic tires, particularly higher longitudinal stiffness and lower lateral stiffness, without sacrificing vertical load-bearing capacity. Moreover, the combined simulation–analysis framework provides an efficient early-stage screening tool by mapping desired stiffness ratios directly to geometric parameters, narrowing the feasible design space before full-wheel FE verification. Overall, this work demonstrates that 3D discrete curved spokes present a practical and interpretable route toward stiffness-decoupled, directionally programmable meta-wheels for next-generation mobility platforms.
Han, HeeseungLiu, ZhipengJu, Jaehyung
In the stringent market of BEV, the development of integrated Drive Modules (iDM) fitting environmental and customer needs is mandatory. It is important to extract the best from the less. To achieve those goals, a deep insight into complex multiphysics phenomena occurring in an iDM has been achieved by accurate and validated models. This engineering methodology is applied through the development of BorgWarner products, comprising non-exhaustively iDM 180-HF, Externally Excited Synchronous Machine and Multi-Level Inverter. The paper will review the methodology development for deeper understanding involving in-house technical excellence and complemented by strategic partnerships with academic institutions and start-ups. It will present the approach of integrating advanced multiphysics models with high-quality experimental validations, specifically on loss evaluation on electrical machines and inverters. Complex models involving multiphysics such as thermal/fluid coupling or electric-magnetic-mechanical behaviors are usually difficult to optimize separately since their objectives are often contradictory. Thus, BorgWarner PDS Engineering uses tools involving close coupling to optimize iDM products. The lecture will focus on innovation and optimization which are supported by several key pillars in the scope of a Next Generation iDM development. These are based on the following strategic levers such as process and design development, material development and control strategy among others. This ensures tailoring all components at the best of their capabilities to reduce their weight and maximize their use. Finally, the results achieved by the high-fidelity model-based optimization on the selected example will be presented (e.g., impact of the cooling improvement on overall iDM performances), demonstrating the benefit of capturing the system from granular view to a helicopter view in the design phase of next generation eDrives.
Leblay, ArnaudBourniche, EricBossi, AdrienDavid, PascalNanjundaswamy, Harsha
The present study investigates optimization of ultimate tensile strength (UTS) in FSW of AA2024-T3 and SS304 in a butt joint configuration. An L18 mixed-level orthogonal array was used to design 18 experiments, varying tool rotational speed (450, 560, and 710 rpm), traverse speed (20, 25, and 40 mm/min), and pin offset (1 and 1.5 mm toward the Al side). The tool rotational speed had the greatest influence on UTS, contributing nearly one-third of the total variance, followed by pin offset and traverse speed. The optimal combination, 450 rpm, 20 mm/min, 1.5 mm offset, yielded a UTS of 344.7 MPa and a joint efficiency of 78.3%. At this setting, peak temperatures reached ~356 °C, ensuring sufficient plasticization and uniform mixing of the Al–SS interface, producing a refined stir zone with an average grain size of 4.2 μm. Fracture analysis revealed ductile failure at the optimal parameters, whereas suboptimal conditions resulted in brittle or mixed fractures due to either insufficient or excessive heat input. These results demonstrate that Taguchi optimization effectively correlates process parameters, thermal profile, material mixing, and mechanical performance, enabling reliable, defect-free dissimilar FSW joints for structural and aerospace applications.
Mir, Fayaz AhmadKhan, Noor ZamanPali, Harveer Singh
This work presents two approaches for weld optimization aimed at reducing manufacturing cost and process time, while meeting structural performance requirements in automotive structures. The first approach uses topology optimization to identify the most efficient weld layouts. A design space is generated along mating flanges, joints, and panel interfaces, where potential weld locations are defined. Welds are treated as discrete design variables, and the topology optimization systematically evaluates their contribution to global stiffness and load path integrity. Non-critical welds, those with minimal impact on stiffness, durability, or crashworthiness, are eliminated, resulting in a minimized weld pattern that maintains structural performance. The second approach applies Multi-Disciplinary Optimization (MDO) to balance weld reduction with performance targets across multiple domains, including linear and non-linear stiffness, crashworthiness, and fatigue. Using a preprocessing tool, welds are parameterized to allow flexible control of their placement. A Design of Experiments (DoE) is generated to simulate various weld configurations under relevant load cases. Surrogate models are then developed to approximate the relationship between weld layout and key performance metrics. These response surfaces enable efficient optimization that minimizes weld count while satisfying all structural requirements. Together, these strategies form a data-driven, simulation-based framework for weld design that supports aggressive cost and time reduction targets without compromising safety or durability. The results demonstrate the potential for integrating advanced optimization techniques into early design phases for more efficient and manufacturable vehicle structures.
Koppaka, VinayaYoo, Dong YeonChavare, Sudeep
The useability of development processes in the automotive sector has decreased in the past years to a level at which their application and true benefit to is being questioned. Such degradation can be attributed to new additions to the processes and introduction of FuSa and Cybersecurity standards. The processes try to keep up with the shift from the traditional ‘plan–implement–test–roll-out' methodology to more agile methods. In addition, process departments typically in charge of these processes, focus on compliance to the letter of the standard to achieve certification, often with little thought to the actual implementation and the process they will be used by their engineering teams. Process growth to meet the needs of new and more complex technologies often mandates the use of new tools, which if implemented incorrectly can lead to unnecessary bureaucracy and additional overheads. Furthermore, the language of these new processes is in a form from assessor, making it difficult for an engineer to understand, interpret and implement. As a result, engineers become annoyed, losing productivity and motivation when working with what they perceive as burdensome standards, that simply exist to slow development. This has a huge impact on the competitiveness of companies especially in markets that are facing existential threats from internal and external pressures such as the automotive industry. Against popular belief, the application of generative AI (and large language models) will not solve the problem. On the contrary, it risks automating complex processes in the same unfamiliar language and creating documents to serve process overhead, rather than engineering development. This paper presents inefficiencies in the current state-of-the art processes used in the automotive sector and proposes a structured approach that increases the efficiency of automotive software development. It does so by documenting and implementing development processes based on how engineers actually perform their work. In the second step the adjustments that are necessary to ensure compliance of the product with industry standards are made. Such an approach produces efficient, compact and compliant process definition.
Weber, MatthiasKmiec, MateuszRomijn, MarcelNedkov, Detelin
The proven usefulness of large language models (LLMs) as tools for software development and the recent rapid increase in their capabilities have made it possible and attractive to extend their scope of application to almost all tasks in the engineering of complex and even safety-critical systems. While these tools promise substantial efficiency gains and improved engineering productivity, they remain prone to errors, and the generated artifacts may not meet the stringent quality requirements for safety-critical systems. In this paper, we systematically analyze potential applications of LLMs throughout the engineering lifecycle of safety-critical systems and identify associated risks as well as practical approaches to risk mitigation. We classify LLM-supported use cases according to LLM autonomy, impact, and artifact observability, and compare the corresponding mitigation strategies with established approaches used for traditional engineering automation. In addition, we examine the cultural and psychological aspects influencing trust in LLM-based engineering tools and the risks of both over-reliance and unwarranted rejection. Our analysis shows that LLMs can provide substantial benefits as engineering support tools, but they also represent a significant source of development risk if applied without appropriate safeguards. Based on these findings, we propose guidelines for responsibly using LLM-based tools in the engineering of safety-critical systems.
Thomas, CarstenWagner, Michael
Understanding the fluid flow behavior over and into narrow gaps is crucial for many industrial applications, particularly in the automotive sector. Evaluating the potential of water ingress into narrow pathways and towards components is of great importance to design the water management of such components. The employment of CFD simulations supports the evaluation of potential water ingress into such gaps. Lagrangian based tools are used in a variety of simulation scenarios of fluid flow, especially due to their ability to easily simulate free surfaces with strong curvatures. In our previous work, a validated simulation setup was developed using the meshless simulation tool MESHFREE from Fraunhofer ITWM [8] for simulating water entering small gaps. Especially for industrial use cases, the computation time of several days is too expensive. Thus, we enhanced this approach to a fast and robust CFD simulation that realizes industrial use cases within appropriate time. The development was conducted in two stages. First, the previously validated simulation method was analyzed with respect to different parameters (e.g. parameters influencing time step sizes) in a simplified benchmark case. This allowed for an initial assessment of their effects on computation time, accuracy, and robustness. Second, the improved parameter configuration was then further optimized for industrial applications to maximize performance across these criteria. The results demonstrate great potential in reducing the computation time. These findings will contribute to improving future work on modeling water pathways inside a vehicle.
Zrnic, DinoKonstantinovics, AthenaKospach, AlexanderRugerri, EvelynLoy, MichaelBäder, DirkMichel, Isabel
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 seamless integration with the open-source Woodpecker EV platform at the University of Detroit Mercy. The affordability and open-source nature of the framework offer a practical alternative to proprietary tools, while also enabling future adaptation to diverse automotive contexts.
Pries, AndrewMohammad, Utayba
In a few extreme customer abuse load cases such as curb impact and potholes, automotive structures see non-linear (plastic) deformations as well as large rigid body motion. The load cases can be simulated by a few tools: crash analysis tools such as LS-Dyna, non-linear structure analysis tools, or multi-body dynamics (MBD) analysis tools like Ansys Motion. The three simulation tools have pros and cons, respectively. In this study, a curb impact simulation was performed using the multi-body dynamic approach with nonlinear structural analysis capabilities included in Ansys Motion. The tool demonstrated the simulation was completed faster than other MBD tools due to smartly recycling the system Jacobian matrix when structural deformation was not significant. The results were compared with structural analysis and correlated reasonably well. The post-impact suspension alignment changes can also be simulated for reviewing design requirements. This approach proposes a new way to simulate customer abuse load cases, where only a part of vehicle system get significantly damaged such as curb impact and pothole simulations.
Hong, Hyung-JooKim, Wangoo
Military tactical vehicles are increasingly incorporating anti-idle kits as a method to reduce fuel consumption. The larger battery pack associated with the anti-idle kit has the potential to provide new capabilities to the warfighter, who can use the battery pack to power pieces of equipment. This study analyzes a set of these new capabilities derived from the U.S. Army Universal Task List, supplemented with user interviews and doctrinal analysis. These capabilities include powering dismounted soldier systems, counter-drone and surveillance equipment, mobile refrigeration for medical applications, field maintenance tools, and mobile food services. The study then uses geolocation data collected from the U.S. Army’s National Training Center to model daily fuel consumption for soldiers performing each of these activities. The model was subsequently adapted to incorporate an anti-idle kit, revealing significant reductions in fuel usage. The analysis uses the results to define common functional requirements and inform the conceptual design of a modular kit that integrates with anti-idle systems to enable new capabilities, thereby allowing vehicles to serve as mobile energy platforms in addition to their traditional role of providing mobility.
Lusian, TrevonteMummert, TaigeKaiser, CalebGreer, MichaelBlack, NathanielOng, BennettTapahonso, EugeneMittal, Vikram
This document is a guideline for format, structure and content for ground support equipment (GSE) technical manuals. This document focuses on requirements specific to the GSE industry and does not cover general technical publication practices. Additional standards for GSE and for manufacturer’s publications exist and may add requirements beyond what is covered in this standard. This may include EU Directive 2006/42/EC. This document is written in specific terms by intention, and conforms to recognized practices in the industry. When the word SHALL is used in this standard, it indicates a requirement that must be adhered to in total and does not allow for variance. When the word SHOULD is used, it indicates a recommended practice which allows the manual writer to use discretionary judgment. This document does not apply to electronic test equipment.
AGE-3 Aircraft Ground Support Equipment Committee
AE-8C2 Terminating Devices and Tooling Committee
Off-highway equipment operates in an environment defined by extremes - extreme loads, extreme duty cycles, extreme temperatures and extreme expectations. OEMs and fleet operators face mounting pressure to deliver more power, more uptime and more precision from platforms that are becoming increasingly compact, intelligent and complex. Whether the task is hauling, lifting, dumping, clearing or moving materials, the equipment must deliver consistent, reliable performance without compromise. This pressure is reshaping the mobile-hydraulic ecosystem. The industry is steadily shifting away from piecemeal systems and toward integrated, intelligent power architectures that maximize efficiency across the entire vehicle. Leaders in this space, Eaton among them, demonstrate how a system-level approach to PTOs, hydraulic pumps and control valves is enabling a new generation of off-highway innovation.
Bogdan, Corneliu
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